Predictors and Adverse Outcomes of Acute Kidney Injury in Hospitalized Renal Transplant Recipients

Data about in-hospital AKI in RTRs is lacking. We conducted a retrospective study of 292 RTRs, with 807 hospital admissions, to reveal predictors and outcomes of AKI during admission. In-hospital AKI developed in 149 patients (51%). AKI in a previous admission was associated with a more than twofold increased risk of AKI in subsequent admissions (OR 2.13, p < 0.001). Other major significant predictors for in-hospital AKI included an infection as the major admission diagnosis (OR 2.93, p = 0.015), a medical history of hypertension (OR 1.91, p = 0.027), minimum systolic blood pressure (OR 0.98, p = 0.002), maximum tacrolimus trough level (OR 1.08, p = 0.005), hemoglobin level (OR 0.9, p = 0.016) and albumin level (OR 0.51, p = 0.025) during admission. Compared to admissions with no AKI, admissions with AKI were associated with longer length of stay (median time of 3.83 vs. 7.01 days, p < 0.001). In-hospital AKI was associated with higher rates of mortality during admission, almost doubled odds for rehospitalization within 90 days from discharge and increased the risk of overall mortality in multivariable mixed effect models. In-hospital AKI is common and is associated with poor short- and long-term outcomes. Strategies to prevent AKI during admission in RTRs should be implemented to reduce re-admission rates and improve patient survival.


INTRODUCTION
The prevalence of chronic kidney disease is increasing, accounting for more than 10% of hospital admissions in the adult population. The parallel increase in the rates of in-hospital acute kidney injury (AKI) may reach as much as 50% of intensive care unit (ICU) admissions (1,2). The consequences of AKI during hospitalization are dismal (3,4): Even modest changes in serum creatinine (Scr) (an increase >0.5 mg/dL) have been associated with a 6.5-fold increase in the odds of death and a 3.5-day increase in the length of stay (LOS) (5). Small changes in Scr have been also associated with increased mortality and prolonged hospitalizations in elderly patients admitted with congestive heart failure (6).
With the aim of preventing this serious complication, different studies have sought to establish predictors for AKI during hospitalization, both in the general population (7)(8)(9)(10)(11) and particularly for renal transplant recipients (RTRs). Unfortunately, however, information on predictors for AKI during hospitalization of RTRs is still lacking, although 11% of RTRs develop in-hospital AKI during the first three posttransplant years, which is associated with transplant failure and death (12). For RTRs, studies to date have focused mostly on delayed graft function, which is a form of AKI in the immediate peri-transplant period (13,14).
RTRs constitute a unique population with an inherent increased risk vs. the general population for in-hospital AKI secondary to different etiologies related to subclinical and chronic rejection, higher risk of infections and immunosuppressive therapy. As a result, strategies to prevent or minimize the occurrence and consequences of AKI during hospitalization in this population would necessarily be more complex than those for the general population.
Renal allograft survival has improved significantly in the short term, with one-year graft survival rates reaching 98.4% (15). However, ensuring long-term graft survival still poses a very significant challenge in renal transplantation. For RTRs, a better understanding of the risk factors for AKI during admission would form the basis for developing preventive therapeutic measures aimed at reducing the rate of in-hospital AKI, resulting in improved long-term renal allograft survival.
In this study, we sought to pinpoint the risk factors for AKI during hospitalization of RTRs in a non-intensive care setting. In addition, we examined the implications of in-patient AKI for inhospital mortality, duration of hospitalization, subsequent inhospital AKI, re-hospitalizations, and overall mortality in this vulnerable population.

Study Population and Design
Clinical and biochemical parameters were collected retrospectively from the MdClone system, the data acquisition tool at Sheba Medical Center. Additional data was collected from clinical records, as needed. The study was approved by the local ethics committee (IRB approval number: SMC-70-5320). Data was collected for up to 12 admissions post "Renal Transplant" diagnosis for admission dates falling between July 2007 and November 2020.
The initial dataset included 1405 hospitalizations for 399 transplant recipients. We then excluded from the analysis admissions post graft loss (baseline eGFR<15 mL/min per 1.73 m 2 ), post chronic dialysis initiation, and/or admissions ≤30 days from transplant to eliminate the effect of changes in immunosuppressive medications or in renal allograft function early post-transplant secondary to slow and/or delayed graft function, infections and early rejections. Hospitalizations with no Scr or only one Scr measured during admission were also excluded ( Figure 1). The final study cohort included 292 RTRs who had undergone kidney transplantation between June 1982 and June 2000, with a total of 807 non-ICU admissions.

