RESUMO
Background Acute kidney injury (AKI) is one of the most common and significant problems in patients with Coronavirus Disease 2019 (COVID-19). However, little is known about the incidence and impact of AKI occurring in the community or early in the hospital admission. The traditional Kidney Disease Improving Global Outcomes (KDIGO) definition can fail to identify patients for whom hospitalisation coincides with recovery of AKI as manifested by a decrease in serum creatinine (sCr). We hypothesised that an extended KDIGO (eKDIGO) definition, adapted from the International Society of Nephrology (ISN) 0by25 studies, would identify more cases of AKI in patients with COVID-19 and that these may correspond to community-acquired AKI (CA-AKI) with similarly poor outcomes as previously reported in this population. Methods and findings All individuals recruited using the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC)–World Health Organization (WHO) Clinical Characterisation Protocol (CCP) and admitted to 1,609 hospitals in 54 countries with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection from February 15, 2020 to February 1, 2021 were included in the study. Data were collected and analysed for the duration of a patient’s admission. Incidence, staging, and timing of AKI were evaluated using a traditional and eKDIGO definition, which incorporated a commensurate decrease in sCr. Patients within eKDIGO diagnosed with AKI by a decrease in sCr were labelled as deKDIGO. Clinical characteristics and outcomes—intensive care unit (ICU) admission, invasive mechanical ventilation, and in-hospital death—were compared for all 3 groups of patients. The relationship between eKDIGO AKI and in-hospital death was assessed using survival curves and logistic regression, adjusting for disease severity and AKI susceptibility. A total of 75,670 patients were included in the final analysis cohort. Median length of admission was 12 days (interquartile range [IQR] 7, 20). There were twice as many patients with AKI identified by eKDIGO than KDIGO (31.7% versus 16.8%). Those in the eKDIGO group had a greater proportion of stage 1 AKI (58% versus 36% in KDIGO patients). Peak AKI occurred early in the admission more frequently among eKDIGO than KDIGO patients. Compared to those without AKI, patients in the eKDIGO group had worse renal function on admission, more in-hospital complications, higher rates of ICU admission (54% versus 23%) invasive ventilation (45% versus 15%), and increased mortality (38% versus 19%). Patients in the eKDIGO group had a higher risk of in-hospital death than those without AKI (adjusted odds ratio: 1.78, 95% confidence interval: 1.71 to 1.80, p-value < 0.001). Mortality and rate of ICU admission were lower among deKDIGO than KDIGO patients (25% versus 50% death and 35% versus 70% ICU admission) but significantly higher when compared to patients with no AKI (25% versus 19% death and 35% versus 23% ICU admission) (all p-values <5 × 10−5). Limitations include ad hoc sCr sampling, exclusion of patients with less than two sCr measurements, and limited availability of sCr measurements prior to initiation of acute dialysis. Conclusions An extended KDIGO definition of AKI resulted in a significantly higher detection rate in this population. These additional cases of AKI occurred early in the hospital admission and were associated with worse outcomes compared to patients without AKI.
