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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Transpl Int</journal-id>
<journal-title>Transplant International</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Transpl Int</abbrev-journal-title>
<issn pub-type="epub">1432-2277</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">12312</article-id>
<article-id pub-id-type="doi">10.3389/ti.2024.12312</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Health Archive</subject>
<subj-group>
<subject>Systematic Review and Meta-Analysis</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Prevalence of Musculoskeletal and Metabolic Disorders in Kidney Transplant Recipients: A Systematic Review and Meta-Analysis</article-title>
<alt-title alt-title-type="left-running-head">Herreros-Carretero et al.</alt-title>
<alt-title alt-title-type="right-running-head">Disorders After Kidney Transplant</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Herreros-Carretero</surname>
<given-names>&#xc1;lvaro</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2559098/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Berlanga-Mac&#xed;as</surname>
<given-names>Carlos</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2551775/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Mart&#xed;nez-Vizca&#xed;no</surname>
<given-names>Vicente</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Torres-Costoso</surname>
<given-names>Ana</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pascual-Morena</surname>
<given-names>Carlos</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hern&#xe1;ndez-Castillejo</surname>
<given-names>Luis Enrique</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Sequ&#xed;-Dom&#xed;nguez</surname>
<given-names>Irene</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Garrido-Miguel</surname>
<given-names>Miriam</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Facultad de Enfermer&#xed;a</institution>, <institution>Universidad de Castilla-La Mancha</institution>, <addr-line>Albacete</addr-line>, <country>Spain</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Health and Social Research Center</institution>, <institution>Universidad de Castilla-La Mancha</institution>, <addr-line>Cuenca</addr-line>, <country>Spain</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Investigaci&#xf3;n en Cuidados de la Salud Cardiovascular (CARVASCARE)</institution>, <institution>Centro de Estudio Sociosanitarios</institution>, <institution>Universidad de Castilla-La Mancha</institution>, <addr-line>Cuenca</addr-line>, <country>Spain</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Facultad de Ciencias de la Salud</institution>, <institution>Universidad Aut&#xf3;noma de Chile</institution>, <addr-line>Talca</addr-line>, <country>Chile</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS)</institution>, <addr-line>Cuenca</addr-line>, <country>Spain</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Facultad de Fisioterapia y Enfermer&#xed;a</institution>, <institution>Universidad de Castilla-La Mancha</institution>, <addr-line>Toledo</addr-line>, <country>Spain</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Complejo Hospitalario Universitario de Albacete</institution>, <addr-line>Albacete</addr-line>, <country>Spain</country>
</aff>
<author-notes>
<corresp id="c001">&#x2a;Correspondence: Carlos Berlanga-Mac&#xed;as, <email>carlos.berlanga@uclm.es</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>24</day>
<month>04</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>37</volume>
<elocation-id>12312</elocation-id>
<history>
<date date-type="received">
<day>26</day>
<month>10</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>08</day>
<month>04</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Herreros-Carretero, Berlanga-Mac&#xed;as, Mart&#xed;nez-Vizca&#xed;no, Torres-Costoso, Pascual-Morena, Hern&#xe1;ndez-Castillejo, Sequ&#xed;-Dom&#xed;nguez and Garrido-Miguel.</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Herreros-Carretero, Berlanga-Mac&#xed;as, Mart&#xed;nez-Vizca&#xed;no, Torres-Costoso, Pascual-Morena, Hern&#xe1;ndez-Castillejo, Sequ&#xed;-Dom&#xed;nguez and Garrido-Miguel</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction:</title>
<p>Musculoskeletal disorders could be associated with metabolic disorders that are common after kidney transplantation, which could reduce the quality of life of patients. The aim of this study was to assess the prevalence of both musculoskeletal and metabolic disorders in kidney transplant patients.</p>
</sec>
<sec>
<title>Methods:</title>
<p>MEDLINE, CINAHL, Cochrane Library, EMBASE and Web of Science were searched from their inception up to June 2023. DerSimonian and Laird random-effects method was used to calculate pooled prevalence estimates and their 95% confidence intervals (CIs).</p>
</sec>
<sec>
<title>Results:</title>
<p>21,879 kidney transplant recipients from 38 studies were analysed. The overall proportion of kidney transplant patients with musculoskeletal disorders was 27.2% (95% CI: 18.4&#x2013;36.0), with low muscle strength (64.5%; 95% CI: 43.1&#x2013;81.3) being the most common disorder. Otherwise, the overall proportion of kidney transplant patients with metabolic disorders was 37.6% (95% CI: 21.9&#x2013;53.2), with hypovitaminosis D (81.8%; 95% CI: 67.2&#x2013;90.8) being the most prevalent disorder.</p>
</sec>
<sec>
<title>Conclusion:</title>
<p>The most common musculoskeletal disorders were low muscle strength, femoral osteopenia, and low muscle mass. Hypovitaminosis D, hyperparathyroidism, and hyperuricemia were also the most common metabolic disorders. These disorders could be associated with poorer quality of life in kidney transplant recipients.</p>
</sec>
<sec>
<title>Systematic Review Registration:</title>
<p>
<ext-link ext-link-type="uri" xlink:href="https://www.crd.york.ac.uk/prospero/">https://www.crd.york.ac.uk/prospero/</ext-link>, identifier [CRD42023449171].</p>
</sec>
</abstract>
<abstract abstract-type="graphical">
<title>Graphical Abstract</title>
<p>
<graphic xlink:href="TI_ti-2024-12312_wc_abs.tif" position="anchor"/>
</p>
</abstract>
<kwd-group>
<kwd>renal transplant</kwd>
<kwd>musculoskeletal</kwd>
<kwd>metabolic</kwd>
<kwd>proportion</kwd>
<kwd>meta-analysis</kwd>
</kwd-group>
<contract-num rid="cn001">RD21/0016/0025 RD12/0005/0009</contract-num>
<contract-sponsor id="cn001">Ministerio de Econom&#xed;a y Competitividad<named-content content-type="fundref-id">10.13039/501100003329</named-content>
</contract-sponsor>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Renal transplantation represents the best therapy for patients diagnosed with end-stage renal disease. Major advances in surgical techniques and immunosuppressive treatment have led to a substantial improvement in the survival of these patients over the last few decades, resulting in a higher quality of life and lower treatment-related costs compared to dialysis [<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>]. This surgical procedure involves the replacement of a healthy kidney, either from a living or deceased donor, in a patient whose kidneys are not functioning properly [<xref ref-type="bibr" rid="B1">1</xref>]. According to the Global Observatory on Donation and Transplantation (GODT3), a total of 65,668 kidney transplants were performed worldwide in 2021, making the kidney commonly the most transplanted organ [<xref ref-type="bibr" rid="B3">3</xref>].</p>
<p>Despite the improvement in the patient&#x2019;s clinical status compared to the patient&#x2019;s previous disease status, this therapy does not imply a cure [<xref ref-type="bibr" rid="B4">4</xref>]. The evolution of kidney transplant recipients will depend fundamentally on the use of immunosuppressive drugs, the origin of the transplanted kidney, the characteristics of the patient and several events that may occur in the post-transplant period [<xref ref-type="bibr" rid="B1">1</xref>], which pose certain risks to the health and quality of life of the transplant recipient. These post-transplant events include renal, infectious, urological, surgical, cardiovascular, and cerebrovascular complications, side effects of the drugs used to prevent rejection, and metabolic disorders [<xref ref-type="bibr" rid="B1">1</xref>].</p>
<p>In relation to the above, there are several metabolic disorders, such as hypercalcemia, hypophosphatemia, hyperparathyroidism, and hypovitaminosis D, among others, which are common in these patients and have the potential to cause loss of bone mineral density (BMD), as occurs with the use of glucocorticoids, whose doses are higher immediately after transplantation [<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>]. This loss of BMD leads to several musculoskeletal disorders that can affect the quality of life of transplant patients and need to be controlled.</p>
