Urine Output and Mortality in Patients Resuscitated from out of Hospital Cardiac Arrest.

BACKGROUND: Limited data exist regarding urine output (UO) as a prognostic marker in out-of-hospital-cardiac-arrest (OHCA) survivors undergoing targeted temperature management (TTM). METHODS: We included 247 comatose adult patients who underwent TTM after OHCA between 2007 and 2017, excluding patients with end-stage renal disease. Three groups were defined based on mean hourly UO during the first 24 h: Group 1 (<0.5 mL/kg/h, n = 73), Group 2 (0.5-1 mL/kg/h, n = 81) and Group 3 (>1 mL/kg/h, n = 93). Serum creatinine was used to classify acute kidney injury (AKI). The primary and secondary outcomes respectively were in-hospital mortality and favorable neurological outcome at hospital discharge (modified Rankin Scale [mRS]<3). RESULTS: In-hospital mortality decreased incrementally as UO increased (adjusted OR 0.9 per 0.1 mL/kg/h higher; p = 0.002). UO < 0.5 mL/kg/h was strongly associated with higher in-hospital mortality (adjusted OR 4.2 [1.6-10.8], p = 0.003) and less favorable neurological outcomes (adjusted OR 0.4 [0.2-0.8], p = 0.007). Even among patients without AKI, lower UO portended higher mortality (40% vs 15% vs 9% for UO groups 1, 2, and 3 respectively, p < 0.001). CONCLUSION: Higher UO is incrementally associated with lower in-hospital mortality and better neurological outcomes. Oliguria may be a more sensitive early prognostic marker than creatinine-based AKI after OHCA.

Acute Kidney Injury Survivor Care Following Hospital Discharge: A Mixed-Methods Study of Nephrologists and Primary Care Providers.

Rationale & Objective: Widespread delivery of high-quality care for acute kidney injury (AKI) survivors after hospital discharge requires a multidisciplinary team. We aimed to compare management approaches between nephrologists and primary care providers (PCPs) and explored strategies to optimize collaboration. Study Design: Explanatory sequential mixed-methods study using a case-based survey followed by semi-structured interviews. Setting & Participants: Nephrologists and PCPs providing AKI survivor care at 3 Mayo Clinic sites and the Mayo Clinic Health System were included. Outcomes: Survey questions and interviews elucidated participants' recommendations for post-AKI care. Analytical Approach: Descriptive statistics were used to summarize survey responses. Qualitative data analysis used deductive and inductive strategies. A connecting and merging approach was used for mixed-methods data integration. Results: 148 of 774 (19%) providers submitted survey responses (24/72 nephrologists and 105/705 PCPs). Nephrologists and PCPs recommended laboratory monitoring and follow-up with a PCP shortly after hospital discharge. Both indicated that the need for nephrology referral, and its timing should be dictated by clinical and non-clinical patient-specific factors. There were opportunities for improvement in medication and comorbid condition management in both groups. Incorporation of multidisciplinary specialists (eg, pharmacists) was recommended to expand knowledge, optimize patient-centered care, and alleviate provider workload. Limitations: Survey findings may have been affected by non-response bias and the unique challenges facing clinicians and health systems during the COVID-19 pandemic. Participants were from a single health system, and their views or experiences may differ from those in other health systems or serving different populations. Conclusions: A multidisciplinary team-based model of post-AKI care may facilitate implementation of a patient-centered care plan, improve adherence to best practices, and reduce clinician and patient burden. Individualizing care for AKI survivors based on clinical and non-clinical patient-specific factors is needed to optimize outcomes for patients and health systems.

An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems.

