Search

Atypical antipsychotics are used in cardiac intensive care units (CICU) to treat delirium despite limited data on safety in patients with acute cardiovascular conditions. Patients treated with these agents may be at higher risk for adverse events such as QTc prolongation and arrhythmias. We performed a retrospective cohort study of 144 adult patients who were not receiving antipsychotics before admission and received olanzapine (n = 50) or quetiapine (n = 94) in the Michigan Medicine CICU. Data on baseline characteristics, antipsychotic dose and duration, length of stay, and adverse events were collected. Adverse events included ventricular tachycardia (sustained ventricular tachycardia attributed to the medication), hypotension (systolic blood pressure90 mm Hg attributed to the medication), and QTc prolongation (QTc increase by ≥60 ms or to an interval ≥500 ms). Twenty-six patients (18%) experienced an adverse event. Of those adverse events, 20 patients (14%) experienced QTc prolongation, 3 patients (2%) had ventricular tachycardia, and 3 patients (2%) had hypotension. Patients who received quetiapine had a higher rate of adverse events (25% vs 6%, p = 0.01) including QTc prolongation (18% vs 6%, p = 0.046). Intensive care unit length of stay was shorter in patients who received olanzapine (6.5 vs 9.5 days, p = 0.047). Eighteen patients (13%) had their antipsychotic continued at discharge from the hospital. In conclusion, QTc prolongation was more common in patients treated with quetiapine versus olanzapine although the number of events was relatively low with both agents in a CICU cohort.

Hospital readmission is a key metric of hospital quality, such as for comparing Veterans Affairs (VA) hospitals to private sector hospitals. To calculate readmission rates, one must first identify individual hospitalizations. However, in the VA Corporate Data Warehouse (CDW), data are organized by “bedded stays,” that is, any stay in a healthcare facility where a patient is provided a bed, not hospitalizations. Thus, CDW data poses several challenges to identifying hospitalizations including: (1) bedded stays include both non-acute inpatient stays (i.e. nursing home, mental health) and acute inpatient hospital care; (2) transfers between VA facilities appear as separate bedded stays; and (3) VA care may also be fragmented by non-VA care. Thus, we sought to develop a rigorous method to identify acute hospitalizations using the VA CDW. We examined all VA bedded stays with an admission date in 2009. Non-acute portions of a stay were dropped. VA to VA transfers were merged when consecutive discharge and admission dates were within one calendar day. Finally, hospitalizations that occurred in a non-VA facility were merged. The 30-day readmission rate was calculated at each step of the algorithm to demonstrate the impact. The total number of VA medical hospitalizations in 2009 with live discharges was 505,861. The 30-day readmission rate after adjusting for VA to VA transfers and incorporating non-VA care was 18.3% (95% confidence interval (CI): 18.2, 18.4%).

Background:We sought to determine the incidence of community-onset and hospital-acquired coinfection in patients hospitalized with coronavirus disease 2019 (COVID-19) and to evaluate associated predictors and outcomes.Methods:In this multicenter retrospective cohort study of patients hospitalized for COVID-19 from March 2020 to August 2020 across 38 Michigan hospitals, we assessed prevalence, predictors, and outcomes of community-onset and hospital-acquired coinfections. In-hospital and 60-day mortality, readmission, discharge to long-term care facility (LTCF), and mechanical ventilation duration were assessed for patients with versus without coinfection.Results:Of 2,205 patients with COVID-19, 141 (6.4%) had a coinfection: 3.0% community onset and 3.4% hospital acquired. Of patients without coinfection, 64.9% received antibiotics. Community-onset coinfection predictors included admission from an LTCF (OR, 3.98; 95% CI, 2.34–6.76; P < .001) and admission to intensive care (OR, 4.34; 95% CI, 2.87–6.55; P < .001). Hospital-acquired coinfection predictors included fever (OR, 2.46; 95% CI, 1.15–5.27; P = .02) and advanced respiratory support (OR, 40.72; 95% CI, 13.49–122.93; P < .001). Patients with (vs without) community-onset coinfection had longer mechanical ventilation (OR, 3.31; 95% CI, 1.67–6.56; P = .001) and higher in-hospital mortality (OR, 1.90; 95% CI, 1.06–3.40; P = .03) and 60-day mortality (OR, 1.86; 95% CI, 1.05–3.29; P = .03). Patients with (vs without) hospital-acquired coinfection had higher discharge to LTCF (OR, 8.48; 95% CI, 3.30–21.76; P < .001), in-hospital mortality (OR, 4.17; 95% CI, 2.37–7.33; P ≤ .001), and 60-day mortality (OR, 3.66; 95% CI, 2.11–6.33; P ≤ .001).Conclusion:Despite community-onset and hospital-acquired coinfection being uncommon, most patients hospitalized with COVID-19 received antibiotics. Admission from LTCF and to ICU were associated with increased risk of community-onset coinfection. Future studies should prospectively validate predictors of COVID-19 coinfection to facilitate the reduction of antibiotic use.