Primary Outcome
The primary outcome was AKI during admission, which was defined as a difference of ≥50% between peak Scr during admission and baseline Scr, according to the Kidney Disease Improving Global Outcomes (KDIGO) definition. AKI staging was based on the KDIGO definitions for SCr increases, i.e., a difference between peak Scr during admission and baseline Scr that was: Stage 1, ≥1.5-1.9 times the baseline Scr; Stage 2, ≥2-2.9 times the baseline Scr; and Stage 3, >3 times the baseline Scr or a peak Scr during admission ≥4.0 mg/dL or initiation of renal replacement therapy.
To determine baseline eGFR, we chose the minimum Scr in the 120 days to 1 day prior to admission. For admissions without Scr measurements in the 1-to 120-day period, we used minimum Scr during admission. To avoid misjudgment of baseline renal allograft function affected by frequent changes in Scr early posttransplant, we used minimum Scr during admission for baseline eGFR assessment in admissions of less than 150 days from transplant.

Data Extraction and Study Assessments
The following information was extracted from electronic patient records: age, gender, etiology of end stage renal disease (ESRD), dialysis pre-transplant (yes/no), transplant number, donor type, transplant date and relevant medical history, specifically hypertension, congestive heart failure (CHF), ischemic heart disease (IHD) and pre-transplant diabetes. All diagnoses during admissions were obtained from MDClone. After a manual review of in-patient diagnoses, the main hospitalization etiology was selected, and diagnoses were grouped into five categories: infectious disease, cardiovascular disease, disease of the gastrointestinal system, neoplasm, and all others.
The following biochemical parameters during hospitalization were retrieved in an automated fashion from MDClone: average and maximum tacrolimus trough level, average total white blood cell count, average and minimum absolute lymphocyte count, average hemoglobin, average albumin, maximum and minimum glucose, maximum globulins, and average C-reactive protein. The following additional clinical and biochemical information during admission was also retrieved from MDClone: average and minimum systolic and diastolic blood pressures, average weight and body mass index (BMI), fever, maximum pulse, and minimum oxygen saturation. Use and average dose administered during admission for the following medications was automatically obtained from MDClone: tacrolimus, cyclosporine, mycophenolic acid (MPA) (for 238 admissions, mycophenolate dose was converted to the equivalent MPA dose by dividing mycophenolate dose by 1.388) and steroids (steroid derivatives used during admission, such as hydrocortisone, dexamethasone and methylprednisolone, were converted to the equivalent prednisone dose). Other medications administered during admission were also recorded.

Statistical Analysis
All demographic, clinical and biochemical covariates of interest were tabulated and compared between patients for AKI during admission (yes/no) and between admissions (with and without AKI, and partitioned into AKI stage for AKI patients). Categorical variables were compared using the Chi-squared test (or Fisher's test where the numbers were small), while continuous variables were first tested for normality using the Shapiro-Wilks Test (and for equality of variances), and were then compared using a t-test (or Anova) for normally distributed variables or a-parametric tests for non-normally distributed variables. An FDR [false discovery rate (Benjamini and Hochberg)] procedure was then carried out to correct for multiple comparisons. For the primary outcome of AKI during admission, logistic mixed models were used, with RTR being a random effect, and other variables being fixed effects. Univariate models were considered first; variables that were significant (p = 0.05) and/ or those with clinical importance were entered into multivariate models.
For the secondary outcomes, LOS was examined using a linear mixed model, with RTR as a random effect and the other variables being fixed effects. LOS (which is inherently right-tailed) was logtransformed to normalize it. Mortality during admission was modeled using the Cox proportional hazards model, which modeled the time from transplant to death or end of follow-up, taking into account the number of admissions per person. Overall mortality was modeled using Kaplan-Meier estimation, with AKI in different staging groups. Thereafter, the Cox proportional hazards model was used to model the time from transplant to death or end of follow-up. Readmission within 90 days was calculated. Logistic mixed models were used to predict the cause of readmission within 90 days, with RTR being a random effect, and other variables being mixed effects. For all secondary outcomes, univariate models were considered first. Significant variables and/or those with clinical importance were entered into multivariate models.
All statistical analyses were carried out using R-3

Univariate Comparison of RTRs Without Any AKI vs. With Any AKI During Admission
Of the 292 RTRs, 149 (51%) had 1 to 8 AKI admission events. For patients with any AKI during admission, the number of admissions per person, the death rate during admission, and the overall mortality were all higher (p < 0.001). ESRD secondary to APCKD and renal living donor transplant were more common in RTRs without vs. with any AKI during admission as the difference between the groups approached statistical significance. All other comparisons of characteristics, including age, sex, time from transplant to first admission, transplant number and dialysis pretransplant, are shown in Table 1.