BACKGROUND: We applied machine learning (ML) algorithms to generate a risk prediction tool [Collaboration for Risk Evaluation in COVID-19 (CORE-COVID-19)] for predicting the composite of 30-day endotracheal intubation, intravenous administration of vasopressors, or death after COVID-19 hospitalization and compared it with the existing risk scores. METHODS: This is a retrospective study of adults hospitalized with COVID-19 from March 2020 to February 2021. Patients, each with 92 variables, and one composite outcome underwent feature selection process to identify the most predictive variables. Selected variables were modeled to build four ML algorithms (artificial neural network, support vector machine, gradient boosting machine, and Logistic regression) and an ensemble model to generate a CORE-COVID-19 model to predict the composite outcome and compared with existing risk prediction scores. The net benefit for clinical use of each model was assessed by decision curve analysis. RESULTS: Of 1796 patients, 278 (15%) patients reached primary outcome. Six most predictive features were identified. Four ML algorithms achieved comparable discrimination (P > 0.827) with c-statistics ranged 0.849-0.856, calibration slopes 0.911-1.173, and Hosmer-Lemeshow P > 0.141 in validation dataset. These 6-variable fitted CORE-COVID-19 model revealed a c-statistic of 0.880, which was significantly (P < 0.04) higher than ISARIC-4C (0.751), CURB-65 (0.735), qSOFA (0.676), and MEWS (0.674) for outcome prediction. The net benefit of the CORE-COVID-19 model was greater than that of the existing risk scores. CONCLUSION: The CORE-COVID-19 model accurately assigned 88% of patients who potentially progressed to 30-day composite events and revealed improved performance over existing risk scores, indicating its potential utility in clinical practice.

Assessment of respiratory support decision and the outcome of invasive mechanical ventilation in severe COVID-19 with ARDS.

Background: The coronavirus disease 2019 (COVID-19) is an ongoing pandemic. Invasive mechanical ventilation (IMV) is essential for the management of COVID-19 with acute respiratory distress syndrome (ARDS). We aimed to assess the impact of compliance with a respiratory decision support system on the outcomes of patients with COVID-19-associated ARDS who required IMV. Methods: In this retrospective, single-center, case series study, patients with COVID-19-associated ARDS who required IMV at Zhongnan Hospital of Wuhan University, China, from January 8th, 2020, to March 24th, 2020, with the final follow-up date of April 20th, 2020, were included. Demographic, clinical, laboratory, imaging, and management information were collected and analyzed. Compliance with the respiratory support decision system was documented, and its relationship with 28-day mortality was evaluated. Results: The study included 46 COVID-19-associated ARDS patients who required IMV. The median age of the 46 patients was 68.5 years, and 31 were men. The partial pressure of arterial oxygen (PaO2)/fraction of inspired oxygen (FiO2) ratio at intensive care unit (ICU) admission was 104 mmHg. The median total length of IMV was 12.0 (interquartile range [IQR]: 6.0-27.3) days, and the median respiratory support decision score was 11.0 (IQR: 7.8-16.0). To 28 days after ICU admission, 18 (39.1%) patients died. Survivors had a significantly higher respiratory support decision score than non-survivors (15.0 [10.3-17.0] vs. 8.5 (6.0-10.3), P = 0.001). Using receiver operating characteristic (ROC) curve to assess the discrimination of respiratory support decision score to 28-day mortality, the area under the curve (AUC) was 0.796 (95% confidence interval [CI]: 0.657-0.934, P = 0.001) and the cut-off was 11.5 (sensitivity = 0.679, specificity = 0.889). Patients with a higher score (>11.5) were more likely to survive at 28 days after ICU admission (log-rank test, P < 0.001). Conclusions: For severe COVID-19-associated ARDS with IMV, following the respiratory support decision and assessing completion would improve the progress of ventilation. With a decision score of >11.5, the mortality at 28 days after ICU admission showed an obvious decrease.

Characteristics, Treatment Patterns, and Clinical Outcomes After Heart Failure Hospitalizations During the COVID-19 Pandemic, March to October 2020.