RESUMO
BackgroundAcute kidney injury (AKI) is one of the most common and significant problems in patients with COVID-19. However, little is known about the incidence and impact of AKI occurring in the community or early in the hospital admission. The traditional KDIGO definition can fail to identify patients for whom hospitalization coincides with recovery of AKI as manifested by a decrease in serum creatinine (sCr). We hypothesized that an extended KDIGO definition, adapted from the International Society of Nephrology 0by25 studies, would identify more cases of AKI in patients with COVID-19 and that these may correspond to community-acquired AKI with similarly poor outcomes as previously reported in this population. Methods and FindingsAll individuals in the ISARIC cohort admitted to hospital with SARS-CoV-2 infection from February 15th, 2020, to February 1st, 2021, were included in the study. Data was collected and analysed for the duration of a patients admission. Incidence, staging and timing of AKI were evaluated using a traditional and extended KDIGO (eKDIGO) definition which incorporated a commensurate decrease in serum creatinine. Patients within eKDIGO diagnosed with AKI by a decrease in sCr were labelled as deKDIGO. Clinical characteristic and outcomes - intensive care unit (ICU) admission, invasive mechanical ventilation and in-hospital death - were compared for all three groups of patients. The relationship between eKDIGO AKI and in-hospital death was assessed using survival curves and logistic regression, adjusting for disease severity and AKI susceptibility. 75,670 patients from 54 countries were included in the final analysis cohort. Median length of admission was 12 days (IQR 7, 20). There were twice as many patients with AKI identified by eKDIGO than KDIGO (31.7 vs 16.8%). Those in the eKDIGO group had a greater proportion of stage 1 AKI (58% vs 36% in KDIGO patients). Peak AKI occurred early in the admission more frequently among eKDIGO than KDIGO patients. Compared to those without AKI, patients in the eKDIGO group had worse renal function on admission, more in-hospital complications, higher rates of ICU admission (54% vs 23%) invasive ventilation (45% vs 15%) and increased mortality (38% vs 19%). Patients in the eKDIGO group had a higher risk of in-hospital death than those without AKI (adjusted OR: 1.78, 95% confidence interval: 1.71-1.8, p-value < 0.001). Mortality and rate of ICU admission were lower among deKDIGO than KDIGO patients (25% vs 50% death and 35% vs 70% ICU admission) but significantly higher when compared to patients with no AKI (25% vs 19% death and 35% vs 23% ICU admission) (all p values < 5x10-5). Limitations include ad hoc sCr sampling, exclusion of patients with less than two sCr measurements, and limited availability of sCr measurements prior to initiation of acute dialysis. ConclusionsThe use of an extended KDIGO definition to diagnose AKI in this population resulted in a significantly higher incidence rate compared to traditional KDIGO criteria. These additional cases of AKI appear to be occurring in the community or early in the hospital admission and are associated with worse outcomes than those without AKI. Author SummaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIPrevious studies have shown that acute kidney injury (AKI) is a common problem among hospitalized patients with COVID-19. C_LIO_LIThe current biochemical criteria used to diagnose AKI may be insufficient to capture AKI that develops in the community and is recovering by the time a patient presents to hospital. C_LIO_LIThe use of an extended definition, that can identify AKI both during its development and recovery phase, may allow us to identify more patients with AKI. These patients may benefit from early management strategies to improve long term outcomes. C_LI What did the researchers do and find?O_LIIn this study, we examined AKI incidence, severity and outcomes among a large international cohort of patients with COVID-19 using both a traditional and extended definition of AKI. C_LIO_LIWe found that using the extended definition identified almost twice as many cases of AKI than the traditional definition (31.7 vs 16.8%). C_LIO_LIThese additional cases of AKI were generally less severe and occurred earlier in the hospital admission. Nevertheless, they were associated with worse outcomes, including ICU admission and in-hospital death (adjusted odds ratio: 1.78, 95% confidence interval: 1.71-1.8, p-value < 0.001) than those with no AKI. C_LI What do these findings mean?O_LIThe current definition of AKI fails to identify a large group of patients with AKI that appears to develop in the community or early in the hospital admission. C_LIO_LIGiven the finding that these cases of AKI are associated with worse admission outcomes than those without AKI, identifying and managing them in a timely manner is enormously important. C_LI
Assuntos
Doença de Addison , Nefropatias , Morte , Injúria Renal Aguda , COVID-19RESUMO
Background: Risk factors associated with mortality in patients with coronavirus disease 2019 (COVID-19) on mechanical ventilation are still not fully elucidated. Thus, we aimed to identify patient-level factors, readily available at the bedside, associated with the risk of in-hospital mortality within 28 days from commencement of invasive mechanical ventilation (28-day IMV mortality) in patients with COVID-19. Methods: Prospective observational cohort study in 148 intensive care units in the global COVID-19 Critical Care Consortium . Patients with clinically suspected or laboratory confirmed COVID-19 infection admitted to the intensive care unit (ICU) from February 2 nd through December 29th, 2020, requiring IMV. No study-specific interventions were performed. Patient characteristics and clinical data were assessed upon ICU admission, the commencement of IMV and for 28 days thereafter. We primarily aimed to identify time-independent and time-dependent risk factors for 28-day IMV mortality. Results: : A total of 1713 patients were included in the survival analysis, 588 patients died in hospital within 28 days of commencing IMV (34.3%). Cox-regression analysis identified associations between the hazard of 28-day IMV mortality with age (HR 1.27 per 10-year increase in age, 95% CI 1.17 to 1.37, P<0.001), PEEP upon commencement of IMV (HR 0.78 per 5-cmH 2 O increase, 95% CI 0.66-0.93, P=0.005). Time-dependent parameters associated with 28-day IMV mortality were serum creatinine (HR 1.30 per doubling, 95% CI 1.19-1.42, P<0.001), lactate (HR 1.16 per doubling, 95% CI 1.06-1.27 P=0.001), PaCO 2 (HR 1.31 per doubling, 95% CI 1.05-1.64, P=0.015), pH (HR 0.82 per 0.1 increase, 95% CI 0.74-0.91, P<0.001), PaO 2 /FiO 2 (HR 0.56 per doubling, 95% CI 0.50-0.62, P<0.001) and mean arterial pressure (HR 0.92 per 10 mmHg increase, 95% CI 0.88-0.97, P=0.002). Conclusions: : This international study establishes that in mechanically ventilated patients with COVID-19, older age and clinically relevant variables monitored at the bedside are risk factors for 28-day IMV mortality. Further investigation is warranted to validate any causative roles these parameters might play in influencing clinical outcomes.