<p>Musculoskeletal disorders include a group of pathologies suffered by many patients after surgery, the exact prevalence of which is not yet well known [<xref ref-type="bibr" rid="B6">6</xref>]. This group includes disorders such as osteopenia, osteoporosis, and sarcopenia, which involve both a reduction in bone density and a reduction in strength and muscle mass, respectively [<xref ref-type="bibr" rid="B7">7</xref>]. Although it is a common complication in these patients, involving the loss of bone and muscle mass, especially in the first months after transplantation, both diagnosis and treatment to prevent these pathologies are still inadequate [<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>]. Furthermore, there is a lack of studies that accurately synthesize and estimate the proportion of musculoskeletal and metabolic disorders in renal transplant patients. Therefore, the aim of this study was to carry out a systematic review and meta-analysis to determine the prevalence of musculoskeletal disorders and their related metabolic disorders in kidney transplant patients.</p>
</sec>
<sec sec-type="methods" id="s2">
<title>Methods</title>
<p>This systematic review adhered to the Cochrane Collaboration Handbook, the Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines, and the &#x201c;Preferred Reporting Items for Systematic Reviews and Meta-Analysis&#x201d; (PRISMA) guidelines [<xref ref-type="bibr" rid="B10">10</xref>]. This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO) with the registration number (CRD42023449171).</p>
<sec id="s2-1">
<title>Search Strategy</title>
<p>A systematic search in MEDLINE (via PubMed), CINAHL, Cochrane Library, EMBASE (via Scopus), and Web of Science (WOS) was conducted from inception to June 2023. Gray literature and the references of selected studies were also reviewed to identify additional studies. The search strategy combined the following terms using Boolean operators: &#x201c;post-kidney transplant,&#x201d; &#x201c;post-renal transplant,&#x201d; &#x201c;kidney transplant,&#x201d; &#x201c;renal transplant,&#x201d; &#x201c;musculoskeletal,&#x201d; &#x201c;muscular pain,&#x201d; &#x201c;muscle pain,&#x201d; sarcopenia, fibromyalgia, myopathy, &#x201c;joint pain,&#x201d; fracture, fragility, &#x201c;bone pain syndrome,&#x201d; &#x201c;bone syndrome,&#x201d; &#x201c;bone pain,&#x201d; &#x201c;bone disease,&#x201d; &#x201c;bone disorder,&#x201d; &#x201c;lower limb pain,&#x201d; hyperparathyroidism, hypophosphatemia, gout, hyperuricemia, arthritis, &#x201c;bone loss,&#x201d; osteoporosis, osteopenia, osteomalacia, &#x201c;mineral disorder,&#x201d; hypercalcemia, &#x201c;vitamin D,&#x201d; &#x201c;hypovitaminosis D,&#x201d; &#x201c;vitamin D deficiency.&#x201d; The references of the included studies were also checked. If the full text of a study was not available, the authors of the study were contacted. The systematic search was conducted independently by two investigators (AH-C and MG-M). The detailed search strategy is available in <xref ref-type="sec" rid="s10">Supplementary Table S1</xref>.</p>
</sec>
<sec id="s2-2">
<title>Eligibility Criteria</title>
<p>Observational studies analysing musculoskeletal and metabolic disorders developed in kidney transplant patients were included. The inclusion criteria were as follows: 1) population: adult patients over 18&#xa0;years of age; 2) study design: cross-sectional or baseline data from longitudinal studies without language restriction; and 3) outcome: primary outcomes including prevalence of musculoskeletal or metabolic disorders in kidney transplant recipients. Exclusion criteria were as follows: 1) ineligible publication types (clinical trials, literature reviews, commentaries, or letters to the editor); 2) patients with other previous nonrenal transplants; 3) pregnant or breastfeeding women; and 4) no access to full text.</p>
</sec>
<sec id="s2-3">
<title>Data Extraction</title>
<p>After selecting the studies that met the inclusion criteria, the following data were collected and described in a descriptive table (<xref ref-type="table" rid="T1">Table 1</xref>): (a) first author and year of publication; (b) country; (c) study design; and (d) sample characteristics (year of transplantation, number of participants, age, and sex); and (e) outcome analysed. If more than one study provided data on the same sample, the study with the most detailed results and/or with the largest sample size was selected for data synthesis.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Characteristics of the studies included (<italic>n</italic> &#x3d; 38).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Author and year</th>
<th rowspan="2" align="center">Country</th>
<th rowspan="2" align="center">Study design</th>
<th colspan="5" align="center">Sample characteristics</th>
<th rowspan="2" align="center">Outcome (prevalence)</th>
</tr>
<tr>
<th align="center">Transplant year</th>
<th align="center">n</th>
<th align="center">Age and gender (% women)</th>
<th align="center">Time since transplant</th>
<th align="center">Time on haemodialysis prior to transplant</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="3" align="left">Alagoz S. et al. [<xref ref-type="bibr" rid="B11">11</xref>] 2019</td>
<td rowspan="3" align="left">Turkey</td>
<td rowspan="3" align="left">Retrospective longitudinal</td>
<td rowspan="3" align="center">2002&#x2013;2012</td>
<td rowspan="3" align="center">176</td>
<td rowspan="3" align="center">32.9 &#xb1; 11.8 (38.1)</td>
<td align="left">1&#xa0;month</td>
<td rowspan="3" align="left">33.8 &#xb1; 33.1&#xa0;months</td>
<td align="left">Hypercalcemia (18.2%) Hypophosphatemia (33.3%) Hyperparathyroidism (45.3%)</td>
</tr>
<tr>
<td align="left">12&#xa0;months</td>
<td align="left">Hypercalcemia (17.2%) Hypophosphatemia (8.6%) Hyperparathyroidism (29.4%)</td>
</tr>
<tr>
<td align="left">60&#xa0;months</td>
<td align="left">Hypercalcemia (13.2%) Hypophosphatemia (11.4%) Hyperparathyroidism (9.2%)</td>
</tr>
<tr>
<td align="left">Amin T. et al. [<xref ref-type="bibr" rid="B12">12</xref>] 2016</td>
<td align="left">Australia</td>
<td align="left">Cross-sectional</td>
<td align="center">1971&#x2013;2011</td>
<td align="center">679</td>
<td align="center">55 &#xb1; 13 (39)</td>
<td align="left">&#x2265;3 months</td>
<td align="left">28.8 &#xb1; 24 months</td>
<td align="left">Hypercalcemia (15%)</td>
</tr>
<tr>
<td rowspan="2" align="left">Batteux B. et al. [<xref ref-type="bibr" rid="B13">13</xref>] 2020</td>
<td rowspan="2" align="left">France</td>
<td rowspan="2" align="left">Prospective longitudinal</td>
<td rowspan="2" align="center">2012&#x2013;2018</td>
<td rowspan="2" align="center">310</td>
<td rowspan="2" align="center">51.1 &#xb1; 12.8 (37.4)</td>
<td rowspan="2" align="left">1&#xa0;month</td>
<td rowspan="2" align="left">30&#xa0;months</td>
<td align="left">Osteopenia: lumbar area (34.5%); femoral area (53.5%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (6.1%); femoral area (10%)</td>
</tr>
<tr>
<td align="left">Berga JK. Et al [<xref ref-type="bibr" rid="B14">14</xref>]. 2010</td>
<td align="left">Spain</td>
<td align="left">Retrospective longitudinal</td>
<td align="center">&#x2014;</td>
<td align="center">110</td>
<td align="center">50.2 &#xb1; 11 (53)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">Hypovitaminosis D (96.4%): insufficiency (43.6%), deficiency (52.7%)</td>
</tr>
<tr>
<td rowspan="3" align="left">Braga Jr JWR. et al. [<xref ref-type="bibr" rid="B15">15</xref>] 2006</td>
<td rowspan="3" align="left">Brazil</td>
<td rowspan="3" align="left">Cross-sectional</td>
<td rowspan="3" align="center">2000</td>
<td rowspan="3" align="center">191</td>
<td rowspan="3" align="center">44.8 &#xb1; 0.8 (50.8)</td>
<td rowspan="3" align="left">87 &#xb1; 3.7&#xa0;months</td>
<td rowspan="3" align="left">46.48 &#xb1; 3.03&#xa0;months</td>
<td align="left">Osteopenia: lumbar area (32.5%); femoral area (33%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (11.5%); femoral area (11%)</td>
</tr>
<tr>
<td align="left">Fractures (24.1%)</td>
</tr>
<tr>
<td rowspan="3" align="left">Chan W. et al. [<xref ref-type="bibr" rid="B16">16</xref>] 2019</td>
<td rowspan="3" align="left">United Kingdom</td>
<td rowspan="3" align="left">Prospective longitudinal</td>
<td rowspan="3" align="center">2010&#x2013;2013</td>
<td rowspan="3" align="center">128</td>
<td rowspan="3" align="center">49 &#xb1; 15 (44)</td>
<td rowspan="3" align="left">60 (12&#x2013;132)&#xa0;months</td>
<td rowspan="3" align="left">&#x2014;</td>
<td align="left">Sarcopenia (28.9%)</td>
</tr>
<tr>
<td align="left">Low muscle strength (64.1%)</td>
</tr>
<tr>
<td align="left">Low muscle mass (35.9%)</td>
</tr>
<tr>