OBJECTIVE: To compare clinical characteristics, treatment patterns, and 30-day all-cause readmission and mortality between patients hospitalized for heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic. PATIENTS AND METHODS: The study was conducted at 16 hospitals across 3 geographically dispersed US states. The study included 6769 adults (mean age, 74 years; 56% [5033 of 8989] men) with cumulative 8989 HF hospitalizations: 2341 hospitalizations during the COVID-19 pandemic (March 1 through October 30, 2020) and 6648 in the pre-COVID-19 (October 1, 2018, through February 28, 2020) comparator group. We used Poisson regression, Kaplan-Meier estimates, multivariable logistic, and Cox regression analysis to determine whether prespecified study outcomes varied by time frames. RESULTS: The adjusted 30-day readmission rate decreased from 13.1% (872 of 6648) in the pre-COVID-19 period to 10.0% (234 of 2341) in the COVID-19 pandemic period (relative risk reduction, 23%; hazard ratio, 0.77; 95% CI, 0.66 to 0.89). Conversely, all-cause mortality increased from 9.7% (645 of 6648) in the pre-COVID-19 period to 11.3% (264 of 2341) in the COVID-19 pandemic period (relative risk increase, 16%; number of admissions needed for one additional death, 62.5; hazard ratio, 1.19; 95% CI, 1.02 to 1.39). Despite significant differences in rates of index hospitalization, readmission, and mortality across the study time frames, the disease severity, HF subtypes, and treatment patterns remained unchanged (P>0.05). CONCLUSION: The findings of this large tristate multicenter cohort study of HF hospitalizations suggest lower rates of index hospitalizations and 30-day readmissions but higher incidence of 30-day mortality with broadly similar use of HF medication, surgical interventions, and devices during the COVID-19 pandemic compared with the pre-COVID-19 time frame.

Optimising transitions of care for acute kidney injury survivors: protocol for a mixed-methods study of nephrologist and primary care provider recommendations.

INTRODUCTION: Acute kidney injury (AKI) affects nearly 20% of all hospitalised patients and is associated with poor outcomes. Long-term complications can be partially attributed to gaps in kidney-focused care and education during transitions. Building capacity across the healthcare spectrum by engaging a broad network of multidisciplinary providers to facilitate optimal follow-up care represents an important mechanism to address this existing care gap. Key participants include nephrologists and primary care providers and in-depth study of each specialty's approach to post-AKI care is essential to optimise care processes and healthcare delivery for AKI survivors. METHODS AND ANALYSIS: This explanatory sequential mixed-methods study uses survey and interview methodology to assess nephrologist and primary care provider recommendations for post-AKI care, including KAMPS (kidney function assessment, awareness and education, medication review, blood pressure monitoring and sick day education) elements of follow-up, the role of multispecialty collaboration, and views on care process-specific and patient-specific factors influencing healthcare delivery. Nephrologists and primary care providers will be surveyed to assess recommendations and clinical decision-making in the context of post-AKI care. Descriptive statistics and the Pearson's χ2 or Fisher's exact test will be used to compare results between groups. This will be followed by semistructured interviews to gather rich, qualitative data that explains and/or connects results from the quantitative survey. Both deductive analysis and inductive analysis will occur to identify and compare themes. ETHICS AND DISSEMINATION: This study has been reviewed and deemed exempt by the Institutional Review Board at Mayo Clinic (IRB 20-0 08 793). The study was deemed exempt due to the sole use of survey and interview methodology. Results will be disseminated in presentations and manuscript form through peer-reviewed publication.

Accelerated versus watchful waiting strategy of kidney replacement therapy for acute kidney injury: a systematic review and meta-analysis of randomized clinical trials.

