Risk Factors and Outcomes Associated With the Development of Persistent Acute Kidney Injury in Non-Renal Solid Organ Transplant Recipients: Systematic Review and Meta-Analysis.

Persistent acute kidney injury (pAKI), compared with acute kidney injury (AKI) that resolves in <72 h, is associated with worse prognosis in critically ill patients. Definitions and prognosis of pAKI are not well characterized in solid organ transplant patients. Our aims were to investigate (a) definitions and incidence of pAKI; (b) association with clinical outcomes; and (c) risk factors for pAKI among heart, lung, and liver transplant recipients. We systematically reviewed the literature including PubMed, Embase, Web of Science, and Cochrane from inception to 8/1/2023 for human prospective and retrospective studies reporting on the development of pAKI in heart, lung, or liver transplant recipients. We assessed heterogeneity using Cochran's Q and I2. We identified 25 studies including 6330 patients. AKI (8%-71.6%) and pAKI (2.7%-55.1%) varied widely. Definitions of pAKI included 48-72 h (six studies), 7 days (three studies), 14 days (four studies), or more (12 studies). Risk factors included age, body mass index (BMI), diabetes, preoperative chronic kidney disease (CKD), intraoperative vasopressor use, and intraoperative circulatory support. pAKI was associated with new onset of CKD (odds ratio [OR] 1.41-11.2), graft dysfunction (OR 1.81-8.51), and long-term mortality (OR 3.01-13.96), although significant heterogeneity limited certainty of CKD and graft dysfunction outcome analyses. pAKI is common and is associated with worse mortality among liver and lung transplant recipients. Standardization of the nomenclature of AKI will be important in future studies (PROSPERO CRD42022371952).

Characterizing intensive care unit rounding teams using meta-data from the electronic health record.

PURPOSE: Teamwork is an important determinant of outcomes in the intensive care unit (ICU), yet the nature of individual ICU teams remains poorly understood. We examined whether meta-data in the form of digital signatures in the electronic health record (EHR) could be used to identify and characterize ICU teams. METHODS: We analyzed EHR data from 27 ICUs over one year. We linked intensivist physicians, nurses, and respiratory therapists to individual patients based on selected EHR meta-data. We then characterized ICU teams by their members' overall past experience and shared past experience; and used network analysis to characterize ICUs by their network's density and centralization. RESULTS: We identified 2327 unique providers and 30,892 unique care teams. Teams varied based on their average team member experience (median and total range: 262.2 shifts, 9.0-706.3) and average shared experience (median and total range: 13.2 shared shifts, 1.0-99.3). ICUs varied based on their network's density (median and total range: 0.12, 0.07-0.23), degree centralization (0.50, 0.35-0.65) and closeness centralization (0.45, 0.11-0.60). In a regression analysis, this variation was only partially explained by readily observable ICU characteristics. CONCLUSIONS: EHR meta-data can assist in the characterization of ICU teams, potentially providing novel insight into strategies to measure and improve team function in critical care.

Adoption and Deadoption of Medications to Treat Hospitalized Patients With COVID-19.

OBJECTIVES: The COVID-19 pandemic was characterized by rapidly evolving evidence regarding the efficacy of different therapies, as well as rapidly evolving health policies in response to that evidence. Data on adoption and deadoption are essential as we learn from this pandemic and prepare for future public health emergencies. DESIGN: We conducted an observational cohort study in which we determined patterns in the use of multiple medications to treat COVID-19: remdesivir, hydroxychloroquine, IV corticosteroids, tocilizumab, heparin-based anticoagulants, and ivermectin. We analyzed changes both overall and within subgroups of critically ill versus Noncritically ill patients. SETTING: Data from Optum's deidentified Claims-Clinical Dataset, which contains multicenter electronic health record data from U.S. hospitals. PATIENTS: Adults hospitalized with COVID-19 from January 2020 to June 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 141,533 eligible patients, 34,515 (24.4%) required admission to an ICU, 14,754 (10.4%) required mechanical ventilation, and 18,998 (13.4%) died during their hospitalization. Averaged over the entire time period, corticosteroid use was most common (47.0%), followed by remdesivir (33.2%), anticoagulants (19.3%), hydroxychloroquine (7.3%), and tocilizumab (3.4%). Usage patterns varied substantially across treatments. For example, hydroxychloroquine use peaked in March 2020 and leveled off to near zero by June 2020, whereas the use of remdesivir, corticosteroids, and tocilizumab all increased following press releases announcing positive results of large international trials. Ivermectin use increased slightly over the study period but was extremely rare overall (0.4%). CONCLUSIONS: During the COVID-19 pandemic, medication treatment patterns evolved reliably in response to emerging evidence and changes in policy. These findings may inform efforts to promote optimal adoption and deadoption of treatments for acute care conditions.