<td align="left">Conley E. et al. [<xref ref-type="bibr" rid="B17">17</xref>] 2008</td>
<td align="left">United States</td>
<td align="left">Retrospective longitudinal</td>
<td align="center">1998&#x2013;2006</td>
<td align="center">554</td>
<td align="center">46.3 &#xb1; 0.5 (42.2)</td>
<td align="left">14&#xa0;months</td>
<td align="left">&#x2014;</td>
<td align="left">Fractures (13%)</td>
</tr>
<tr>
<td align="left">Einollahi E. et al. [<xref ref-type="bibr" rid="B18">18</xref>] 2013</td>
<td align="left">Iran</td>
<td align="left">Cross-sectional</td>
<td align="center">2008&#x2013;2011</td>
<td align="center">4,217</td>
<td align="center">38 &#xb1; 15 (36)</td>
<td align="left">60&#xa0;months</td>
<td align="left">&#x2014;</td>
<td align="left">Hyperuricemia (31.8%)</td>
</tr>
<tr>
<td rowspan="4" align="left">Evenepoel P. et al. [<xref ref-type="bibr" rid="B19">19</xref>] 2019</td>
<td rowspan="4" align="left">Belgium</td>
<td rowspan="4" align="left">Cross-sectional</td>
<td rowspan="4" align="center">2006&#x2013;2013</td>
<td rowspan="4" align="center">518</td>
<td rowspan="4" align="center">54.7 &#xb1; 12.8 (39.4)</td>
<td rowspan="4" align="left">&#x3e;2&#xa0;weeks</td>
<td rowspan="4" align="left">&#x2014;</td>
<td align="left">Hypovitaminosis (38.4%): insufficiency (35.1%); deficiency (3.3%)</td>
</tr>
<tr>
<td align="left">Osteopenia: lumbar area (8.1%); femoral area (55%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (23.7%); femoral area (22%)</td>
</tr>
<tr>
<td align="left">Fractures (7.3%)</td>
</tr>
<tr>
<td rowspan="4" align="left">F&#xe9;rnandez Castillo R. et al. [<xref ref-type="bibr" rid="B20">20</xref>] 2018</td>
<td rowspan="4" align="left">Spain</td>
<td rowspan="4" align="left">Cross-sectional</td>
<td rowspan="4" align="center">&#x2014;</td>
<td rowspan="4" align="center">119</td>
<td rowspan="4" align="center">&#x2212;(41.2)</td>
<td rowspan="2" align="left">6&#xa0;months</td>
<td rowspan="4" align="left">&#x2014;</td>
<td align="left">Osteopenia: lumbar area (32.9%); femoral area (49.3%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (30.1%); femoral area (15.1%)</td>
</tr>
<tr>
<td rowspan="2" align="left">12&#xa0;months</td>
<td align="left">Osteopenia: lumbar area (38.4%); femoral area (51.5%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (30.8%); femoral area (16.7%)</td>
</tr>
<tr>
<td rowspan="3" align="left">Gregorini M. et al. [<xref ref-type="bibr" rid="B21">21</xref>] 2017</td>
<td rowspan="3" align="left">Italy</td>
<td rowspan="3" align="left">Cross-sectional</td>
<td rowspan="3" align="center">2000&#x2013;2016</td>
<td rowspan="3" align="center">297</td>
<td rowspan="3" align="center">55.5 &#xb1; 12 (34.7)</td>
<td rowspan="3" align="left">24&#xa0;months</td>
<td rowspan="3" align="left">&#x2014;</td>
<td align="left">Osteopenia: lumbar area (40.4%); femoral area (50.2%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (13.8%); femoral area (20.9%)</td>
</tr>
<tr>
<td align="left">Fractures (12.1%)</td>
</tr>
<tr>
<td rowspan="4" align="left">Hamidian Jahromi A. et al. [<xref ref-type="bibr" rid="B22">22</xref>] 2009</td>
<td rowspan="4" align="left">England</td>
<td rowspan="4" align="left">Prospective longitudinal</td>
<td rowspan="4" align="center">2000&#x2013;2002</td>
<td rowspan="4" align="center">121</td>
<td rowspan="4" align="center">35.5 &#xb1; 12.5 (30.6)</td>
<td rowspan="2" align="left">3&#xa0;months</td>
<td rowspan="4" align="left">17.4 &#xb1; 6&#xa0;months</td>
<td align="left">Hypercalcemia (17.4%)</td>
</tr>
<tr>
<td align="left">Hyperparathyroidism (9.9%)</td>
</tr>
<tr>
<td rowspan="2" align="left">12&#xa0;months</td>
<td align="left">Hypercalcemia (5.7%)</td>
</tr>
<tr>
<td align="left">Hyperparathyroidism (5.7%)</td>
</tr>
<tr>
<td align="left">Jerman A. et al. [<xref ref-type="bibr" rid="B23">23</xref>] 2017</td>
<td align="left">Slovenia</td>
<td align="left">Cross-sectional</td>
<td align="center">1976&#x2013;2011</td>
<td align="center">507</td>
<td align="center">54.3 &#xb1; 12 (45)</td>
<td align="left">116.4&#xa0;months</td>
<td align="left">63.4 &#xb1; 43.6&#xa0;months</td>
<td align="left">Fractures (12.6%)</td>
</tr>
<tr>
<td rowspan="2" align="left">J&#xf8;rgensen HS. et al. [<xref ref-type="bibr" rid="B24">24</xref>] 2016</td>
<td rowspan="2" align="left">Norway</td>
<td rowspan="2" align="left">Cross-sectional</td>
<td rowspan="2" align="center">2006&#x2013;2011</td>
<td rowspan="2" align="center">701</td>
<td rowspan="2" align="center">52.2 &#xb1; 14.7 (32.4)</td>
<td rowspan="2" align="left">2.5&#xa0;months</td>
<td rowspan="2" align="left">13.8 (7.8&#x2013;26.3)&#xa0;months</td>
<td align="left">Osteopenia: lumbar area (35.7%); femoral area (51.8%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (16.8%); femoral area (26%)</td>
</tr>
<tr>
<td rowspan="2" align="left">Khosravi M. et al. [<xref ref-type="bibr" rid="B25">25</xref>] 2020</td>
<td rowspan="2" align="left">Iran</td>
<td rowspan="2" align="left">Cross-sectional</td>
<td rowspan="2" align="center">&#x2014;</td>
<td rowspan="2" align="center">148</td>
<td rowspan="2" align="center">43.8 &#xb1; 12.7 (48)</td>
<td rowspan="2" align="left">67.59 &#xb1; 42.66&#xa0;months</td>
<td rowspan="2" align="left">14.18 &#xb1; 16.05&#xa0;months</td>
<td align="left">Osteopenia: lumbar area (49.3%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (18.9%)</td>
</tr>
<tr>
<td align="left">Kim KM. et al. [<xref ref-type="bibr" rid="B26">26</xref>] 2010</td>
<td align="left">South Korea</td>
<td align="left">Cross-sectional</td>
<td align="center">1990&#x2013;2008</td>
<td align="center">356</td>
<td align="center">39.3 &#xb1; 10.3 (39.3)</td>
<td align="left">102.63 &#xb1; 27.25&#xa0;months</td>
<td align="left">&#x2014;</td>
<td align="left">Hyperuricemia (15.4%)</td>
</tr>
<tr>
<td align="left">Kosoku A. et al. [<xref ref-type="bibr" rid="B27">27</xref>] 2020</td>
<td align="left">Japan</td>
<td align="left">Cross-sectional</td>
<td align="center">&#x2014;</td>
<td align="center">210</td>
<td align="center">55 &#xb1; 10 (42)</td>
<td align="left">85 (43&#x2013;135)&#xa0;months</td>
<td align="left">19 (6&#x2013;67)&#xa0;months</td>
<td align="left">Sarcopenia (11%)</td>
</tr>
<tr>
<td rowspan="3" align="left">Limirio LS. et al. [<xref ref-type="bibr" rid="B28">28</xref>] 2019</td>
<td rowspan="3" align="left">Brazil</td>
<td rowspan="3" align="left">Cross-sectional</td>
<td rowspan="3" align="center">&#x2014;</td>
<td rowspan="3" align="center">127</td>
<td rowspan="3" align="center">47.6 &#xb1; 11.5 (31.5)</td>
<td rowspan="3" align="left">95.5 &#xb1; 78.2&#xa0;months</td>
<td rowspan="3" align="left">55.4 &#xb1; 43.5&#xa0;months</td>
<td align="left">Sarcopenia (50.4%)</td>
</tr>
<tr>
<td align="left">Low muscle strength (80.3%)</td>
</tr>
<tr>
<td align="left">Low muscle mass (61.4%)</td>
</tr>
<tr>
<td rowspan="2" align="left">L&#xf3;pez Ruiz ML. et al. [<xref ref-type="bibr" rid="B29">29</xref>] 2015</td>
<td rowspan="2" align="left">Spain</td>
<td rowspan="2" align="left">Cross-sectional</td>
<td rowspan="2" align="center">2002&#x2013;2009</td>
<td rowspan="2" align="center">306</td>
<td rowspan="2" align="center">46.9 &#xb1; 13.8 (37.6)</td>
<td rowspan="2" align="left">12&#xa0;months</td>
<td rowspan="2" align="left">&#x2014;</td>
<td align="left">Osteopenia: lumbar area (14.4%); femoral area (19.6%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (12.4%); femoral area (6.9%)</td>
</tr>
<tr>
<td align="left">Malheiro J. et al. [<xref ref-type="bibr" rid="B30">30</xref>] 2012</td>
<td align="left">Portugal</td>
<td align="left">Cross-sectional</td>
<td align="center">1983&#x2013;2010</td>
<td align="center">302</td>
<td align="center">49.6 &#xb1; 13.4 (39.4)</td>
<td align="left">91.2 (27.6&#x2013;170.4)&#xa0;months</td>
<td align="left">&#x2014;</td>
<td align="left">Hyperuricemia (42.1%)</td>
</tr>
<tr>
<td align="left">Marc&#xe9;n R. et al. [<xref ref-type="bibr" rid="B31">31</xref>] 2009</td>
<td align="left">Spain</td>
<td align="left">Cross-sectional</td>
<td align="center">&#x2014;</td>
<td align="center">509</td>
<td align="center">45.4 &#xb1; 14.5 (42)</td>
<td align="left">113 &#xb1; 76&#xa0;months</td>
<td align="left">&#x2014;</td>
<td align="left">Hypovitaminosis D (85.3%): insufficiency (47%); deficiency (38.3%)</td>
</tr>
<tr>
<td rowspan="3" align="left">Menna Barreto APM. et al. [<xref ref-type="bibr" rid="B32">32</xref>] 2019</td>
<td rowspan="3" align="left">Brazil</td>
<td rowspan="3" align="left">Cross-sectional</td>
<td rowspan="3" align="center">&#x2014;</td>
<td rowspan="3" align="center">185</td>
<td rowspan="3" align="center">50 &#xb1; 7 (43)</td>
<td rowspan="3" align="left">117 (32&#x2013;173)&#xa0;months</td>
<td rowspan="3" align="left">&#x2014;</td>
<td align="left">Sarcopenia (17.3%)</td>
</tr>
<tr>
<td align="left">Low muscle strength (45.9%)</td>