Rationale: Quantifying acute respiratory disease syndrome (ARDS) severity is essential for prognostic enrichment to stratify patients for invasive or higher-risk treatments; however, the comparative performance of many ARDS severity measures is unknown. Objectives: To validate ARDS severity measures for their ability to predict hospital mortality and an ARDS-specific outcome (defined as death from pulmonary dysfunction or the need for extracorporeal membrane oxygenation [ECMO] therapy). Methods: We compared five individual ARDS severity measures including the ratio of arterial oxygen tension/pressure to fraction of inspired oxygen (Pa(O(2))/Fi (O(2)) ratio), oxygenation index, ventilatory ratio, lung compliance, and radiologic assessment of lung edema (RALE); two ARDS composite severity scores including the Murray Lung Injury Score, and a novel score combining RALE, Pa(O(2))/Fi (O(2)) ratio, and ventilatory ratio; and the Acute Physiology and Chronic Health Evaluation IV score, using data collected at ARDS onset in patients hospitalized at a single center in 2016 and 2017. Discrimination of hospital mortality and the ARDS-specific outcome was evaluated using the area under the receiver operator characteristic curve (AUROC). Measure calibration was also evaluated. Results: Among 340 patients with ARDS, 125 (37%) died during hospitalization and 36 (10.6%) had the ARDS-specific outcome, including one who received ECMO. Among the five individual ARDS severity measures, the RALE score had the highest discrimination of the ARDS-specific outcome (AUROC = 0.67; 95% confidence interval [CI], 0.58–0.77), although other ARDS severity measures had similar performance. However, their ability to discriminate overall mortality was low. In contrast, the Acute Physiology and Chronic Health Evaluation IV score best discriminated overall mortality (AUROC = 0.73; 95% CI, 0.67–0.79) but was unable to discriminate the ARDS-specific outcome (AUROC = 0.54; 95% CI, 0.44–0.65). Among ARDS composite severity scores, the lung injury score had an AUROC = 0.67 (95% CI, 0.58–0.75) for the ARDS-specific outcome whereas the novel score had an AUROC = 0.70 (95% CI, 0.61–0.79). Patients grouped by quartile of the novel score had a 6%, 2%, 10%, and 24% rate of the ARDS-specific outcome. Conclusions: Although most ARDS severity measures had poor discrimination of hospital mortality, they performed better at predicting death from severe pulmonary dysfunction or ECMO needs. A novel composite score had the highest discrimination of this outcome.

Background Existing sepsis quality improvement initiatives focus on recognition and treatment of sepsis upon hospital admission. Yet many patients are evaluated in the clinic within 1 day of sepsis hospitalization. Objectives To determine the circumstances of clinic visits that precede sepsis hospitalization, including illness severity, whether patients are referred to the hospital, and time lapse and change in illness severity between clinic and hospital evaluation. Methods In a retrospective cohort study at a tertiary academic medical center, data from electronic medical records were collected for all adult patients evaluated in an outpatient clinic within 1 day of sepsis hospitalization in 2017. Results Of 1450 patients hospitalized with sepsis, 118 had an established outpatient provider and a clinic visit within 1 day of admission and thus were included. During the clinic visit, 47 patients (39.8%) had a quick Sequential Organ Failure Assessment (qSOFA) score ≥1, and 59 (50.0%) had vital sign abnormalities. Most (74, 62.7%) were sent directly to the emergency department or hospital. Upon emergency department/hospital presentation, 62 patients (52.5%) had a worsening qSOFA score and/ or vital signs and 27 (22.9%) had worsening of multiple parameters. Median time lapse from clinic to emergency department/hospital evaluation was 3.2 hours. Conclusions One in 10 patients hospitalized for sepsis had been evaluated in a clinic within 1 day of admission. At that clinic visit, most patients had an elevated qSOFA score or abnormal vital signs and a majority were sent directly to the emergency department/hospital. Half experienced clinical deterioration between the clinic visit and arrival in the emergency department/hospital.

Supplemental Digital Content is available in the text., OBJECTIVES: To determine whether the previously described trend of improving mortality in people with coronavirus disease 2019 in critical care during the first wave was maintained, plateaued, or reversed during the second wave in United Kingdom, when B117 became the dominant strain. DESIGN: National retrospective cohort study. SETTING: All English hospital trusts (i.e., groups of hospitals functioning as single operational units), reporting critical care admissions (high dependency unit and ICU) to the Coronavirus Disease 2019 Hospitalization in England Surveillance System. PATIENTS: A total of 49,862 (34,336 high dependency unit and 15,526 ICU) patients admitted between March 1, 2020, and January 31, 2021 (inclusive). INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: The primary outcome was inhospital 28-day mortality by calendar month of admission, from March 2020 to January 2021. Unadjusted mortality was estimated, and Cox proportional hazard models were used to estimate adjusted mortality, controlling for age, sex, ethnicity, major comorbidities, social deprivation, geographic location, and operational strain (using bed occupancy as a proxy). Mortality fell to trough levels in June 2020 (ICU: 22.5% [95% CI, 18.2–27.4], high dependency unit: 8.0% [95% CI, 6.4–9.6]) but then subsequently increased up to January 2021: (ICU: 30.6% [95% CI, 29.0–32.2] and high dependency unit, 16.2% [95% CI, 15.3–17.1]). Comparing patients admitted during June–September 2020 with those admitted during December 2020–January 2021, the adjusted mortality was 59% (CI range, 39–82) higher in high dependency unit and 88% (CI range, 62–118) higher in ICU for the later period. This increased mortality was seen in all subgroups including those under 65. CONCLUSIONS: There was a marked deterioration in outcomes for patients admitted to critical care at the peak of the second wave of coronavirus disease 2019 in United Kingdom (December 2020–January 2021), compared with the post-first-wave period (June 2020–September 2020). The deterioration was independent of recorded patient characteristics and occupancy levels. Further research is required to determine to what extent this deterioration reflects the impact of the B117 variant of concern.

