BACKGROUND AND AIMS During the last 2 years, we have witnessed several waves of the COVID-19 pandemic characterized by massive infections among the general population, sudden increases in the number of hospitalizations and variable rates of complications and mortality among patients. Acute kidney injury (AKI) has been described as a common and serious complication of COVID-19. However, multiple factors that are involved in the development of this complication have been modified throughout these months, including the appearance of new variants of the virus, the modification of treatment protocols or the advancement of vaccination among the general population. In this study, we aimed to compare the rates of AKI among patients who required admission due to COVID-19 in the first and current (sixth) waves of the pandemic. METHOD Consecutive patients that required admission due to COVID-19 in a tertiary referral hospital during the first (March to May 2020) and current (December 2021) waves of the pandemic were enrolled in the study. Patient characteristics, rates of AKI incidence, 28-day mortality and in-hospital length of stay were compared between groups. Viral infection was confirmed by real-time RT-qPCR in all cases. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines using peak serum creatinine and acute dialysis criteria. Multivariate logistic regression was performed to define potential predictors of AKI. RESULTS Table 1 summarizes demographic and clinical characteristics among enrolled patients. Compared with the current wave, patients admitted during the first wave were older, had higher baseline serum creatinine and lower baseline eGFR. During the first wave, patients presented higher peak serum creatinine values and a higher incidence of in-hospital AKI. Age, male sex, hypertension, diabetes, CKD and pandemic wave were included in multivariate logistic regression analysis as potential predictors of AKI. Only past history of hypertension [OR 2.867; 95% confidence interval (95% CI) 1.279–6.424; P-value: .011] and CKD (OR 2.418; 95% CI 1.237–4.73; P-value: .01) independently predicted AKI in the sample. CONCLUSION Despite multiple changes that have occurred throughout the pandemic, including new treatment protocols, the appearance of new variants of the virus with different clinical profiles or the extensive application of vaccines, these changes have not translated into a significant decrease in the risk of AKI among patients admitted due to COVID-19, which appears to still be conditioned mainly by comorbidities of each patient, including past history of CKD.
Background and Aims The risk scores used in Critical Care Units estimate the severity and mortality of patients. The SAPS (Simplified Acute Physiologic Score) and its SAPS II and SAPS III variants calculate the severity by collecting the values recorded in the first 24 hours. The EPTS (Estimated Post-Transplant-Survival) is used as a reference for the allocation of organs in the US by the OPTN. The objective is to determine its use in recent renal transplant units as estimator of subsequent renal function, in services where patients move from the operating room to a nephrological intermediate care unit. Method The SAPS (II and III) and OPTN scores were applied in 87 (N = 87) consecutive renal transplanted patients. The point value of each of the scales was evaluated with the creatinine values at hospital discharge, and one month after the transplant. The scores obtained on the SAPS scales were divided as follows (SAPSIIA <20 points, SAPSIIB ≥20 points) (SAPSIII A <30 points, SAPSIIIB ≥30 points). In the EPTS scale, two cut-off points were used to divide the groups (20% Score; EPTS-IA ≤20%, EPTS-IB> 20%), (Score 40%; EPTS-IIA ≤40%, EPTS -IIB> 40). The sérum creatinine means of each of the groups were compared. Data were analyzed with SPSS 20.0.0 Results Significant differences were found in serum creatinine levels in renal function at the first month of transplantation in the SAPS II groups (SAPS IIA 1.38 mg / dl, SAPS IIB 1.79 mg / dl; P = 0.017 95% CI). With an area under the ROC curve of 0.65 (P = 0.017 95% CI). In the SAPS III groups no significant differences were found. In the EPTS scales, there were also significant differences in creatinine one month after the transplant in the group with a score of 40% (EPTS-IIA ≤40% 1.42 mg / dl, EPTS-IIB> 40 1.81 mg / dl; P = 0.024 95% CI) With an Area under the ROC curve of 0.64 (P = 0.037 95% CI). Conclusion The SAPSII and EPTS scores can be a useful tool in estimating renal function one month after renal transplantation, giving a prognosis of renal graft function. The combined use of these scales together with other functional graft tests could have an important relevance in the management and follow-up of recent renal transplantation. Other studies with larger sample sizes are necessary to establish the appropriate cut-off points for the scales.
Background and Aims Acute tubular necrosis is a common complication after kidney transplantation and is closely related to delayed graft function (DGF) and slower graft function recovery after surgery. The furosemide stress test (FST) uses a standardized dose of furosemide to evaluate the integrity of the renal tubule and determine which patients have developed severe tubular damage. We aimed to apply the FST to a sample of incident deceased-donor kidney transplant recipients and describe its association with DGF and serum creatinine (SCr) at discharge. Method Single-center prospective observational study of deceased-donor kidney transplant recipients. The FST, a standardized bolus dose of furosemide (1.5 mg/kg) was administered between the 3rd and 5th day after surgery. Patients were excluded if, during that time period, they presented evidence of active bleeding, obstructive uropathy or volume depletion. Urine output (UO) 60 and 120 min after FST was registered. To reduce the risk of hypovolemia, each ml of UO produced for six hours after FST was replaced with 1 ml of normal saline. Results 25 patients were included in the study. Mean 2h FST UO was 1012±570 ml. Demographic and clinical data are summarized in Table 1. Subjects that suffered DGF had a significantly lower 2h FST UO (534 vs 1164 ml; P=0.015). In adjusted linear regression analysis only a 2h FST UO<1000 ml (β=0.906; 95%CI: 0.04-1.772; P=0.041) and DGF (β=1.592; 95%CI: 0.488-2.696; P=0.008) were independent predictors of SCr at discharge (model adjusted for recipient age, cold ischemia time, number of HLA mismatches, donor SCr and donor hypertension). Conclusion Recipients with a 2h FST UO <1000 ml suffered DGF more frequently. FST and DGF were independent predictors of SCr at discharge. A standardized FST could help clinicians distinguish patients with more severe tubular dysfunction and higher risk of DGF.