</tr>
<tr>
<td align="left">Low muscle mass (23.8%)</td>
</tr>
<tr>
<td rowspan="8" align="left">Muirhead N. et al. [<xref ref-type="bibr" rid="B33">33</xref>] 2014</td>
<td rowspan="8" align="left">Canada</td>
<td rowspan="8" align="left">Retrospective longitudinal</td>
<td rowspan="8" align="center">2003&#x2013;2008</td>
<td rowspan="8" align="center">1,000</td>
<td rowspan="8" align="center">50 &#xb1; 12.5 (35.6)</td>
<td rowspan="2" align="left">12&#xa0;months</td>
<td rowspan="8" align="left">&#x2014;</td>
<td align="left">Hypercalcemia (16.6%)</td>
</tr>
<tr>
<td align="left">Hyperparathyroidism (47.6%)</td>
</tr>
<tr>
<td rowspan="2" align="left">24&#xa0;months</td>
<td align="left">Hypercalcemia (13.6%)</td>
</tr>
<tr>
<td align="left">Hyperparathyroidism (51.1%)</td>
</tr>
<tr>
<td rowspan="2" align="left">36&#xa0;months</td>
<td align="left">Hypercalcemia (9.5%)</td>
</tr>
<tr>
<td align="left">Hyperparathyroidism (43.4%)</td>
</tr>
<tr>
<td rowspan="2" align="left">48&#xa0;months</td>
<td align="left">Hypercalcemia (10.1%)</td>
</tr>
<tr>
<td align="left">Hyperparathyroidism (39.3%)</td>
</tr>
<tr>
<td align="left">Ozkayar N. et al. [<xref ref-type="bibr" rid="B34">34</xref>] 2014</td>
<td align="left">Turkey</td>
<td align="left">Cross-sectional</td>
<td align="center">&#x2014;</td>
<td align="center">166</td>
<td align="center">37.9 &#xb1; 11.9 (41)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">Sarcopenia (20.5%)</td>
</tr>
<tr>
<td rowspan="2" align="left">Park WY. et al. [<xref ref-type="bibr" rid="B35">35</xref>] 2017</td>
<td rowspan="2" align="left">United Kingdom</td>
<td rowspan="2" align="left">Prospective longitudinal</td>
<td rowspan="2" align="center">2011&#x2013;2013</td>
<td rowspan="2" align="center">207</td>
<td rowspan="2" align="center">45 &#xb1; 11 (46.4)</td>
<td rowspan="2" align="left">12&#xa0;months</td>
<td rowspan="2" align="left">25.3&#xa0;months</td>
<td align="left">Osteopenia: femoral area (40.1%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: femoral area (47.3%)</td>
</tr>
<tr>
<td rowspan="3" align="left">Patel S. et al. [<xref ref-type="bibr" rid="B36">36</xref>] 2001</td>
<td rowspan="3" align="left">United Kingdom</td>
<td rowspan="3" align="left">Cross-sectional</td>
<td rowspan="3" align="center">1998</td>
<td rowspan="3" align="center">165</td>
<td rowspan="3" align="center">46 &#xb1; (42)</td>
<td rowspan="3" align="left">61.2&#xa0;months</td>
<td rowspan="3" align="left">18&#xa0;months</td>
<td align="left">Osteopenia: lumbar area (30.9%); femoral area (40.6%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (7.9%); femoral area (10.3%)</td>
</tr>
<tr>
<td align="left">Fractures (16.4%)</td>
</tr>
<tr>
<td rowspan="4" align="left">Savaj S. et al. [<xref ref-type="bibr" rid="B37">37</xref>] 2012</td>
<td rowspan="4" align="left">Iran</td>
<td rowspan="4" align="left">Cross-sectional</td>
<td rowspan="4" align="center">2010</td>
<td rowspan="4" align="center">113</td>
<td rowspan="4" align="center">46.1 &#xb1; 13.6 (51.3)</td>
<td rowspan="4" align="left">106.4 &#xb1; 77.0&#xa0;months</td>
<td rowspan="4" align="left">147.1 &#xb1; 92.8&#xa0;months</td>
<td align="left">Hyperparathyroidism (76.1%)</td>
</tr>
<tr>
<td align="left">Hypovitaminosis D (94.7%): insufficiency (49.6%). deficiency (45.1%)</td>
</tr>
<tr>
<td align="left">Osteopenia: lumbar area (52.2%); femoral area (36.3%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (12.4%); femoral area (45.1%)</td>
</tr>
<tr>
<td align="left">Schreiber W. et al. [<xref ref-type="bibr" rid="B38">38</xref>] 2020</td>
<td align="left">Switzerland</td>
<td align="left">Prospective longitudinal</td>
<td align="center">2008&#x2013;2009</td>
<td align="center">135</td>
<td align="center">51 &#xb1; 11 (33.3)</td>
<td align="left">6&#xa0;months</td>
<td align="left">&#x2014;</td>
<td align="left">Vitamin D deficiency (65.2%)</td>
</tr>
<tr>
<td rowspan="3" align="left">Segaud N. et al. [<xref ref-type="bibr" rid="B39">39</xref>] 2018</td>
<td rowspan="3" align="left">France</td>
<td rowspan="3" align="left">Prospective longitudinal</td>
<td rowspan="3" align="center">2005&#x2013;2011</td>
<td rowspan="3" align="center">259</td>
<td rowspan="3" align="center">49.7 &#xb1; 12.1 (37.1)</td>
<td rowspan="3" align="left">8.8 &#xb1; 1.9&#xa0;months</td>
<td rowspan="3" align="left">38.4&#xa0;months</td>
<td align="left">Osteopenia: femoral area (42.9%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: femoral area (40.9%)</td>
</tr>
<tr>
<td align="left">Fractures (10.8%)</td>
</tr>
<tr>
<td align="left">Simbolon FR. et al. [<xref ref-type="bibr" rid="B40">40</xref>] 2018</td>
<td align="left">Taiwan</td>
<td align="left">Retrospective longitudinal</td>
<td align="center">1997&#x2013;2010</td>
<td align="center">5,917</td>
<td align="center">45.1 &#xb1; 11.9 (48.6)</td>
<td align="left">32.4&#xa0;months</td>
<td align="left">&#x2014;</td>
<td align="left">Gout (8.8%)</td>
</tr>
<tr>
<td align="left">Stamp L. et al. [<xref ref-type="bibr" rid="B41">41</xref>] 2006</td>
<td align="left">New Zealand</td>
<td align="left">Cross-sectional</td>
<td align="center">2004</td>
<td align="center">202</td>
<td align="center">53 (31.9)</td>
<td align="left">&#x3e;36&#xa0;months</td>
<td align="left">&#x2014;</td>
<td align="left">Gout (23.3%)</td>
</tr>
<tr>
<td rowspan="5" align="left">Torres A. et al. [<xref ref-type="bibr" rid="B42">42</xref>] 2016</td>
<td rowspan="5" align="left">Spain</td>
<td rowspan="5" align="left">Cross-sectional</td>
<td rowspan="5" align="center">2008&#x2013;2010</td>
<td rowspan="5" align="center">727</td>
<td rowspan="5" align="center">55 &#xb1; 13.6 (39.9)</td>
<td rowspan="5" align="left">&#x3e;12&#xa0;months</td>
<td rowspan="5" align="left">67 &#xb1; 29&#xa0;months</td>
<td align="left">Hypercalcemia (6.5%)</td>
</tr>
<tr>
<td align="left">Hypophosphatemia (6.2%)</td>
</tr>
<tr>
<td align="left">Hyperparathyroidism (76.9%)</td>
</tr>
<tr>
<td align="left">Hypovitaminosis D (83.2%): insufficiency (50.8%); deficiency (32.5%)</td>
</tr>
<tr>
<td align="left">Fractures (14.6%)</td>
</tr>
<tr>
<td rowspan="5" align="left">Velioglu A. et al. [<xref ref-type="bibr" rid="B43">43</xref>] 2021</td>
<td rowspan="5" align="left">Turkey</td>
<td rowspan="5" align="left">Cross-sectional</td>
<td rowspan="5" align="center">2017&#x2013;2018</td>
<td rowspan="5" align="center">153</td>
<td rowspan="5" align="center">46.5 &#xb1; 11.9 (50.3)</td>
<td rowspan="5" align="left">86.4&#xa0;months</td>
<td rowspan="5" align="left">35&#xa0;months</td>
<td align="left">Hyperparathyroidism (52.9%)</td>
</tr>
<tr>
<td align="left">Hypovitaminosis D (68.8%): insufficiency (49.7%); deficiency (19%)</td>
</tr>
<tr>
<td align="left">Osteopenia: lumbar area (28.1%); femoral area (41.2%)</td>
</tr>
<tr>
<td align="left">Osteoporosis: lumbar area (7.2%); femoral area (7.8%)</td>
</tr>
<tr>
<td align="left">Fractures (43.4%)</td>
</tr>
<tr>
<td rowspan="2" align="left">Vilarta CF. Et al [<xref ref-type="bibr" rid="B44">44</xref>]. 2017</td>
<td rowspan="2" align="left">Brazil</td>
<td rowspan="2" align="left">Cross-sectional</td>
<td rowspan="2" align="center">&#x2014;</td>
<td rowspan="2" align="center">149</td>
<td rowspan="2" align="center">44 &#xb1; &#x2212;(56.4)</td>
<td rowspan="2" align="left">72&#xa0;months</td>
<td rowspan="2" align="left">&#x2014;</td>
<td align="left">Hypovitaminosis D (79.2%): insufficiency (37.6%); deficiency (41.6%)</td>
</tr>
<tr>
<td align="left">Fractures (10%)</td>
</tr>
<tr>
<td rowspan="4" align="left">Wang C. et al. [<xref ref-type="bibr" rid="B45">45</xref>] 2021</td>
<td rowspan="4" align="left">China</td>
<td rowspan="4" align="left">Cross-sectional</td>
<td rowspan="4" align="center">&#x2014;</td>
<td rowspan="4" align="center">216</td>
<td rowspan="4" align="center">41.5 &#xb1; 9.9 (27.8)</td>
<td rowspan="4" align="left">&#x2014;</td>
<td rowspan="4" align="left">15&#xa0;months</td>
<td align="left">Hypercalcemia (8.8%)</td>
</tr>
<tr>
<td align="left">Hypophosphatemia (3.7%)</td>
</tr>
<tr>
<td align="left">Hypovitaminosis D (78.7%): insufficiency (46.3%); deficiency (32.4%)</td>
</tr>
<tr>
<td align="left">Fractures (3.2%)</td>
</tr>
<tr>
<td rowspan="2" align="left">Weng SC. et al. [<xref ref-type="bibr" rid="B46">46</xref>] 2014</td>
<td rowspan="2" align="left">Taiwan</td>
<td rowspan="2" align="left">Prospective longitudinal</td>
<td rowspan="2" align="center">1999&#x2013;2013</td>
<td rowspan="2" align="center">880</td>
<td rowspan="2" align="center">48.7 &#xb1; 12.3 (46.8)</td>
<td rowspan="2" align="left">&#x2014;</td>
<td rowspan="2" align="left">&#x2014;</td>
<td align="left">Hyperuricemia (44.2%)</td>
</tr>
<tr>
<td align="left">Gout (17.7%)</td>
</tr>
<tr>
<td rowspan="3" align="left">Wolf M. et al. [<xref ref-type="bibr" rid="B47">47</xref>] 2016</td>