Background As more individuals survive sepsis, there is an urgent need to understand its effects on patient-reported outcomes. Research Question What is the effect of sepsis on self-rated health, and what role, if any, does functional disability play in mediating this effect? Study Design and Methods We conducted a survey- and administrative claims-based retrospective cohort study using the US Health and Retirement Study, a nationally representative cohort-based survey of older adults in the United States, from 2000 through 2016. We matched Medicare beneficiaries hospitalized with sepsis in 2000 to 2008 to nonhospitalized individuals. Self-rated health and functional disability were tracked biannually for 8 years. Differences in self-rated health between the cohorts were measured using mixed models with and without controlling for changes in functional disability. Results Seven hundred fifty-eight individuals with sepsis were matched 1:1 to 758 nonhospitalized individuals, all aged 65 years and older. Among survivors, sepsis was associated with worse self-rated health in years 2 and 4 (adjusted absolute difference in self-rated health on a 5-point scale in year 2: −0.24 [95% CI, −0.38 to −0.10] and year 4: −0.17 [95% CI, −0.33 to −0.02]) but not in years 6 or 8. After accounting for changes in functional status, the association between sepsis and self-rated health was still present but reduced in year 2 (adjusted absolute difference in self-rated health, −0.18 [95% CI, −0.31 to −0.05]) and was not present in years 4, 6, or 8. Interpretation Self-rated health worsened initially after sepsis but returned to the level of that of nonhospitalized control subjects by year 6. Mitigating sepsis-related functional disability may play a key role in improving self-rated health after sepsis.

PURPOSE OF REVIEW: Critical illness survivorship is associated with new and worsening physical, cognitive, and emotional status. Survivors are vulnerable to further health set-backs, most commonly because of infection and exacerbation of chronic medical conditions. Awareness of survivors' challenges are important given the anticipated rise in critical illness survivors because of SARS-CoV-2 viral sepsis. RECENT FINDINGS: Studies continue to document challenges of critical illness survivorship. Beyond the cognitive, physical, and mental health sequelae encompassed by postintensive case syndrome, patients commonly experience persistent immunosuppression, re-hospitalization, inability to resume prior employment, and reduced quality of life. Although recommended practices for enhancing recovery from sepsis are associated with better outcomes, only a minority of patients receive all recommended practices. ICU follow-up programs or peer support groups remain important interventions to learn about and address the multifaceted challenges of critical illness survivorship, but there is little evidence of benefit to date. SUMMARY: Survivors of sepsis and critical illness commonly experience impaired health status, reduced quality of life, and inability to return to prior employment. Although the challenges of critical illness survivorship are increasingly well documented, there are relatively few studies on enhancing recovery. Future studies must focus on identifying best practices for optimizing recovery and strategies to promote their implementation.

Objective: Care coordination is a national priority. Post-acute care use and hospital readmission appear to be common after critical illness. It is unknown whether specialty critical care units have different readmission rates and what these trends have been over time. Methods: In this retrospective cohort study, a cohort of 53,539 medical/surgical patients who were treated in a critical care unit during their index admission were compared with 209,686 patients who were not treated in a critical care unit. The primary outcome was 30-day all cause hospital readmission. Secondary outcomes included post-acute care resource use and immediate readmission, defined as within 7 days of discharge. Results: Compared to patients discharged after an index hospitalization without critical illness, surviving patients following ICU admission were not more likely to be rehospitalized within 30 days (15.8 vs. 16.1%, p = 0.08). However, they were more likely to receive post-acute care services (45.3% vs. 70.9%, p < 0.001) as well as be rehospitalized within 7 days (5.2 vs. 6.0%, p < 0.001). Post-acute care use and 30-day readmission rates varied by ICU type, the latter ranging from 11.7% after admission in a cardiothoracic critical care unit to 23.1% after admission in a medical critical care unit. 30-day readmission after ICU admission did not decline between 2010 and 2015 (p = 0.38). Readmission rates declined over time for 2 of 4 targeted conditions (heart failure and chronic obstructive pulmonary disease), but only when the hospitalization did not include ICU admission. Conclusions: Rehospitalization for survivors following ICU admission is common across all specialty critical care units. Post-acute care use is also common for this population of patients. Overall trends for readmission rates after critical illness did not change over time, and readmission reductions for targeted conditions were limited to hospitalizations that did not include an ICU admission.