Univariate Comparison of Admissions Without vs. With AKI During Admission
An AKI during admission was recorded for 297 of 807 (36.8%) admissions. In admissions with AKI vs. admissions without AKI, ESRD secondary to APCKD was less prevalent, while nephrosclerosis was more common (p = 0.06). RTRs with at least one AKI had higher rates of hypertension and IHD (67% and 43.1% compared to 58.2% and 32.2% of admissions without AKI, p = 0.037 and 0.006, respectively). The main admission diagnosis was an infection in 142 (47.8%) of admissions with AKI vs. 170 (33.3%) in admissions without AKI (p < 0.001). Significant differences in the various vital signs monitored during admission [maximum temperature, maximum, minimum and average pulse, minimum and average systolic blood pressure (SBP) and diastolic blood pressure (DBP), and O 2 saturation] were observed between admissions with and without AKI ( Table 2). Steroids use and average dose during admission were significantly higher in admissions with vs. without AKI [216 (72.2%) vs. 333 (65.3%), p = 0.06 (after adjustment for multiple comparisons) and 22.1 (SD 41.01) vs. 12.27 (SD 26.52) mg, p < 0.001 respectively]. The use of loop diuretics and of proton pump inhibitors was also significantly higher in admissions with vs. without AKI, as opposed to the use of renin-angiotensin-aldosterone system (RAAS) inhibitors, which was lower in admissions with vs. without in-hospital AKI. Laboratory results also differed significantly between admissions with and without AKI. Total white blood cell count, maximum glucose, maximum globulins and C-reactive protein levels were higher in admissions with vs. without AKI, whereas lymphocytes (absolute minimum), average and minimum hemoglobin, minimum glucose and average and minimum albumin were lower in admissions with vs. without AKI. Maximum tacrolimus 12-h trough level was significantly higher in admissions with vs. without AKI [7.1 (IQR 4.05-10.9) vs. 5.7 (4.05-8.5), p = 0.028]. Rates of death during admission and readmission within 90 days as well as LOS were significantly higher for those with vs. without AKI (  Table 3).  Minimum SBP and albumin level during admission were also found to be independent predictors for inhospital AKI ( Table 4).

Outcomes of AKI During Admission in RTRs
We examined four outcomes of AKI during admission: readmission within 90 days, mortality during admission, overall mortality, and LOS.

Mortality During Admission
In a mixed effect logistic regression analysis, admission age, AKI stage 3 vs. no AKI, minimum SBP and minimum albumin during  admission were found to be independent predictors for inhospital mortality. The odds of mortality during admission were four times higher in RTRs with AKI stage 3 vs. RTRs with no AKI during admission (OR 4.0, 95% CI 1.38-11.6, p = 0.01; Table 6).
Overall Mortality Figure 2 shows  Table 7).   admission was associated with adverse events, i.e., for patients who developed AKI, LOS and mortality during admission rose and rates of readmission within 90 days increased with worsening outcomes as AKI severity increased. The overall mortality risk was also higher in RTRs with any AKI vs. no AKI during admission.