<td rowspan="3" align="left">United States</td>
<td rowspan="3" align="left">Prospective longitudinal</td>
<td rowspan="3" align="center">&#x2014;</td>
<td rowspan="3" align="center">246</td>
<td rowspan="3" align="center">52.8 &#xb1; 13.4 (36.7)</td>
<td rowspan="3" align="left">&#x2014;</td>
<td rowspan="3" align="left">42 &#xb1; 34.8&#xa0;months</td>
<td align="left">-Hypercalcemia (30.5%)</td>
</tr>
<tr>
<td align="left">-Hypophosphatemia (53.7%)</td>
</tr>
<tr>
<td align="left">-Hyperparathyroidism (89.4%)</td>
</tr>
<tr>
<td rowspan="4" align="left">Zhang K. et al. [<xref ref-type="bibr" rid="B48">48</xref>] 2015</td>
<td rowspan="4" align="left">China</td>
<td rowspan="4" align="left">Retrospective longitudinal</td>
<td rowspan="4" align="center">2008&#x2013;2011</td>
<td rowspan="4" align="center">573</td>
<td rowspan="4" align="center">41.4 &#xb1; 9.5 (31.6)</td>
<td align="left">1&#xa0;month</td>
<td rowspan="4" align="left">&#x2014;</td>
<td align="left">-Hyperuricemia (16.2%)</td>
</tr>
<tr>
<td align="left">3&#xa0;months</td>
<td align="left">-Hyperuricemia (24.1%)</td>
</tr>
<tr>
<td align="left">24&#xa0;months</td>
<td align="left">-Hyperuricemia (30.9%)</td>
</tr>
<tr>
<td align="left">36&#xa0;months</td>
<td align="left">-Hyperuricemia (42.8%)</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Two reviewers (AH-C and MG-M) independently conducted the data extraction, and disagreements were resolved by consensus or by a third reviewer (CB-M). Articles retrieved were imported and managed by Mendeley reference manager.</p>
</sec>
<sec id="s2-4">
<title>Methodological Quality Assessment</title>
<p>To assess the methodological quality of the studies included in this systematic review and meta-analysis, we used the Joanna Briggs Institute (JBI) tool <italic>&#x201c;Checklist for prevalence studies&#x201d;</italic> scale by Munn et al [<xref ref-type="bibr" rid="B49">49</xref>] for cross-sectional descriptive studies and the JBI tool <italic>&#x201c;Checklist for cohort studies&#x201d;</italic> scale by Moola et al [<xref ref-type="bibr" rid="B50">50</xref>] for longitudinal cohort studies. Both scales [<xref ref-type="bibr" rid="B49">49</xref>, <xref ref-type="bibr" rid="B50">50</xref>] consist of 9 and 11 items, respectively. They are scored as &#x201c;yes&#x201d; (1), &#x201c;no&#x201d; (0), &#x201c;not applicable&#x201d; (NA) and &#x201c;unclear&#x201d; (?). The final score for each study therefore ranged from 0 to 9 or 11. Depending on this score, each study was classified as having a low (&#x3e;7), moderate (4&#x2013;6) or high (1&#x2013;3) risk of bias [<xref ref-type="bibr" rid="B49">49</xref>, <xref ref-type="bibr" rid="B50">50</xref>].</p>
<p>Both the data extraction and the quality assessment were performed independently by two reviewers (AH-C and MG-M), and disagreements were resolved by consensus or by involving a third reviewer (CB-M).</p>
</sec>
<sec id="s2-5">
<title>Statistical Analysis and Data Synthesis</title>
<p>Pooled prevalence estimates with their respective 95% confidence intervals (CIs) were calculated for each subgroup of musculoskeletal disorders (sarcopenia, low muscle strength, and low muscle mass, osteopenia, osteoporosis, fractures, and gout) and metabolic disorders subgroup (hypercalcemia, hypophosphatemia, hyperparathyroidism, hyperuricemia, and hypovitaminosis D). In addition, the overall pooled prevalence of both musculoskeletal and metabolic disorders was also estimated. DerSimonian and Laird random-effects method [<xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B52">52</xref>] was used to calculate pooled prevalence estimates and their 95% CIs. Heterogeneity between studies was assessed using the <italic>I</italic>
<sup>2</sup> statistic [<xref ref-type="bibr" rid="B53">53</xref>] with values considered as follows: not important (0%&#x2013;40%), moderate (30%&#x2013;60%), substantial (50%&#x2013;90%) and considerable heterogeneity (75%&#x2013;100%). The significance value of the pooled effect size was estimated based on the 95% CI. Two-sided <italic>p</italic> values of .05 or less were considered significant.</p>
<p>We conducted a sensitivity analysis to determine the robustness of the summary estimates by removing each included study from the analysis one by one. Furthermore, meta-regression models were performed considering mean age, percentage of women, time on hemodialysis prior to transplant, and time since transplant to determine their influence on prevalence estimates. Due to the limited number of studies included (<italic>n</italic> &#x3c; 10) in each subgroup analysis, meta-regression analysis was only performed with the following outcome variables: osteopenia (lumbar area), osteopenia (femoral area), osteoporosis (lumbar area), osteoporosis (femoral area) and fractures.</p>
<p>Statistical analyses were performed using Stata SE software, version 15 (StataCorp) and Comprehensive Meta-Analysis V3. Global prevalence was estimated using the STATA metaprop statistical package.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>Study Selection</title>
<p>A total of 1,770 articles were retrieved from the bibliographic search. After removing duplicates, a total of 38 articles [<xref ref-type="bibr" rid="B11">11</xref>&#x2013;<xref ref-type="bibr" rid="B48">48</xref>] were selected for quantitative synthesis (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>PRISMA 2020 flowchart.</p>
</caption>
<graphic xlink:href="ti-37-12312-g001.tif"/>
</fig>
<sec id="s3-1-1">
<title>Characteristics of the Selected Studies</title>
<p>The characteristics of the studies selected for this systematic review and meta-analysis are detailed in <xref ref-type="table" rid="T1">Table 1</xref>. The study design was cross-sectional in 27 studies [<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B23">23</xref>&#x2013;<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B34">34</xref>&#x2013;<xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B41">41</xref>&#x2013;<xref ref-type="bibr" rid="B45">45</xref>] (71.1%) and longitudinal in 11 [<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B38">38</xref>&#x2013;<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B46">46</xref>&#x2013;<xref ref-type="bibr" rid="B48">48</xref>] (28.9%). All these articles were published between 2001 and 2021, and most of them were conducted in Europe [<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B29">29</xref>&#x2013;<xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B35">35</xref>, <xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B42">42</xref>] (44.7%), although there were also studies from Asia [<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B25">25</xref>&#x2013;<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B48">48</xref>] (31.6%), America [<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B47">47</xref>] (18.4%) and Oceania [<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B41">41</xref>] (5.3%).</p>
<p>A total of 21,879 patients (41.4% women) with a mean age of 45.4&#xa0;years were analysed in this study. The kidney transplants were performed between 1971 and 2018. The mean time since transplantation was 41.3&#xa0;months (3.4&#xa0;years), and the mean time on dialysis before transplantation was 36.08&#xa0;months (3&#xa0;years).</p>
<p>The musculoskeletal disorders analysed in this review were sarcopenia, low muscle strength and low muscle mass, osteopenia and osteoporosis, bone fractures and gout. The outcomes analysed for metabolic disorders were hypercalcemia, hypophosphatemia, hyperparathyroidism, hyperuricemia and hypovitaminosis D.</p>
</sec>
<sec id="s3-1-2">
<title>Study Quality</title>
<p>Of the cross-sectional studies (<xref ref-type="sec" rid="s10">Supplementary Table S2</xref>), 96.3% and 3.7% had a low and a moderate risk of bias, respectively. For longitudinal studies, 54.5% and 45.6% had a low and a moderate risk of bias, respectively (<xref ref-type="sec" rid="s10">Supplementary Table S3</xref>). Considering all the studies, 84.2% and 15.8% had a low and moderate risk of bias, respectively.</p>
</sec>
<sec id="s3-1-3">
<title>Main Results</title>
<p>A general estimate of the outcomes regarding both musculoskeletal and metabolic disorders is shown in <xref ref-type="fig" rid="F2">Figures 2</xref>, <xref ref-type="fig" rid="F3">3</xref>, respectively. Each outcome was also independently analysed and is shown in <xref ref-type="sec" rid="s10">Supplementary Figures S1&#x2013;S16</xref>. The overall proportion of kidney transplant patients with musculoskeletal disorders was 27.2 (95% CI: 18.4&#x2013;36.0; <italic>I</italic>
<sup>2</sup> &#x3d; 92.3%) (<xref ref-type="fig" rid="F2">Figure 2</xref>), and that with metabolic disorders was 37.6% (95% CI: 21.9&#x2013;53.2; <italic>I</italic>