Objectives To determine clinician accuracy in the identification and prediction of multiple organ dysfunction syndrome. Design Prospective cohort study. Setting University of Michigan's C.S. Mott Children's Hospital PICU. Patients Patients admitted to the PICU with an anticipated PICU length of stay greater than 48 hours. Interventions None. Measurements and main results For each patient, the clinical team (attending, fellow, resident/nurse practitioner) was surveyed regarding existing and anticipated organ dysfunction. The primary outcomes were clinicians' accuracy at identifying multiple organ dysfunction syndrome and predicting new or progressive multiple organ dysfunction syndrome, compared to the objective assessment of multiple organ dysfunction syndrome using Proulx criteria. We also measured sensitivity, specificity, negative and positive predictive values, and negative and positive likelihood ratios of clinician assessments. We tested for differences in accuracy by clinician type using chi-square tests. Clinicians rated their confidence in prediction on a 5-point Likert scale. There were 476 eligible PICU admissions, for whom 1,218 surveys were completed. Multiple organ dysfunction syndrome was present in 89 patients (18.7%) at enrollment, and new or progressive multiple organ dysfunction syndrome occurred in 39 (8.2%). Clinicians correctly identified multiple organ dysfunction syndrome with 79.9% accuracy and predicted additional organ dysfunction with 82.6% accuracy. However, the positive and negative likelihood ratios for new or progressive multiple organ dysfunction syndrome prediction were 3.0 and 0.7, respectively, indicating a weak relationship between the clinician prediction and development of new or progressive multiple organ dysfunction syndrome. The positive predictive value of new or progressive multiple organ dysfunction syndrome prediction was just 22.1%. We found no differences in accuracy by clinician type for either identification of multiple organ dysfunction syndrome (80.2% vs 78.2% vs 81.0%; p = 0.57) or prediction of new or progressive multiple organ dysfunction syndrome (84.8% vs 82.8% vs 80.3%; p = 0.26) for attendings, fellows, and residents/nurse practitioners, respectively. There was a weak correlation between the confidence and accuracy of prediction (pairwise correlation coefficient, 0.26; p Conclusions PICU clinicians correctly identified multiple organ dysfunction syndrome and predicted new or progressive multiple organ dysfunction syndrome with 80% accuracy. However, only 8% of patients developed new or progressive multiple organ dysfunction syndrome, so accuracy was largely due to true negative predictions. The positive predictive value for new or progressive multiple organ dysfunction syndrome prediction was just 22%. Accuracy did not differ by clinician type, but was correlated with self-rated confidence and was higher for negative predictions.

Background Acute hypoxemic respiratory failure (AHRF) and acute respiratory distress syndrome (ARDS) are associated with high in-hospital mortality. However, in cohorts of ARDS patients from the 1990s, patients more commonly died from sepsis or multi-organ failure rather than refractory hypoxemia. Given increased attention to lung-protective ventilation and sepsis treatment in the past 25 years, we hypothesized that causes of death may be different among contemporary cohorts. These differences may provide clinicians with insight into targets for future therapeutic interventions. Methods We identified adult patients hospitalized at a single tertiary care center (2016–2017) with AHRF, defined as PaO2/FiO2 ≤ 300 while receiving invasive mechanical ventilation for > 12 h, who died during hospitalization. ARDS was adjudicated by multiple physicians using the Berlin definition. Separate abstractors blinded to ARDS status collected data on organ dysfunction and withdrawal of life support using a standardized tool. The primary cause of death was defined as the organ system that most directly contributed to death or withdrawal of life support. Results We identified 385 decedents with AHRF, of whom 127 (33%) had ARDS. The most common primary causes of death were sepsis (26%), pulmonary dysfunction (22%), and neurologic dysfunction (19%). Multi-organ failure was present in 70% at time of death, most commonly due to sepsis (50% of all patients), and 70% were on significant respiratory support at the time of death. Only 2% of patients had insupportable oxygenation or ventilation. Eighty-five percent died following withdrawal of life support. Patients with ARDS more often had pulmonary dysfunction as the primary cause of death (28% vs 19%; p = 0.04) and were also more likely to die while requiring significant respiratory support (82% vs 64%; p

Intensive care survivors often experience post-intensive care sequelae, which are frequently gathered together under the term “post-intensive care syndrome” (PICS). The consequences of PICS on quality of life, health-related costs and hospital readmissions are real public health problems. In the present Viewpoint, we summarize current knowledge and gaps in our understanding of PICS and approaches to management., SCOPUS: ar.j, info:eu-repo/semantics/published

BACKGROUND Hospital-specific template matching is a newer method of hospital performance measurement that may be fairer than regression-based benchmarking. However, it has been tested in only limited research settings. OBJECTIVE The objective of this study was to test the feasibility of hospital-specific template matching assessments in the Veterans Affairs (VA) health care system and determine power to detect greater-than-expected 30-day mortality. RESEARCH DESIGN Observational cohort study with hospital-specific template matching assessment. For each VA hospital, the 30-day mortality of a representative subset of hospitalizations was compared with the pooled mortality from matched hospitalizations at a set of comparison VA hospitals treating sufficiently similar patients. The simulation was used to determine power to detect greater-than-expected mortality. SUBJECTS A total of 556,266 hospitalizations at 122 VA hospitals in 2017. MEASURES A number of comparison hospitals identified per hospital; 30-day mortality. RESULTS Each hospital had a median of 38 comparison hospitals (interquartile range: 33, 44) identified, and 116 (95.1%) had at least 20 comparison hospitals. In total, 8 hospitals (6.6%) had a significantly lower 30-day mortality than their benchmark, 5 hospitals (4.1%) had a significantly higher 30-day mortality, and the remaining 109 hospitals (89.3%) were similar to their benchmark. Power to detect a standardized mortality ratio of 2.0 ranged from 72.5% to 79.4% for a hospital with the fewest (6) versus most (64) comparison hospitals. CONCLUSIONS Hospital-specific template matching may be feasible for assessing hospital performance in the diverse VA health care system, but further refinements are needed to optimize the approach before operational use. Our findings are likely applicable to other large and diverse multihospital systems.