Assuntos
COVID-19RESUMO
Background: Neuromuscular blocking agents (NMBA) have been previously used in patients with acute respiratory distress syndrome (ARDS). It is unknown if NMBA are useful in COVID-19 patients who require invasive mechanical ventilation (IMV).Methods: We investigated use of NMBA in COVID-19 patients on IMV from February 1 to November 24, 2020, in 147 hospitals across 6 continents, comprising the COVID-19 Critical Care Consortium. We performed propensity score (PS) matched Cox proportional hazards analysis to appraise the impact of NMBA use for ≥2 days, continuously or discontinuously (treatment), vs. no use of NMBA or only upon commencement of IMV (control) on 28-day intensive care unit (ICU) mortality.Findings: 1548 (72%) patients received any NMBA therapy; 1165 (54%) of patients were stratified in the treatment group, with a median (IQR) time from ICU admission to commencement of NMBA therapy of 0 (0-2) days. The median (IQR) duration of NMBA therapy was 3 (2-6) days (N=1548). Upon commencement of IMV, patients who received NMBA therapy had a lower mean (±SD) PaO2/FiO2 (139±75 vs 157±93; P<0.001). After PS matching, Cox proportional hazard model demonstrated that NMBA therapy was significantly associated with higher 28-day ICU mortality (adjusted HR 2.20, 95% CI 1.67, 2.89, P<0.001). Sensitivity analyses testing various NMBA therapeutic regimens confirmed similar associations with mortality.Interpretation: Use of NMBA is common in COVID-19 patients on IMV and associated with a 2.2-fold increase in risk of 28-day mortality. Until further randomised evidence is available, NMBA should be applied cautiously in routine clinical practice.Funding Statement: University of Queensland, Wesley Medical Research, The Prince Charles Hospital Foundation, The Health Research Board of Ireland; Biomedicine international training research programme for excellent clinician-scientists; European Union’s research and innovation programme (Horizon 2020); la Caixa Foundation. Finally, Carol Hodgson is funded by a National Health and Medical Research Council Grant.Declaration of Interests: Dr. Li Bassi received research support from Fisher & Paykel outside the submitted work. Dr. Dalton has consulting from Innovative ECMO Concepts, Abiomed and Instrumentation Labs , none which affect the current work. Dr. Brodie receives research support from ALung Technologies and he has been on the medical advisory boards for Baxter, Abiomed, Xenios and Hemovent. Dr. Fan reports personal fees from ALung Technologies, Baxter, Fresenius Medical Care, Getinge, and MC3Cardiopulmonary outside the submitted work. Dr. Laffey reports consulting fees from Baxter and Cala Medical, both outside the submitted work. Dr Nichol is supported by a health Research Board of Ireland award (CTN-2014-012). Dr. Fraser receives research support from Fisher & Paykel outside the submitted work. Remaining authors do not have any competing interest to declare. Ethics Approval Statement: Participating hospitals obtained local ethics committee approval and a waiver of informed consent was granted in all cases.De-identified patient data were collected and stored via the REDCap (Vanderbilt/NIH/NCATS UL1 TR000445 v.10.0.23) electronic data capture tool, hosted at the University of Oxford, United Kingdom and University of Queensland.