<sup>2</sup> &#x3d; 97.8%) (<xref ref-type="fig" rid="F3">Figure 3</xref>).<list list-type="simple">
<list-item>
<p>(i) Musculoskeletal disorders</p>
<list list-type="simple">
<list-item>
<p>(a) Muscle disorders (sarcopenia, low muscle strength and low muscle mass): The prevalence of sarcopenia was analysed in five studies [<xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B34">34</xref>]. A total of 816 individuals were included, with an overall prevalence of 23.6% (95% CI: 13.2&#x2013;38.5; <italic>I</italic>
<sup>2</sup> &#x3d; 94.1) (<xref ref-type="sec" rid="s10">Supplementary Figure S1</xref>). Three studies [<xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B32">32</xref>], with 440 subjects, included the other two outcomes. For low muscle strength, the overall prevalence was 64.5% (95% CI: 43.1&#x2013;81.3; <italic>I</italic>
<sup>2</sup> &#x3d; 94.4), and the prevalence of low muscle mass was 39.5% (95% CI: 20.3&#x2013;62.6; <italic>I</italic>
<sup>2</sup> &#x3d; 95.3) (<xref ref-type="sec" rid="s10">Supplementary Figures S2, S3</xref>).</p>
</list-item>
<list-item>
<p>(b) Osteopenia and osteoporosis: Eleven articles [<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B43">43</xref>] investigated the prevalence in the lumbar area, and 12 [<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B35">35</xref>&#x2013;<xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B43">43</xref>] studied the prevalence in the femoral area, with 3,021 and 3,339 transplant recipients, respectively. The prevalence of osteopenia in the lumbar area was 30.7% (95% CI: 23.3&#x2013;39.3; <italic>I</italic>
<sup>2</sup> &#x3d; 95.1). In the femoral area, it was 42.6% (95% CI: 36.5&#x2013;48.8; <italic>I</italic>
<sup>2</sup> &#x3d; 91.9) (<xref ref-type="sec" rid="s10">Supplementary Figures S4, S5</xref>). For lumbar osteoporosis, the prevalence was 13.8% (95% CI: 10.4&#x2013;17.9; <italic>I</italic>
<sup>2</sup> &#x3d; 88.2). Finally, for the femoral area, the prevalence was 19.2% (95% CI: 13.4&#x2013;26.7; <italic>I</italic>
<sup>2</sup> &#x3d; 95.6) (<xref ref-type="sec" rid="s10">Supplementary Figures S6, S7</xref>).</p>
</list-item>
<list-item>
<p>(c) Fractures: Eleven articles [<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B42">42</xref>&#x2013;<xref ref-type="bibr" rid="B45">45</xref>] assessed this outcome. The prevalence in 3,736 patients was 13.1% (95% CI: 9.6&#x2013;18.5; <italic>I</italic>
<sup>2</sup> &#x3d; 93.1) (<xref ref-type="sec" rid="s10">Supplementary Figure S8</xref>).</p>
</list-item>
<list-item>
<p>(d) Gout: Three studies [<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B46">46</xref>] analysed the prevalence of this disorder in renal transplant recipients, including 6,999 participants, where the overall prevalence of gout was 15.4% (95% CI: 8.3&#x2013;26.9; <italic>I</italic>
<sup>2</sup> &#x3d; 97.3) (<xref ref-type="sec" rid="s10">Supplementary Figure S9</xref>).</p>
</list-item>
</list>
</list-item>
<list-item>
<p>(ii) Metabolic disturbances.</p>
<list list-type="simple">
<list-item>
<p>(a) Hypercalcaemia: Seven studies [<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B47">47</xref>] provided data on this disorder, with a total of 3,165 subjects analysed. The overall prevalence in this population was 15.7% (95% CI: 14.5&#x2013;17.0; <italic>I</italic>
<sup>2</sup> &#x3d; 91.3) (<xref ref-type="sec" rid="s10">Supplementary Figure S10</xref>).</p>
</list-item>
<list-item>
<p>(b) Hypophosphatemia: Four studies [<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B47">47</xref>] analysed the prevalence of hypophosphatemia among kidney transplant recipients. The overall prevalence of 1,365 individuals was 12.4% (95% CI: 4.3&#x2013;31.2; <italic>I</italic>
<sup>2</sup> &#x3d; 98.1) (<xref ref-type="sec" rid="s10">Supplementary Figure S11</xref>).</p>
</list-item>
<list-item>
<p>(c) Hyperparathyroidism: The prevalence of this disorder was obtained from seven studies [<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B47">47</xref>]. The overall prevalence obtained in this population of 2,536 subjects was 47.6% (95% CI: 31.3&#x2013;64.5; <italic>I</italic>
<sup>2</sup> &#x3d; 98.2) (<xref ref-type="sec" rid="s10">Supplementary Figure S12</xref>).</p>
</list-item>
<list-item>
<p>(d) Hyperuricemia: Hyperuricemia was analysed in five studies [<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B30">30</xref>, <xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B48">48</xref>], with a total of 6,328 subjects, with metabolic disorders having the largest population. The overall prevalence was 29.8% (95% CI: 23.8&#x2013;36.7; <italic>I</italic>
<sup>2</sup> &#x3d; 96.8) (<xref ref-type="sec" rid="s10">Supplementary Figure S13</xref>).</p>
</list-item>
<list-item>
<p>(e) Hypovitaminosis D: Eight studies [<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B42">42</xref>&#x2013;<xref ref-type="bibr" rid="B45">45</xref>] analysed the prevalence of this disorder. In this population of 2,495 people, the overall prevalence was 81.8% (95% CI: 67.2&#x2013;90.8; <italic>I</italic>
<sup>2</sup> &#x3d; 98.2), with this metabolic disorder being the most common finding (<xref ref-type="sec" rid="s10">Supplementary Figure S14</xref>). This alteration was divided into vitamin D insufficiency and vitamin D deficiency. For the former, the prevalence was 44.9% (95% CI: 40.1&#x2013;49.7; <italic>I</italic>
<sup>2</sup> &#x3d; 80.7), and for vitamin D deficiency, it was 32.9% (95% CI: 23.1&#x2013;44.4; <italic>I</italic>
<sup>2</sup> &#x3d; 96.3) (<xref ref-type="sec" rid="s10">Supplementary Figures S15, S16</xref>).</p>
</list-item>
</list>
</list-item>
</list>
</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Meta-analysis of the proportion of musculoskeletal disorders in kidney transplant recipients.</p>
</caption>
<graphic xlink:href="ti-37-12312-g002.tif"/>
</fig>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Meta-analysis of the proportion of metabolic disorders in kidney transplant recipients.</p>
</caption>
<graphic xlink:href="ti-37-12312-g003.tif"/>
</fig>
<p>These results obtained have been compared with the results of other studies [<xref ref-type="bibr" rid="B54">54</xref>&#x2013;<xref ref-type="bibr" rid="B61">61</xref>] that analyse the same variables in the general population (who have not received a kidney transplant). Among metabolic disturbances, the comparison is as follows: 14.9% vs. 0.8% (general population) for hypercalcemia, 58.0% vs. 0.8% for hyperparathyroidism, 31.2% vs. 13.3% for hyperuricemia, and 81.8% vs. 15.7% for hypovitaminosis D. Regarding musculoskeletal disorders, the differences are as follows: 23.6% vs. 15.5% for sarcopenia, 39.5% vs. 27.0% for low muscle mass, 30.7/42.6% (lumbar/femoral area) vs. 40.4% for osteopenia, 13.8/19.2% (lumbar/femoral area) vs. 18.3% for osteoporosis, 14.2% vs. 1.1% for fractures, and 15.4% vs. 1.1% for gout. This comparison is shown in detail in <xref ref-type="sec" rid="s10">Supplementary Tables S4, S5</xref>, and individually the comparison of each variable can be seen in <xref ref-type="sec" rid="s10">Supplementary Figures S17&#x2013;S26</xref>.</p>
</sec>
</sec>
<sec id="s3-2">
<title>Sensitivity and Meta-Regression Analysis</title>
<p>When the impact of individual studies was examined by removing studies from the analysis one by one, the estimate of the proportion of sarcopenia changed after removing the Limirio LS. sample [<xref ref-type="bibr" rid="B28">28</xref>] (from 23.6% to 19.1%); Menna Barreto ANP. [<xref ref-type="bibr" rid="B32">32</xref>] for low muscle strength (from 64.5% to 71.4%); Limirio LS. [<xref ref-type="bibr" rid="B28">28</xref>] for low muscle mass (from 39.5% to 29.1%); Wang C. [<xref ref-type="bibr" rid="B45">45</xref>] for fractures (from 13.10% to 16.0%), and Simbolon FR. [<xref ref-type="bibr" rid="B40">40</xref>] for gout (from 15.4% to 19.9%) (<xref ref-type="sec" rid="s10">Supplementary Table S6</xref>). On the other hand, regarding the estimated proportions of metabolic disorders, these were modified after removing the samples of Wolf M. [<xref ref-type="bibr" rid="B47">47</xref>] for hypercalcemia (from 15.7% to 13.0%) and hypophosphatemia (from 12.4% to 7.7%), and Evenepoel P. [<xref ref-type="bibr" rid="B19">19</xref>] for vitamin D deficiency (from 32.9% to 40.0%) (<xref ref-type="sec" rid="s10">Supplementary Table S7</xref>).</p>