Length of Stay
The overall incidence of AKI developing 3 months or later after kidney transplantation, excluding RTRs with deceased donor transplants and recipients of second or third transplants, was 20.4% (16). In seeking to compare this finding with values in the literature, we found that there are only very few studies dealing with the subject. In pediatric Modification (ICD-9-CM), which has limited sensitivity, and therefore the overall incidence of AKI was probably underestimated (12). Based on Scr levels pre and post admission, we detected AKI in a median time from transplant of 7.7 years (IQR 4.77-13.48) in 149/292 (51%) of RTRs, with a total of 513 admissions (1-10 admissions per person). Our analysis provides a more accurate assessment of the higher incidence of in-hospital AKI in RTRs compared to the non-transplant population, in which AKI occurs in 4%-20% of hospitalized patients (16,18,19). Similarly to our findings, a higher rate of AKI following cardiac surgery (46% vs. 28%) was observed in RTRs compared with non-RTRs (2). In a study of 11,683 patients developing in-hospital AKI, 2954 (25%) were re-hospitalized with recurrent AKI within 12 months of discharge (20), with each episode of recurrence conferring an increased risk for progression to chronic kidney disease (21). Analysis of a large database of about 150,000 patients revealed that approximately 20% were readmitted with AKI and about 10% were seen in an emergency room within 30 days of discharge (22). We found the readmission rate within 90 days to be 51.9% vs. 29% in admissions without in-hospital AKI (p < 0.001). Moreover, the severity of AKI also affected the 90-day readmission rate, which reached 62.4% in stage 3 as opposed to 48.5% in stage 1 AKI. Our study is the first to show the negative effects of in-hospital AKI on the readmission rate and subsequent AKI events in RTRs.
It is not surprising that a major diagnosis of an infection was associated with in-hospital AKI; for example, in a study conducted in Italy the incidence of in-hospital AKI was 31.7% during the COVID-19 pandemic compared to 25.9% during the pre-COVID-19 period (23). RTRs are prone to infections and complications of infections, given the immunosuppressive agents they receive to prevent rejection. Infections are commonly complicated by AKI secondary to sepsis associated with hemodynamic instability, volume depletion, and the nephrotoxicity of antibiotics, among other factors. A medical history of hypertension, associated with oxidative stress and endothelial dysfunction (24), was also found to be an independent predictor for in-hospital AKI in our population, as previously described in patients with AKI following surgical resection of malignant pleural mesothelioma (25).
Given the large number and extensive variety of the components of our dataset (different vital signs, clinical parameters, medications and laboratory results during admission) that were retrieved as possible confounders, we were able to demonstrate associations of SBP, hemoglobin, albumin and maximum tacrolimus trough level with in-hospital AKI. CNI nephrotoxicity, a well-known complication of CNI use (26,27), remains the leading cause of renal failure after transplantation of a non-renal organ (28,29). Similar abnormalities have been found when CNIs are used in other settings, for example, in patients with psoriasis (30). The pathophysiology of acute CNI nephrotoxicity is related to profound alterations in renal vascular resistance and blood flow in the afferent and efferent arterioles and even a reduced diameter of the afferent arterioles (27). In line with our findings, higher vs. lower preoperative CNI trough levels (73% vs. 36%) have been associated with higher rates of AKI following cardiac surgery in RTRs (2).
The pathophysiology of low SBP and a low hemoglobin level associated AKI is related to the reduction in perfusion pressure and oxygenation, leading to ischemic injury. Renal ischemiareperfusion injury in kidney transplantation leads to AKI, delayed graft function, and even graft loss (31). Kidney transplantation involves implantation of denervated kidneys, with impairment of blood flow autoregulation, rendering the renal allograft highly susceptible to ischemic injury and subsequent inflammation and cell death. A reduced nephron mass in RTRs may also increase their susceptibility to ischemic injury. Furthermore, renal allograft ischemia may exacerbate immune-related mechanisms of allograft injury, as manifested by the effect of cold and warm ischemia times on graft function and rejection (32).
AKI is common in RTRs and confers a high risk for graft failure and death (12,17,33). In populations other than RTRs, AKI has been associated with increased LOS and higher mortality (25,34). We are the first to describe the association of in-hospital AKI in RTRs with  increased LOS and mortality during admission. Our study is probably underpowered to detect an association between in-hospital mortality and milder AKI, found in studies of non-transplant patients (25). In addition, we found a strong association of AKI with overall mortality over a period of more than 30 years. Several limitations should be mentioned, including the retrospective study design. In addition, minimum Scr during admission used as baseline Scr in recipients with no Scr within 120 days prior to admission or within 150 days from transplant may not reflect baseline Scr as it could be elevated due to AKI prior to admission, there is no information about the exact timing of maximum Scr during admission, rejection, use of erythropoietin stimulating agents, admissions to other hospitals, transplant loss, renal replacement therapy or recovery from AKI, mortality (death with a functioning graft) and death-censored graft loss. Urine output criteria were not used. In addition, the use of serum creatinine levels to estimate GFR has limitations in assessing kidney function. The   strengths of this study include the large size of the cohort, creatininebased definitions to capture index and recurrent AKI, and the power to examine multiple potential confounders. Nonetheless, we cannot exclude potential residual confounding as in-hospital AKI may be a surrogate for disease severity.
In conclusion, in-hospital AKI in RTRs is an independent risk factor associated with poor short-and long-term outcomes. RTRs with an AKI during admission should be followed up closely, with specific monitoring after discharge to reduce the risk of rehospitalization and death. Efforts should be made to identify patients at high risk for AKI, to develop strategies to prevent AKI during admission, and to minimize adverse outcomes. RTRs should be closely monitored during admission to prevent hypotension, anemia, and hypoalbuminemia. The association of CNI with in-hospital AKI further emphasizes the importance of individualized tailoring of immunosuppressive therapy based on rejection vs. infection risk to prevent complications associated with over immunosuppression, including infections, which are independently associated with in-hospital AKI and AKI itself.

DATA AVAILABILITY STATEMENT
The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

ETHICS STATEMENT
The study was approved by the local ethics committee in Sheba medical center (IRB approval number: SMC-70-5320). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

AUTHOR CONTRIBUTIONS
TH: Conception and design, data acquisition, data interpretation, writing, revising; BO: Data analysis; NS: Data acquisition; LL: Data interpretation; GS: Conception and design; PB: Data acquisition; KC-H: Data interpretation; EM: Revising; EG: Revising; EZ: Conception and design, data interpretation; MS: conception and design, data interpretation, revising. All authors contributed to the article and approved the submitted version.