OBJECTIVES: Racial disparities in the United States healthcare system are well described across a variety of clinical settings. The ICU is a clinical environment with a higher acuity and mortality rate, potentially compounding the impact of disparities on patients. We sought to systematically analyze the literature to assess the prevalence of racial disparities in the ICU. DATA SOURCES:We conducted a comprehensive search of PubMed/ MEDLINE, Scopus, CINAHL, and the Cochrane Library. STUDY SELECTION:We identified articles that evaluated racial differences on outcomes among ICU patients in the United States. Two authors independently screened and selected articles for inclusion. DATA EXTRACTION:We dual-extracted study characteristics and outcomes that assessed for disparities in care (e.g., in-hospital mortality, ICU length of stay). Studies were assessed for bias using the Newcastle-Ottawa Scale.DATA SYNTHESIS: Of 1,325 articles screened, 25 articles were included (n = 751,796 patients). Studies demonstrated race-based differences in outcomes, including higher mortality rates for Black patients when compared with White patients. However, when controlling for confounding variables, such as severity of illness and hospital type, mortality differences based on race were no longer observed. Additionally, results revealed that Black patients experienced greater financial impacts during an ICU admission, were less likely to receive early tracheostomy, and were less likely to receive timely antibiotics than White patients. Many studies also observed differences in patients' end-of-life care, including lower rates on the quality of dying, less advanced care planning, and higher intensity of interventions at the end of life for Black patients. CONCLUSIONS:This systematic review found significant differences in the care and outcomes among ICU patients of different races. Mortality differences were largely explained by accompanying demographic and patient factors, highlighting the effect of structural inequalities on racial differences in mortality in the ICU. This systematic review provides evidence that structural inequalities in care persist in the ICU, which contribute to racial disparities in care. Future research should evaluate interventions to address inequality in the ICU.
Background Heterogeneous respiratory system static compliance (CRS) values and levels of hypoxemia in patients with novel coronavirus disease (COVID-19) requiring mechanical ventilation have been reported in previous small-case series or studies conducted at a national level. Methods We designed a retrospective observational cohort study with rapid data gathering from the international COVID-19 Critical Care Consortium study to comprehensively describe CRS—calculated as: tidal volume/[airway plateau pressure-positive end-expiratory pressure (PEEP)]—and its association with ventilatory management and outcomes of COVID-19 patients on mechanical ventilation (MV), admitted to intensive care units (ICU) worldwide. Results We studied 745 patients from 22 countries, who required admission to the ICU and MV from January 14 to December 31, 2020, and presented at least one value of CRS within the first seven days of MV. Median (IQR) age was 62 (52–71), patients were predominantly males (68%) and from Europe/North and South America (88%). CRS, within 48 h from endotracheal intubation, was available in 649 patients and was neither associated with the duration from onset of symptoms to commencement of MV (p = 0.417) nor with PaO2/FiO2 (p = 0.100). Females presented lower CRS than males (95% CI of CRS difference between females-males: − 11.8 to − 7.4 mL/cmH2O p < 0.001), and although females presented higher body mass index (BMI), association of BMI with CRS was marginal (p = 0.139). Ventilatory management varied across CRS range, resulting in a significant association between CRS and driving pressure (estimated decrease − 0.31 cmH2O/L per mL/cmH20 of CRS, 95% CI − 0.48 to − 0.14, p < 0.001). Overall, 28-day ICU mortality, accounting for the competing risk of being discharged within the period, was 35.6% (SE 1.7). Cox proportional hazard analysis demonstrated that CRS (+ 10 mL/cm H2O) was only associated with being discharge from the ICU within 28 days (HR 1.14, 95% CI 1.02–1.28, p = 0.018). Conclusions This multicentre report provides a comprehensive account of CRS in COVID-19 patients on MV. CRS measured within 48 h from commencement of MV has marginal predictive value for 28-day mortality, but was associated with being discharged from ICU within the same period. Trial documentation: Available at https://www.covid-critical.com/study. Trial registration: ACTRN12620000421932.
BackgroundRisk calculation is increasingly used in lipid management, congestive heart failure, and atrial fibrillation. The risk scores are then used for decisions about statin use, anticoagulation, and implantable defibrillator use. Calculating risks for patients and making decisions based on these risks is often done at the point of care and is an additional time burden for clinicians that can be decreased by automating the tasks and using clinical decision-making support.MethodsUsing Morae Recorder software, we timed 30 healthcare providers tasked with calculating the overall risk of cardiovascular events, sudden death in heart failure, and thrombotic event risk in atrial fibrillation. Risk calculators used were the American College of Cardiology Atherosclerotic Cardiovascular Disease risk calculator (AHA-ASCVD risk), Seattle Heart Failure Model (SHFM risk), and CHA2DS2VASc. We also timed the 30 providers using Ask Mayo Expert care process models for lipid management, heart failure management, and atrial fibrillation management based on the calculated risk scores. We used the Mayo Clinic primary care panel to estimate time for calculating an entire panel risk.ResultsMean provider times to complete the CHA2DS2VASc, AHA-ASCVD risk, and SHFM were 36, 45, and 171 s respectively. For decision making about atrial fibrillation, lipids, and heart failure, the mean times (including risk calculations) were 85, 110, and 347 s respectively.ConclusionEven under best case circumstances, providers take a significant amount of time to complete risk assessments. For a complete panel of patients this can lead to hours of time required to make decisions about prescribing statins, use of anticoagulation, and medications for heart failure. Informatics solutions are needed to capture data in the medical record and serve up automatically calculated risk assessments to physicians and other providers at the point of care.
Racial disparities in the United States healthcare system are well described across a variety of clinical settings. The intensive care unit (ICU) poses a unique environment with a higher acuity and mortality rate, potentially compounding the impact of disparities on patients. We sought to systematically analyze the literature to assess the prevalence of racial disparities in the ICU, including effects on mortality, length of stay, and palliative care. Methods: We conducted a comprehensive search of PubMed, CINAHL, Scopus and the Cochrane Library to identify articles that evaluated for racial differences of any outcome in a cohort of ICU patients in the United States. Two authors independently screened and selected articles for inclusion. We then dual-extracted study outcomes that assessed for disparities in care (e.g., inhospital mortality, 30-day mortality, rates of antibiotic use). Studies were assessed for bias using the Newcastle-Ottawa Quality Assessment form. Results: 25 articles were included (n= 649, 384 patients). Studies demonstrated differences in race based on varying outcomes, including higher mortality rates for black patients when compared to white patients. However, when controlling for confounding variables, including severity of illness and hospital type, mortality differences based on race were not observed. Additionally, Black patients had higher loss of family savings during an ICU admission, were less likely to receive certain specialty care, less likely to receive early tracheostomy, and less likely to receive timely antibiotics. Many studies revealed significant differences in end-of-life care, including lower rates on the quality of dying, less advanced care planning, and higher intensity of interventions at the end of life. Conclusions: These data demonstrate a difference in care and outcomes between white and non-white patients. However, once confounding factors were accounted for, differences in mortality disappeared. This provides evidence that structural inequalities in care persist in the ICU, which contribute to many racial disparities in care. Future research should evaluate interventions to address disparities in the ICU and seek to further understand racial differences in patient preference, knowledge and attitudes of care in the ICU.
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