Background: Critically ill patients with severe acute kidney injury (AKI) requiring kidney replacement therapy (KRT) have a grim prognosis. Recently, multiple studies focused on the impact of KRT initiation time [i.e., accelerated versus watchful waiting KRT initiation (WWS-KRT)] on patient outcomes. We aim to review the results of all related clinical trials. Methods: In this systematic review, we searched all relevant randomized clinical trials from January 2000 to April 2021. We assessed the impacts of accelerated versus WWS-KRT on KRT dependence, KRT-free days, mortality and adverse events, including hypotension, infection, arrhythmia and bleeding. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. Results: A total of 4932 critically ill patients with AKI from 10 randomized clinical trials were included in this analysis. The overall 28-day mortality rate was 38.5%. The 28-day KRT-dependence rate was 13.0%. The overall incident of KRT in the accelerated group was 97.4% and 62.8% in the WWS-KRT group. KRT in the accelerated group started 36.7 h earlier than the WWS-KRT group. The two groups had similar risks of 28-day [pooled log odds ratio (OR) 1.001, P = 0.982] and 90-day (OR 0.999, P = 0.991) mortality rates. The accelerated group had a significantly higher risk of 90-day KRT dependence (OR 1.589, P = 0.007), hypotension (OR 1.687, P < 0.001) and infection (OR 1.38, P = 0.04) compared with the WWS-KRT group. Conclusions: This meta-analysis revealed that accelerated KRT leads to a higher probability of 90-day KRT dependence and dialysis-related complications without any impact on mortality rate when compared with WWS-KRT. Therefore, we suggest the WWS-KRT strategy for critically ill patients.

Publisher Correction: COVID-19-associated acute kidney injury: consensus report of the 25th Acute Disease Quality Initiative (ADQI) Workgroup.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

COVID-19-associated acute kidney injury: consensus report of the 25th Acute Disease Quality Initiative (ADQI) Workgroup.

Kidney involvement in patients with coronavirus disease 2019 (COVID-19) is common, and can range from the presence of proteinuria and haematuria to acute kidney injury (AKI) requiring renal replacement therapy (RRT; also known as kidney replacement therapy). COVID-19-associated AKI (COVID-19 AKI) is associated with high mortality and serves as an independent risk factor for all-cause in-hospital death in patients with COVID-19. The pathophysiology and mechanisms of AKI in patients with COVID-19 have not been fully elucidated and seem to be multifactorial, in keeping with the pathophysiology of AKI in other patients who are critically ill. Little is known about the prevention and management of COVID-19 AKI. The emergence of regional 'surges' in COVID-19 cases can limit hospital resources, including dialysis availability and supplies; thus, careful daily assessment of available resources is needed. In this Consensus Statement, the Acute Disease Quality Initiative provides recommendations for the diagnosis, prevention and management of COVID-19 AKI based on current literature. We also make recommendations for areas of future research, which are aimed at improving understanding of the underlying processes and improving outcomes for patients with COVID-19 AKI.

Neuropathology of COVID-19: a spectrum of vascular and acute disseminated encephalomyelitis (ADEM)-like pathology.

We report the neuropathological findings of a patient who died from complications of COVID-19. The decedent was initially hospitalized for surgical management of underlying coronary artery disease. He developed post-operative complications and was evaluated with chest imaging studies. The chest computed tomography (CT) imaging results were indicative of COVID-19 and he was subsequently tested for SARS-CoV-2, which was positive. His condition worsened and he died after more than 2 weeks of hospitalization and aggressive treatment. The autopsy revealed a range of neuropathological lesions, with features resembling both vascular and demyelinating etiologies. Hemorrhagic white matter lesions were present throughout the cerebral hemispheres with surrounding axonal injury and macrophages. The subcortical white matter had scattered clusters of macrophages, a range of associated axonal injury, and a perivascular acute disseminated encephalomyelitis (ADEM)-like appearance. Additional white matter lesions included focal microscopic areas of necrosis with central loss of white matter and marked axonal injury. Rare neocortical organizing microscopic infarcts were also identified. Imaging and clinical reports have demonstrated central nervous system complications in patients' with COVID-19, but there is a gap in our understanding of the neuropathology. The lesions described in this case provide insight into the potential parainfectious processes affecting COVID-19 patients, which may direct clinical management and ongoing research into the disease. The clinical course of the patient also illustrates that during prolonged hospitalizations neurological complications of COVID may develop, which are particularly difficult to evaluate and appreciate in the critically ill.