Although characteristics and in-hospital outcomes for persons with coronavirus disease 2019 (COVID-19) have been well described, less is known about the longer-term outcomes of hospitalized patients Although characteristics and in-hospital outcomes for persons with COVID-19 have been well described, less is known about the longer-term outcomes of hospitalized patients Here, a study that aims to describe the 6-day postdischarge clinical, financial, and mental health outcomes of patients with COVID-19 using an observational cohort study is offered

Sepsis, life-threatening organ dysfunction secondary to infection, hospitalizes nearly 75,000 children each year in the United States. Most children survive sepsis. However, there is increasing recognition of the longer-term consequences of pediatric sepsis hospitalization on both the child and their family, including medical, psychosocial, and financial impacts. Here, we describe family spillover effects (the impact of illness on caregivers) of pediatric sepsis, why measurement of family spillover effects is important, and the ways in which family spillover effects can be measured.

Background\ud Sepsis poses a global threat to millions of lives. The Surviving Sepsis Campaign (SSC) guidelines provide evidence-based recommendations on the recognition and management of sepsis and its complications.\ud Methods\ud We formed a panel of 60 experts from 22 countries and 11 members of the public. The panel prioritized questions that are relevant to the recognition and management of sepsis and septic shock in adults. New questions and sections were addressed, relative to the previous guidelines. These questions were grouped under 6 subgroups (screening and early treatment, infection, hemodynamics, ventilation, additional therapies, and long-term outcomes and goals of care). With input from the panel and methodologists, professional medical librarians performed the search strategy tailored to either specific questions or a group of relevant questions. A dedicated systematic review team performed screening and data abstraction when indicated. For each question, the methodologists, with input from panel members, summarized the evidence assessed and graded the quality of evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. The panel generated recommendations using the evidence-to-decision framework. Recommendations were either strong or weak, or in the form of best practice statements. When evidence was insufficient to support a recommendation, the panel was surveyed to generate “in our practice” statements.\ud Results\ud The SSC panel issued 93 statements: 15 best practice statements, 15 strong recommendations, and 54 weak recommendations and no recommendation was provided for 9 questions. The recommendations address several important clinical areas related to screening tools, acute resuscitation strategies, management of fluids and vasoactive agents, antimicrobials and diagnostic tests and the use of additional therapies, ventilation management, goals of care, and post sepsis care.\ud Conclusion\ud The SSC panel issued evidence-based recommendations to help support key stakeholders caring for adults with sepsis or septic shock and their families.

Key Points Question How has timing of antibiotics for sepsis changed over time in US Department of Veterans Affairs Hospitals? Findings In this cohort of 111 385 veterans hospitalized with sepsis from 2013 to 2018, median time to antibiotics declined by 9 minutes per year. However, there was significant variation in time to antibiotics across hospitals, even after adjustment for patient characteristics. Meaning These findings suggest that there is potential for performance improvement for sepsis hospitalizations, but efforts to further accelerate time-to-antibiotics must be weighed against the risks of overtreatment., This cohort study examines temporal trends and variations in time-to-antibiotics for sepsis in the US Department of Veterans Affairs health care system., Importance It is unclear whether antimicrobial timing for sepsis has changed outside of performance incentive initiatives. Objective To examine temporal trends and variation in time-to-antibiotics for sepsis in the US Department of Veterans Affairs (VA) health care system. Design, Setting, and Participants This observational cohort study included 130 VA hospitals from 2013 to 2018. Participants included all patients admitted to the hospital via the emergency department with sepsis from 2013 to 2018, using a definition adapted from the Centers for Disease Control and Prevention Adult Sepsis Event definition, which requires evidence of suspected infection, acute organ dysfunction, and systemic antimicrobial therapy within 12 hours of presentation. Data were analyzed from October 6, 2020, to July 1, 2021. Exposures Time from presentation to antibiotic administration. Main Outcomes and Measures The main outcome was differences in time-to-antibiotics across study periods, hospitals, and patient subgroups defined by presenting temperature and blood pressure. Temporal trends in time-to-antibiotics were measured overall and by subgroups. Hospital-level variation in time-to-antibiotics was quantified after adjusting for differences in patient characteristics using multilevel linear regression models. Results A total of 111 385 hospitalizations for sepsis were identified, including 107 547 men (96.6%) men and 3838 women (3.4%) with a median (interquartile range [IQR]) age of 68 (62-77) years. A total of 7574 patients (6.8%) died in the hospital, and 13 855 patients (12.4%) died within 30 days. Median (IQR) time-to-antibiotics was 3.9 (2.4-6.5) hours but differed by presenting characteristics. Unadjusted median (IQR) time-to-antibiotics decreased over time, from 4.5 (2.7-7.1) hours during 2013 to 2014 to 3.5 (2.2-5.9) hours during 2017 to 2018 (P

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a global pandemic. Beyond the well-described respiratory manifestations, SARS-CoV-2 may cause a variety of neurologic complications, including headaches, alteration in taste and smell, encephalopathy, cerebrovascular disease, myopathy, psychiatric diseases, and ocular disorders. Herein we describe SARS-CoV-2's mechanism of neuroinvasion and the epidemiology, outcomes, and treatments for neurologic manifestations of COVID-19. Expected final online publication date for the Annual Review of Medicine, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