<p>Meta-regression models showed that all the variables considered (age, %females, time since transplant and time on haemodialysis prior to transplant) influenced the prevalence estimates of the outcome variables analysed (<xref ref-type="sec" rid="s10">Supplementary Table S8</xref>).</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>The main objective of this systematic review and meta-analysis was to provide a complete synthesis of the prevalence of musculoskeletal disorders and metabolic disorders in kidney transplant patients. There is a wide range in the prevalence of metabolic disturbances and musculoskeletal disorders in this population. The most common metabolic disorders in this group of patients were hypovitaminosis D (81.8%), hyperparathyroidism (47.6%), and hyperuricemia (29.8%). Among the musculoskeletal disorders, the most common were low muscle strength (64.5%), femoral osteopenia (42.7%), and low muscle mass (39.5%).</p>
<p>Renal transplantation solves many problems of end-stage renal disease; however, certain metabolic disturbances may persist for some time. Hyperparathyroidism, hypercalcemia, hypophosphatemia, hypovitaminosis D, and hyperuricemia are common after transplantation, and they often occur simultaneously. In addition, together with other factors, they may be involved in the development of certain musculoskeletal disorders that affect the quality of life of the transplanted patient [<xref ref-type="bibr" rid="B62">62</xref>].</p>
<p>Despite the improvement in renal function after transplantation, hyperparathyroidism may develop due to a number of factors, including the high levels of parathyroid hormone (PTH) prior to transplantation, the prolonged period of renal disease and dialysis, the degree of hyperplasia of the parathyroid gland or the decrease in vitamin D [<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B62">62</xref>&#x2013;<xref ref-type="bibr" rid="B64">64</xref>]. PTH levels begin to decline during the first 3&#x2013;6&#xa0;months after the procedure, but according to the article published by Hassan et al [<xref ref-type="bibr" rid="B6">6</xref>], high PTH levels can still be found in 30%&#x2013;60% of patients 1&#xa0;year after transplantation [<xref ref-type="bibr" rid="B6">6</xref>]. This alteration is also associated with hypercalcemia and hypophosphatemia, among others, which could lead to loss of BMD [<xref ref-type="bibr" rid="B2">2</xref>].</p>
<p>Approximately 15% of patients with hyperparathyroidism also have hypercalcemia [<xref ref-type="bibr" rid="B65">65</xref>]. PTH increases blood calcium levels by transporting calcium from the bones into the blood, facilitating calcium reabsorption in the kidneys and its absorption in the digestive system [<xref ref-type="bibr" rid="B62">62</xref>]. However, it is not the only factor that allows an increase in blood calcium. The increase in vitamin D levels after transplantation also increases calcium absorption in the intestine, as well as the bone resorption that can occur after the procedure [<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B62">62</xref>]. It is important to emphasize that hypercalcaemia is not a cause of BMD loss but rather a consequence [<xref ref-type="bibr" rid="B62">62</xref>]. This alteration is reported in 5%&#x2013;15% of the transplanted population after the intervention, according to the article published by Bouquegneau et al [<xref ref-type="bibr" rid="B9">9</xref>], and is more common at 3&#x2013;6&#xa0;months, especially in patients with higher blood PTH levels [<xref ref-type="bibr" rid="B9">9</xref>]. This change may resolve in some patients 6&#x2013;8&#xa0;months after transplantation, but in others, it may take years [<xref ref-type="bibr" rid="B64">64</xref>]. Hypercalcemia may play a role in triggering nephrolithiasis, rejection, and dysfunction of the transplanted kidney [<xref ref-type="bibr" rid="B65">65</xref>].</p>
<p>Another change associated with hyperparathyroidism is hypophosphatemia. Like calcium, PTH is involved in the regulation of phosphorus in the body [<xref ref-type="bibr" rid="B62">62</xref>]. In addition, there is another hormone in the body called fibroblast growth factor 23 (FGF-23), which has been identified as the main phosphorus-regulating factor in the body. This hormone is secreted by bone cells, and its production is partially stimulated by PTH. It has also been described that excess FGF-23 [<xref ref-type="bibr" rid="B66">66</xref>] is produced in bone mineralization disorders. These two hormones contribute to a decrease in the reabsorption of phosphorus in the kidney, which is why kidney transplant recipients have low levels of this metabolite [<xref ref-type="bibr" rid="B64">64</xref>]. This alteration is common during the first 3&#xa0;months after transplantation, and according to the study by Bouquegneau et al [<xref ref-type="bibr" rid="B9">9</xref>], it occurs in 50% of transplant recipients and stabilizes after 6&#x2013;12&#xa0;months [<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B67">67</xref>]. This alteration is associated with a decrease in osteoblast activity, resulting in deficient bone mineralization [<xref ref-type="bibr" rid="B9">9</xref>].</p>
<p>Vitamin D metabolism is also affected after renal transplantation. Hypovitaminosis D is associated with immunosuppressive therapy, residual renal function after transplantation, malabsorption, poor diet or reduced exposure to sunlight [<xref ref-type="bibr" rid="B62">62</xref>, <xref ref-type="bibr" rid="B64">64</xref>]. The vitamin D status of the body is tested by blood levels of calcidiol, a precursor of this vitamin; hypovitaminosis D is therefore understood to be a blood level of calcidiol of less than 30&#xa0;ng/mL, with vitamin D insufficiency being between 15 and 30&#xa0;ng/mL and vitamin D deficiency being less than 15&#xa0;ng/mL [<xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B68">68</xref>]. According to the article published by Evenepoel et al, [<xref ref-type="bibr" rid="B68">68</xref>] the prevalence of hypovitaminosis D in the third month after renal transplantation is 78%, and according to the articles by Bouquegneau et al [<xref ref-type="bibr" rid="B9">9</xref>] and Alshayeb et al, [<xref ref-type="bibr" rid="B64">64</xref>] vitamin D deficiency would be present in 30% of the operated patients. As renal function recovers, vitamin D levels begin to rise, although they remain lower than those of the general population (<xref ref-type="sec" rid="s10">Supplementary Table S4</xref>) [<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B62">62</xref>]. Hypovitaminosis D may be associated with lower transplant tolerance, worsening infections, and an upset in BMD [<xref ref-type="bibr" rid="B5">5</xref>].</p>
<p>This BMD alteration is associated with both osteopenia and osteoporosis, as mentioned above, with various metabolic disturbances that occur after renal transplantation [<xref ref-type="bibr" rid="B4">4</xref>]. Although there are also several risk factors, such as advanced age, sex, and ethnicity of the patient [<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B6">6</xref>], the main underlying factor for BMD loss is treatment with glucocorticoids after transplantation. Glucocorticoids inhibit bone tissue formation and increase osteoclast activity by decreasing the formation and differentiation of osteoblasts [<xref ref-type="bibr" rid="B69">69</xref>]. The difference between osteopenia and osteoporosis is the amount of BMD lost, with osteoporosis considered a more severe pathology than osteopenia. These disorders occur most frequently in the first 6&#x2013;12&#xa0;months after transplantation, with the greatest loss of BMD in the first 6&#xa0;months [<xref ref-type="bibr" rid="B70">70</xref>]. In our meta-regression analysis, we have also shown a negative correlation between the time of transplantation and the prevalence of osteoporosis and osteopenia [<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B70">70</xref>]. After 6&#xa0;months, this loss of bone mineral slows down, probably due to the decrease in glucocorticoid use and the gradual correction of the various metabolic disturbances associated with these disorders. According to the study published by Ebeling et al, [<xref ref-type="bibr" rid="B71">71</xref>] the presence of osteoporosis can be found in 17%&#x2013;49% of kidney transplant recipients in the lumbar area and in 11%&#x2013;56% of patients transplanted in the femoral area [<xref ref-type="bibr" rid="B71">71</xref>]. In our meta-analysis, the prevalence of osteoporosis in the lumbar area was 13.8%. In contrast, in the femoral area, the prevalence was 19.2%.</p>
<p>The main consequence of BMD loss is an increased risk of fractures [<xref ref-type="bibr" rid="B2">2</xref>], although there are several factors, such as advanced age, loss of muscle mass and reduced physical activity, that may increase the risk of this adverse event [<xref ref-type="bibr" rid="B4">4</xref>]. Approximately 22.5% of patients suffer at least one fracture in the first 5&#xa0;years after transplantation, which means an incidence 4 times higher than that for the general population but lower than that in patients who remain on dialysis (<xref ref-type="sec" rid="s10">Supplementary Table S5</xref>) [<xref ref-type="bibr" rid="B9">9</xref>]. Fractures are associated with increased hospitalization and mortality in kidney transplant recipients, with hip, ankle, and foot fractures being the most common, suggesting a large economic impact [<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B72">72</xref>, <xref ref-type="bibr" rid="B73">73</xref>]. In our study, the prevalence of fractures after transplant was 14.2%.</p>