BACKGROUND AND AIMS Increased intra-abdominal pressure (IAP) is common after kidney transplantation (KT). However, the role of potential transplant-specific predictors of this complication, such as tacrolimus-associated endothelial dysfunction, remains unclear. We aimed to describe the relationship between tacrolimus trough levels and IAP in a sample of incident KT patients. METHOD Single-centre prospective cohort of deceased-donor KTs. Anesthesia, surgical technique and immunosuppression induction therapy were the same in all cases. IAP monitoring was performed according to WSACS guidelines using the urinary bladder technique (UnoMeter Abdo-Pressure kit). IAP values were registered every 8h during the first 72 h after surgery or until reoperation. Mean IAP values during the first 7 2h (72 h-IAP) were used in this analysis. The first measured tacrolimus trough levels after transplantation were included as a potential predictor of IAP. Patients without recorded tacrolimus trough levels during the first 7 days after surgery were excluded. The study was approved by the local ethics committee. RESULTS A total of 192 patients were enrolled in the study. Table 1A summarizes relevant patient and haemodynamic variables. Subjects with more severe intra-abdominal hypertension were more commonly males, with longer dialysis vintage, higher BMI and suffered diabetes more frequently. Multivariate linear regression analysis was used to examine potential predictors of 72 h-IAP, including male sex, months on dialysis, body mass index (BMI) (Table 1B), 72 h-fluid balance and tacrolimus trough levels. Recipient age, months on dialysis, BMI and tacrolimus trough levels were independent predictors of 72 h-IAP. CONCLUSION Tacrolimus-associated endothelial dysfunction may play a role in the increase of IAP after transplantation. In contrast, accumulated fluid balance, one of the strongest predictors of IAP in the ICU setting, failed to predict IAP values in our sample. These results offer new insight both into the pathophysiology of increased IAP and into the complex mechanisms of tacrolimus-associated nephrotoxicity in the early post-transplant period.
BACKGROUND AND AIMS Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been in our daily practice for almost 2 years now. Since the beginning of the pandemic, we have aimed to study its most immediate effects on patients to find the best line of treatment or, at least, mitigate its worst outcomes. Nevertheless, we also know some long-term health consequences such as fatigue, sleep difficulties, headache, among others, but its long-term kidney effects are not entirely clear yet. The aim of this study was to describe if coronavirus disease's (COVID-19) severity increases the risk of chronic kidney disease (CKD) progression after a previous hospitalization and observe if there are any additional risk factors that could help us predict this outcome. METHOD In this study, a sample of consecutive patients who required admission due to COVID-19 during the first wave of the pandemic (from March to May of 2020) was recruited. Patients were followed for 12 months since initial admission. The composite outcome of the study included either death or CKD progression. CKD progression was defined as incremental progression to a higher KDIGO CKD stage compared to baseline pre COVID-19 renal function [(in mL/min/1.73 m2): estimated glomerular filtration rate (eGFR) ≥60; stage 3a: 45–59; stage 3b: 30–44; stage 4: 15–29; stage 5: <15], or dialysis initiation. Cardiovascular disease was defined as a history of myocardial infarction, stroke, or peripheral vascular disease. Chronic lung diseases included asthma, chronic obstructive pulmonary disease and chronic bronchitis. RESULTS The sample was composed of 93 patients, of which 14 (15.1%) died during follow-up. Of those alive 12 months after initial admission, 17 (21.5%) suffered CKD progression. No patient required renal replacement therapy. Patients that suffered the composite outcome presented a higher prevalence of cancer, tended to be slightly older and suffered from additional comorbidities more frequently (Table). In multivariate logistic regression analysis, previous history of CKD [odds ratio (OR): 1.066 (0.433–2.624); P = 0.889], severe or critical COVID-19 on admission [OR: 0.657 (0.24–1.8); P =0.414] or ICU admission [OR: 0.986 (0.082–11.898); P = 0.991] failed to predict the composite outcome. CONCLUSION Our main hypothesis was that COVID-19 sequelae should be due to an exaggerated activation of the immune system against the virus. Thus, patients that suffered severe COVID-19 should be expected to develop more long-term health consequences of the infection when compared with those with milder disease. However, we failed to prove any link between COVID-19 severity and long-term CKD progression. History of CKD or ICU admission was also unable to predict the composite outcome. Previous studies have described a relationship between COVID-19 severity and adverse renal outcomes, a relationship that we failed to observe. These discrepancies could be due to the small sample size of our study and the different definition of CKD progression applied. In addition, age could act as a potential modifier of CKD progression after admission due to COVID. More studies are required to further clarify the mechanisms and long-term renal consequences of COVID-19 and define potential lines of treatment.
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