ObjectiveTo describe patient characteristics, symptoms, patterns of care and outcomes for patients hospitalised with COVID-19 in Michigan.DesignMulticentre retrospective cohort study.Setting32 acute care hospitals in the state of Michigan.ParticipantsPatients discharged (16 March–11 May 2020) with suspected or confirmed COVID-19 were identified. Trained abstractors collected demographic information on all patients and detailed clinical data on a subset of COVID-19-positive patients.Primary outcome measurementsPatient characteristics, treatment and outcomes including cardiopulmonary resuscitation, mortality and venous thromboembolism within and across hospitals.ResultsDemographic-only data from 1593 COVID-19-positive and 1259 persons under investigation discharges were collected. Among 1024 cases with detailed data, the median age was 63 years; median body mass index was 30.6; and 51.4% were black. Cough, fever and shortness of breath were the top symptoms. 37.2% reported a known COVID-19 contact; 7.0% were healthcare workers; and 16.1% presented from congregated living facilities.During hospitalisation, 232 (22.7%) patients were treated in an intensive care unit (ICU); 558 (54.9%) in a ‘cohorted’ unit; 161 (15.7%) received mechanical ventilation; and 90 (8.8%) received high-flow nasal cannula. ICU patients more often received hydroxychloroquine (66% vs 46%), corticosteroids (34% vs 18%) and antibiotic therapy (92% vs 71%) than general ward patients (pAcross 14 hospitals, the proportion of patients admitted directly to an ICU ranged from 0% to 43.8%; mechanical ventilation on admission from 0% to 12.8%; mortality from 7.9% to 45.7%. Use of at least one COVID-19-specific therapy varied from 32% to 96.3% across sites.ConclusionsDuring the early days of the Michigan outbreak of COVID-19, patient characteristics, treatment and outcomes varied widely within and across hospitals.

Rationale: Sepsis commonly results in elevated serum troponin levels and increased risk for postsepsis cardiovascular complications; however, the association between troponin levels during sepsis and cardiovascular complications after sepsis is unclear. Objectives: To evaluate the association between serum troponin levels during sepsis and 1 year after sepsis cardiovascular events. Methods: We analyzed adults aged ⩾40 years without preexisting cardiovascular disease within 5 years, admitted with sepsis across 21 hospitals from 2011 to 2017. Peak serum troponin I levels during sepsis were grouped as normal (⩽0.04 ng/ml) or tertiles of abnormal (>0.04 to ⩽0.09 ng/ml, >0.09 to ⩽0.42 ng/ml, or >0.42 ng/ml). Multivariable adjusted cause-specific Cox proportional hazards models with death as a competing risk were used to assess associations between peak troponin I levels and a composite cardiovascular outcome (atherosclerotic cardiovascular disease, atrial fibrillation, and heart failure) in the year following sepsis. Models were adjusted for presepsis and intrasepsis factors considered potential confounders. Measurements and Main Results: Among 14,046 eligible adults with troponin I measured, 2,012 (14.3%) experienced the composite cardiovascular outcome, including 832 (10.9%) patients with normal troponin levels, as compared with 370 (17.3%), 376 (17.6%), and 434 (20.3%) patients within each sequential abnormal troponin tertile, respectively (P 0.42) = 1.77; 95% CI, 1.56–2.00). Conclusions: Among patients without preexisting cardiovascular disease, troponin elevation during sepsis identified patients at increased risk for postsepsis cardiovascular complications. Strategies to mitigate cardiovascular complications among this high-risk subset of patients are warranted.

OBJECTIVE Cancer and its treatment are known to be important risk factors for sepsis, contributing to an estimated 12% of U.S. sepsis admissions in the 1990s. However, cancer treatment has evolved markedly over the past 2 decades. We sought to examine how cancer-related sepsis differs from non-cancer-related sepsis. DESIGN Observational cohort. SETTING National Readmissions Database (2013-2014), containing all-payer claims for 49% of U.S. POPULATION PATIENTS A total of 1,104,363 sepsis hospitalizations. INTERVENTIONS We identified sepsis hospitalizations in the U.S. National Readmissions Database using explicit codes for severe sepsis, septic shock, or Dombrovskiy criteria (concomitant codes for infection and organ dysfunction). We classified hospitalizations as cancer-related versus non-cancer-related sepsis based on the presence of secondary diagnosis codes for malignancy. We compared characteristics (site of infection and organ dysfunction) and outcomes (in-hospital mortality and 30-d readmissions) of cancer-related versus non-cancer-related sepsis hospitalizations. We also completed subgroup analyses by age, cancer types, and specific cancer diagnoses. MEASUREMENTS AND MAIN RESULTS There were 27,481,517 hospitalizations in National Readmissions Database 2013-2014, of which 1,104,363 (4.0%) were for sepsis and 4,150,998 (15.1%) were cancer related. In-hospital mortality in cancer-related sepsis was 27.9% versus 19.5% in non-cancer-related sepsis. The median count of organ dysfunctions was indistinguishable, but the rate of specific organ dysfunctions differed by small amounts (e.g., hematologic dysfunction 20.1% in cancer-related sepsis vs 16.6% in non-cancer-related sepsis; p < 0.001). Cancer-related sepsis was associated with an adjusted absolute increase in in-hospital mortality ranging from 2.2% to 15.2% compared with non-cancer-related sepsis. The mortality difference was greatest in younger adults and waned with age. Patients (23.2%) discharged from cancer-related sepsis were rehospitalized within 30 days, compared with 20.1% in non-cancer-related sepsis (p < 0.001). CONCLUSIONS In this cohort of over 1 million U.S. sepsis hospitalizations, more than one in five were cancer related. The difference in mortality varies substantially across age spectrum and is greatest in younger adults. Readmissions were more common after cancer-related sepsis.

