Similar Rates of AKI during the First Two Waves of COVID-19 in Northern Italy: a single-center study

IntroductionTwo waves of COVID-19 cases have overwhelmed most European countries during 2020. It is unclear if the incidence of acute kidney injury (AKI) has changed during the COVID-19 outbreaks. This study aims to evaluate the differences in incidence, risk factors and outcome of AKI in patients with SARS-CoV-2 infection during the first and second wave of COVID-19. MethodWe reviewed the health medical records of 792 consecutive patients with COVID-19 hospitalized at the University Hospital of Modena, Italy, from February 25 to December 14, 2020. ResultsAKI was diagnosed in 122 (15.4%) patients. Incidence of AKI remained steady rate during wave-1 (15.9%) and wave-2 (14.7%) (P=0.89). AKI patients were older (P=<0.001) and had a more severe respiratory impairment (PO2/FO2) (P=[≤]0.001) than their non-AKI counterparts. AKI led to a longer hospital stay (P=0.001), complicated with a higher rate of ICU admission. COVID-19-related AKI was associate with 59.7% of deaths during wave-1 and 70.6% during wave-2. At the end of the period of observation, 24% (wave-1) and 46.7% (wave-2) of survivors were discharged with a not fully recovered kidney function. Risk factors for AKI in patients with COVID-19 were diuretics (HR=5.3; 95%CI, 1.2-23.3; P=0.025) and cardiovascular disease (HR, 2.23; 95%CI, 1.05-5.1; P=0.036). ConclusionThe incidence of AKI (about 15%) remained unchanged during 2020, regardless of the trend of COVID-19. AKI occurred in patients with severe COVID-19 symptoms and was associated with a higher incidence of deaths than non-AKI patients. The risk factors of COVID-19-related AKI were diuretic therapy and cardiovascular disease.

Twenty-four-hour serum creatinine variation is associated with poor outcome in the novel coronavirus disease 2019 (COVID-19) patients

Background@#The development of acute kidney injury (AKI) in patients with coronavirus disease 2019 (COVID-19) is associated with a high risk of death. Published data demonstrate the possibility of severe kidney injury in patients suffering from COVID-19. However, these data are still controversial. @*Methods@#A total of 1,280 patients with a proven diagnosis of COVID-19 were included in our study. COVID-19 was confirmed in all patients using reverse transcriptase polymerase chain reaction test of a nasopharyngeal swab, and based on the typical computed tomography findings. Demographic data, underlying comorbidities, and laboratory blood tests were assessed. We assessed the incidence of AKI and its associated mortality defined by survival status at discharge. @*Results@#Proteinuria was identified with 648 patients (50.6%) with COVID-19. AKI was identified in 371 patients (29.0%). Ten of these patients (2.7%) required dialysis. The risk factors for AKI included age of > 65 years, augmentation of C-reactive protein, ferritin and an increase in values of activated partial thromboplastin time. Overall, 162 of the 1,280 hospitalized patients (12.7%) and 111 of the 371 patients (29.9%) with AKI did not survive. The hazard ratio (HR) for mortality was 3.96 (95% confidence interval, 2.83–5.54) for patients with AKI vs. no AKI. @*Conclusion@#AKI was a relatively common finding among patients with COVID-19. The risk factors for AKI in COVID-19 included old age, the inflammatory response, the severity of lung involvement, and disseminated intravascular coagulation. These same factors, in addition to arterial hypertension, were found to increase the risk of mortality.

Twenty-four-hour serum creatinine variation is associated with poor outcome in the novel coronavirus disease 2019 (COVID-19) patients

Background@#The development of acute kidney injury (AKI) in patients with coronavirus disease 2019 (COVID-19) is associated with a high risk of death. Published data demonstrate the possibility of severe kidney injury in patients suffering from COVID-19. However, these data are still controversial. @*Methods@#A total of 1,280 patients with a proven diagnosis of COVID-19 were included in our study. COVID-19 was confirmed in all patients using reverse transcriptase polymerase chain reaction test of a nasopharyngeal swab, and based on the typical computed tomography findings. Demographic data, underlying comorbidities, and laboratory blood tests were assessed. We assessed the incidence of AKI and its associated mortality defined by survival status at discharge. @*Results@#Proteinuria was identified with 648 patients (50.6%) with COVID-19. AKI was identified in 371 patients (29.0%). Ten of these patients (2.7%) required dialysis. The risk factors for AKI included age of > 65 years, augmentation of C-reactive protein, ferritin and an increase in values of activated partial thromboplastin time. Overall, 162 of the 1,280 hospitalized patients (12.7%) and 111 of the 371 patients (29.9%) with AKI did not survive. The hazard ratio (HR) for mortality was 3.96 (95% confidence interval, 2.83–5.54) for patients with AKI vs. no AKI. @*Conclusion@#AKI was a relatively common finding among patients with COVID-19. The risk factors for AKI in COVID-19 included old age, the inflammatory response, the severity of lung involvement, and disseminated intravascular coagulation. These same factors, in addition to arterial hypertension, were found to increase the risk of mortality.