<p>Another factor that could increase the risk of fractures in transplant recipients is the loss of muscle mass and muscle strength associated with sarcopenia, which is associated with an increased risk of falls, physical disability, lower quality of life and greater morbidity and mortality [<xref ref-type="bibr" rid="B73">73</xref>]. The main risk factors for sarcopenia in kidney transplant recipients are vitamin D deficiency, physical inactivity, prolonged hospitalization, nutritional deficiencies, hyperparathyroidism, and proteinuria [<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B74">74</xref>]. The prevalence of this condition, whose occurrence in kidney transplant recipients is estimated at a younger age in comparison with the general population [<xref ref-type="bibr" rid="B75">75</xref>], varies greatly because there are no universal diagnostic criteria. In addition, together with osteopenia and osteoporosis, the risk of fracture in these patients increases considerably [<xref ref-type="bibr" rid="B7">7</xref>].</p>
<p>On the other hand, gout, which is a type of arthritis that occurs after the deposition of uric acid crystals in the joints, causing attacks of pain and inflammation, is another disorder that could be associated with kidney transplantation [<xref ref-type="bibr" rid="B76">76</xref>]. The main cause for this disorder is hyperuricemia, a metabolic disturbance that is common after renal transplantation. According to the article by Gupta et al, [<xref ref-type="bibr" rid="B77">77</xref>] hyperuricemia could reach a prevalence of 10%&#x2013;84%, while gout could be present in 2%&#x2013;28% of transplant recipients. In our study, the prevalence of gout was specifically 15.4%, although the differences in the date of transplantation between the three included studies may limit the generalisability of this estimate.</p>
<p>In order to compare these results, we have found a series of studies [<xref ref-type="bibr" rid="B54">54</xref>&#x2013;<xref ref-type="bibr" rid="B61">61</xref>] that provide prevalence data for the variables analysed in the general population (<xref ref-type="sec" rid="s10">Supplementary Tables S4, S5</xref>; <xref ref-type="sec" rid="s10">Supplementary Figures S17&#x2013;S26</xref>). It should be noted that for the variables of hypophosphatemia and low muscle strength, we have not been able to find any study providing prevalences in the general population. As for the other variables, we can observe the large difference in prevalence estimates between the transplanted population and the general population for hypercalcemia [<xref ref-type="bibr" rid="B54">54</xref>], hyperparathyroidism [<xref ref-type="bibr" rid="B55">55</xref>], hyperuricemia [<xref ref-type="bibr" rid="B55">55</xref>], hypervitaminosis D [<xref ref-type="bibr" rid="B56">56</xref>], sarcopenia [<xref ref-type="bibr" rid="B57">57</xref>], low muscle mass [<xref ref-type="bibr" rid="B58">58</xref>], fractures [<xref ref-type="bibr" rid="B59">59</xref>] and gout [<xref ref-type="bibr" rid="B55">55</xref>], indicating an increase in the prevalence of these metabolic disturbances and musculoskeletal disorders after kidney transplantation. In the case of osteopenia and osteoporosis, the difference in prevalence between the two populations is small, although it is true that in the studies [<xref ref-type="bibr" rid="B60">60</xref>, <xref ref-type="bibr" rid="B61">61</xref>] we have found in the general population, it is not divided into zones, as it is in the studies [<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B35">35</xref>&#x2013;<xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B43">43</xref>] in the transplanted population, which divide the prevalence into lumbar and femoral areas, so that no conclusions could be drawn when comparing the two populations with regard to these two variables analysed.</p>
<p>This study has several potential limitations, and its findings should be interpreted with some caution. First, they are inherent to the conduct of a systematic review and meta-analysis (selection bias and limited information reported by original studies). Second, the design of most studies was retrospective and cross-sectional, which does not allow establishing a cause-effect relationship. Additionally, the heterogeneity of the results was high, which may limit the extrapolation of data to different populations. Thirdly, the results should be interpreted with caution, given the pooling of studies from different years and geographical locations, with different circumstances and sample characteristics. In this sense, studies were conducted in five different decades, in which the surgical techniques, metabolic goals, and available medications may have been different. On the other hand, there was variability in the time at which the different outcomes were measured after transplantation. Finally, despite the physiological link between hyperparathyroidism and hypercalcemia and hypophosphatemia, our results did not show a clear association between their prevalence estimates. The main reasons for this finding could be the coexistence of some lifestyle-related covariates that were not included in the original analyses, and the small number of studies (only three) that analysed the prevalence of the three outcomes (low muscle strength, low muscle mass and gout), whose sample sizes were not very large. However, the aim of this study was to show the prevalence of different kidney transplant-related disorders.</p>
</sec>
<sec sec-type="conclusion" id="s5">
<title>Conclusion</title>
<p>In conclusion, this systematic review and meta-analysis shows a high prevalence regarding the presence of certain musculoskeletal disorders and their related metabolic disorders in kidney transplant recipients. Hypovitaminosis D, hyperparathyroidism and hyperuricemia were the most common metabolic disturbances. In parallel, low muscle strength, femoral osteopenia and low muscle mass were the main musculoskeletal disorders. At a clinical level, knowledge of these data will allow us to improve the prevention, diagnosis, and treatment of these complications, increase patient wellbeing, reduce the recovery time after surgery and avoid increased hospitalizations, morbidity, and mortality in kidney transplant patients, although further research is needed using experimental designs to test the effectiveness of different therapeutic prevention strategies in this specific population.</p>
</sec>
</body>
<back>
<sec id="s6">
<title>Author Contributions</title>
<p>AH-C had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. AH-C, MG-M, and CB-M designed the study; AH-C, MG-M, CB-M, and VM-V performed the data analysis, and AT-C, CP-M, LH-C, and IS-D interpreted the findings. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec sec-type="funding-information" id="s7">
<title>Funding</title>
<p>The project received a research grant from the Carlos III Institute of Health, Ministry of Economy and Competitiveness (Spain), awarded on the call for the creation of Health Outcomes-Oriented Cooperative Research Networks (RICORS), with reference RD21/0016/0025, co-funded with European Union&#x2014;NextGenerationEU funds. Additional funding was obtained from the Research Network on Preventative Activities and Health Promotion (RD12/0005/0009) to VM-V Likewise, this study was funded by European Regional Development Fund (ERDF) and by the Carvascare Research Group (2022-GRIN-34459 Carvascare Research Group).</p>
</sec>
<sec sec-type="COI-statement" id="s8">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s9">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontierspartnerships.org/articles/10.3389/ti.2024.12312/full#supplementary-material">https://www.frontierspartnerships.org/articles/10.3389/ti.2024.12312/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<sec id="s10">
<title>Abbreviations</title>
<p>BMD, Bone mineral density; CI, Confidence intervals; FGF-23, Fibroblast growth factor 23; GODT3, Global Observatory on Donation and Transplantation; JBI, Joanna Briggs Institute; MOOSE, Meta-analyses of Observational Studies in Epidemiology; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analysis; PROSPERO, International Prospective Register of Systematic Reviews; PTH, Parathyroid hormone; WOS, Web of Science.</p>
</sec>
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