Background To study patient physiology throughout a period of acute hospitalization, we sought to create accessible, standardized nationwide data at the level of the individual patient-facility-day. This methodology paper summarizes the development, organization, and characteristics of the Veterans Affairs Patient Database 2014–2017 (VAPD 2014–2017). The VAPD 2014–2017 contains acute hospitalizations from all parts of the nationwide VA healthcare system with daily physiology including clinical data (labs, vitals, medications, risk scores, etc.), intensive care unit (ICU) indicators, facility, patient, and hospitalization characteristics. Methods The VA data structure and database organization represents a complex multi-hospital system. We define a single-site hospitalization as one or more consecutive stays with an acute treating specialty at a single facility. The VAPD 2014–2017 is structured at the patient-facility-day level, where every patient-day in a hospital is a row with separate identification variables for facility, patient, and hospitalization. The VAPD 2014–2017 includes daily laboratory, vital signs, and inpatient medication. Such data were validated and verified through lab value range and comparison with patient charts. Sepsis, risk scores, and organ dysfunction definitions were standardized and calculated. Results We identified 565,242 single-site hospitalizations (SSHs) in 2014; 558,060 SSHs in 2015; 553,961 SSHs in 2016; and 550,236 SSHs in 2017 at 141 VA hospitals. The average length of stay was four days for all study years. In-hospital mortality decreased from 2014 to 2017 (1.7 to 1.4%), 30-day readmission rates increased from 15.3% in 2014 to 15.6% in 2017; 30-day mortality also decreased from 4.4% in 2014 to 4.1% in 2017. From 2014 to 2017, there were 107,512 (4.8%) of SSHs that met the Center for Disease Control and Prevention’s Electronic Health Record-based retrospective definition of sepsis. Conclusion The VAPD 2014–2017 represents a large, standardized collection of granular data from a heterogeneous nationwide healthcare system. It is also a direct resource for studying the evolution of inpatient physiology during both acute and critical illness. Electronic supplementary material The online version of this article (10.1186/s12874-019-0740-x) contains supplementary material, which is available to authorized users.

OBJECTIVE: Severe sepsis is a significant cause of healthcare use and morbidity among pediatric patients, but little is known about readmission diagnoses. We sought to determine the most common readmission diagnoses after pediatric severe sepsis, the extent to which post-sepsis readmissions may be potentially preventable, and whether patterns of readmission diagnoses differ compared to readmissions after other common acute medical hospitalizations. DESIGN: Observational Cohort Study SETTING: National Readmission Database (2013-2014), including all-payer hospitalizations from 22 states. PATIENTS: 4528 pediatric severe hospitalizations, matched by age, gender, comorbidities, and length of stay to 4528 pediatric hospitalizations for other common acute medical conditions. INTERVENTIONS: None MEASUREMENTS AND MAIN RESULTS: We compared rates of 30-day all-cause, diagnosis-specific, and potentially preventable hospital readmissions using McNemar’s chi-square tests for paired data. Among 5841 eligible pediatric severe sepsis hospitalizations with live discharge, 4528 (77.5%) were matched 1:1 to 4528 pediatric hospitalizations for other acute medical conditions. Of 4528 matched sepsis hospitalizations, 851 (18.8% (95% CI 16.0, 18.2)) were re-hospitalized within 30 days, compared to 775 (17.1% (95% CI 17.1, 20.0)) of matched hospitalizations for other causes (p=0.02). The most common readmission diagnoses were chemotherapy, device complication, and sepsis, all of which were several-fold higher after sepsis versus after matched non-sepsis hospitalization. Only 11.5% of readmissions were for ambulatory care sensitive conditions compared to 23% of rehospitalizations after common acute medical conditions. CONCLUSION: More than 1 in 6 children surviving severe sepsis were re-hospitalized within 30 days, most commonly for maintenance chemotherapy, medical device complications, or recurrent sepsis. Only a small proportion of readmissions were for ambulatory care sensitive conditions.

Sepsis is a leading cause of death and disability whose heterogeneity is often cited as a key impediment to translational progress.To test the hypothesis that there are consequential and significant differences in sepsis outcomes that result from differences in a patient's clinical course leading up to sepsis hospitalization.We conducted an observational cohort study of U.S. Health and Retirement Study (HRS) participants in Medicare (1998-2012) and U.S. Department of Veterans Affairs beneficiaries (2009). Using latent profile analysis, we identified patient subtypes based on trajectory of presepsis healthcare facility use. Subtypes were identified in the derivation cohort (1,512 sepsis hospitalizations among earlier HRS participants), then validated them in two additional cohorts (1,992 sepsis hospitalizations among later HRS participants; 32,525 sepsis hospitalizations among U.S. Department of Veterans Affairs beneficiaries). We measured the association between presepsis path and 90-day mortality using chi-square tests and multivariable logistic regression.We identified three subtypes: low use of inpatient healthcare facilities, comprising 84% of the derivation cohort; rising use, 12%; and high use, 4%. The shape and distribution of presepsis trajectories were similar in all three cohorts. In the derivation cohort, 90-day mortality differed by presepsis trajectory as follows: 38% (low use), 63% (rising use), and 48% (high use) (P 0.001). This association persisted in the validation cohorts (P 0.001 for each). The rising use class remained an independent predictor of mortality after adjustment for potential confounders, including detailed physiologic data.In national cohorts of patients with sepsis, we have shown that several distinct paths into sepsis exist. These paths, identified by trajectories of presepsis healthcare use, are predictive of 90-day mortality.