Incidence, risk factors and mortality outcome in patients with acute kidney injury in COVID-19: a single-center observational study

BackgroundAcute kidney injury (AKI) is a recently recognized complication of coronavirus disease-2019 (COVID-19). This study aims to evaluate the incidence, risk factors and case-fatality rate of AKI in patients with documented COVID-19. MethodsWe reviewed the health medical records of 307 consecutive patients hospitalized for symptoms of COVID-19 at the University Hospital of Modena, Italy. ResultsAKI was diagnosed in 69 out of 307 (22.4%) patients. The stages of AKI were stage 1 in 57.9%, stage 2 in 24.6% and stage 3 in 17.3%. Hemodialysis was performed in 7.2% of the subjects. AKI patients had a mean age of 74.7{+/-}9.9 years and higher serum levels of the main marker of inflammation and organ involvement (lung, liver, hearth and liver) than non-AKI patients. AKI events were more frequent in subjects with severe lung comprise. Two peaks of AKI events coincided with in-hospital admission and death of the patients. Kidney injury was associate with a higher rate of urinary abnormalities including proteinuria (0.448{+/-}0.85 vs 0.18{+/-}0.29; P=<0.0001) and hematuria (P=0.032) compared to non-AKI patients. At the end of follow-up, 65.2% of the patients did not recover their renal function after AKI. Risk factors for kidney injury were age, male sex, CKD and non-renal SOFA. Adjusted Cox regression analysis revealed that AKI was independently associated with in-hospital death (hazard ratio [HR]=3.74; CI 95%, 1.34-10.46) compared to non-AKI patients. Groups of patients with AKI stage 2-3 and failure to recover kidney function were associated with the highest risk of in-hospital mortality. Lastly, long-hospitalization was positively associated with a decrease of serum creatinine, likely due to muscle depletion occurred with prolonged bed rest. ConclusionsAKI was a dire consequence of patients with COVID-19. Identification of patients at high-risk for AKI and prevention of kidney injury by avoiding dehydration and nephrotoxic agents is imperative in this vulnerable cohort of patients.

Hypokalemia in Patients with COVID-19

Patients with COVID-19 may experience multiple conditions (e.g., fever, hyperventilation, anorexia, gastroenteritis, acid-base disorder) that may cause electrolyte imbalances. Hypokalemia is a concerning electrolyte disorder that may increase the susceptibility to various kinds of arrhythmia. This study aimed to estimate prevalence, risk factors and outcome of hypokalemia in a cohort of non-critically ill patients. A retrospective analysis was conducted on 290 hospitalized patients with confirmed COVID-19 infection at the tertiary teaching hospital of Modena, Italy. Hypokalemia (<3.5 mEq/L) was detected in 119 patients (41%). The decrease of serum potassium level was of mild entity (3-3.4 mEq/L) and occurred in association with hypocalcemia (P=0.001) and lower level of serum magnesium (P=0.028) compared to normokaliemic patients. Urine K: creatinine ratio, measured in a small subset of patients (n=45; 36.1%), showed an increase of urinary potassium excretion in the majority of the cases (95.5%). Causes of kaliuria were diuretic therapy (53.4%) and corticosteroids (23.3%). In the remaining patients, urinary potassium loss was associated with normal serum magnesium, low sodium excretion (FENa< 1%) and metabolic alkalosis. Risk factors for hypokalemia were female gender (P=0.002; HR 0.41, 95%CI 0.23-0.73) and diuretic therapy (P=0.027; HR 1.94, 95%CI 1.08-3.48). Hypokalemia, adjusted for sex, age and SOFA score, resulted not associated with ICU admission (P=0.131, 95% CI 0.228-1.212) and in-hospital mortality (P=0.474; 95% CI 0,170-1,324) in our cohort of patients. Hypokalemia is a frequent disorder in COVID-19 patients and urinary potassium loss may be the main cause of hypokalemia. The disorder was mild in the majority of the patients and was unrelated to poor outcomes. Nevertheless, hypokalemic patients required potassium supplements to dampen the risk of arrhythmias.

Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia - challenges, strengths, and opportunities in a global health emergency

AimsThe aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospitalized patients with COVID-19 pneumonia. MethodsThis was an observational study that comprised consecutive patients with COVID-19 pneumonia admitted to hospital from 21 February to 6 April 2020. The patients medical history, demographic, epidemiologic and clinical data were collected in an electronic patient chart. The dataset was used to train predictive models using an established machine learning framework leveraging a hybrid approach where clinical expertise is applied alongside a data-driven analysis. The study outcome was the onset of moderate to severe respiratory failure defined as PaO2/FiO2 ratio <150 mmHg in at least one of two consecutive arterial blood gas analyses in the following 48 hours. Shapley Additive exPlanations values were used to quantify the positive or negative impact of each variable included in each model on the predicted outcome. ResultsA total of 198 patients contributed to generate 1068 usable observations which allowed to build 3 predictive models based respectively on 31-variables signs and symptoms, 39-variables laboratory biomarkers and 91-variables as a composition of the two. A fourth "boosted mixed model" included 20 variables was selected from the model 3, achieved the best predictive performance (AUC=0.84) without worsening the FN rate. Its clinical performance was applied in a narrative case report as an example. ConclusionThis study developed a machine model with 84% prediction accuracy, which is able to assist clinicians in decision making process and contribute to develop new analytics to improve care at high technology readiness levels.