Rationale: In 2013, the New York State Department of Health (NYSDOH) began a mandatory state-wide initiative to improve early recognition and treatment of severe sepsis and septic shock. Objectives: This study examines protocol initiation, 3-hour and 6-hour sepsis bundle completion, and risk-adjusted hospital mortality among adult patients with severe sepsis and septic shock. Methods: Cohort analysis included all patients from all 185 hospitals in New York State reported to the NYSDOH from April 1, 2014, to June 30, 2016. A total of 113,380 cases were submitted to NYSDOH, of which 91,357 hospitalizations from 183 hospitals met study inclusion criteria. NYSDOH required all hospitals to submit and follow evidence-informed protocols (including elements of 3-h and 6-h sepsis bundles: lactate measurement, early blood cultures and antibiotic administration, fluids, and vasopressors) for early identification and treatment of severe sepsis or septic shock. Measurements and Main Results: Compliance with elements of the sepsis bundles and risk-adjusted mortality were studied. Of 91,357 patients, 74,293 (81.3%) had the sepsis protocol initiated. Among these individuals, 3-hour bundle compliance increased from 53.4% to 64.7% during the study period (P

BackgroundAs SARS-CoV-2 continues to spread, and hospitals are treating a large number of patients with COVID-19, easy-to-use risk models that predict hospital mortality can assist in clinical decision making and triage.ObjectiveAs SARS-CoV-2 continues to spread, easy-to-use risk models that predict hospital mortality can assist in clinical decision making and triage. We aimed to develop a risk score model for in-hospital mortality in patients hospitalized with COVID-19 that was robust across hospitals and used clinical factors that are readily available and measured standardly across hospitals.MethodsIn this observational study we developed a risk score model using data collected by trained abstractors for patients in 20 diverse hospitals across the state of Michigan (Mi-COVID19) who were discharged between March 5, 2020 and August 14, 2020. Patients who tested positive for SARS-CoV-2 during hospitalization or were discharged with an ICD-10 code for COVID-19 (U07.1) were included. We employed an iterative forward selection approach to consider the inclusion of 145 potential risk factors available at hospital presentation. Model performance was externally validated with patients from 19 hospitals in the Mi-COVID19 registry not used in model development. We shared the model in an easy-to-use online application that allows the user to predict in-hospital mortality risk for a patient if they have any subset of the variables in the final model.ResultsOur final model includes the patient’s age, first recorded respiratory rate, first recorded pulse oximetry, highest creatinine level on day of presentation, and hospital’s COVID-19 mortality rate. No other factors showed sufficient incremental model improvement to warrant inclusion. The AUC for the derivation and validation sets were .796 and .829 respectively.ConclusionsRisk of in-hospital mortality in COVID-19 patients can be reliably estimated using a few factors, which are standardly measured and available to physicians very early in a hospital encounter.

PurposeTo quantify the frequency and co-occurrence of new diagnoses consistent with post-sepsis morbidity, mortality, new nursing care dependency, and total healthcare costs after sepsis.MethodsPopulation-based cohort study using healthcare claims data from 23 million beneficiaries of a German health insurance provider. We included adult patients with incident hospital-treated sepsis identified by ICD-10 codes in 2013-2014. New medical, psychological and cognitive diagnoses associated with post-sepsis morbidity; mortality; dependency on nursing care; and total health care costs in survivors were assessed to 3 years after hospital discharge.ResultsAmong 116,507 sepsis patients who survived hospitalization for sepsis, 74.3% had a new medical, psychological or cognitive diagnosis in the first year after discharge. 20.6% and 3.8% had new diagnoses in two and three domains, respectively. 31.5% were newly dependent on nursing care, and 30.7% died within the first year. In the second and third year, 65.8% and 59.4% of survivors had new diagnoses, respectively. Healthcare costs totaled an average 36,585 Euro/patient in three years, including index hospitalization costs. Occurrence of new diagnoses in predefined subgroups was: 73.7% (survivors of non-severe sepsis), 75.6% (severe sepsis), 78.3% (ICU-treated sepsis), 72.8% (non-ICU treated sepsis) and 68.5% (survivors without prior diagnoses).ConclusionsNew medical, psychological and cognitive diagnoses consistent with post-sepsis morbidity are common after sepsis, including among patients with less severe sepsis, no prior diagnoses, and younger age. This calls for more efforts to elucidate the underlying mechanisms, define optimal screening for common new diagnoses, and test interventions to prevent and treat post-sepsis morbidity.Trial RegistrationDRKS00016340Take home messageThis large population-based cohort of over 100,000 survivors of hospital-treated sepsis found high rates and a broad spectrum of new diagnoses consistent with post-sepsis morbidity, frequent new nursing care dependency, and high long-term mortality 1-3 years post sepsis. Post-sepsis morbidity was not limited to the oldest survivors or those with the most severe illness, but also affected younger survivors and those without pre-existing diagnoses.

Objectives To identify research priorities in the management, pathophysiology, and host response of coronavirus disease 2019 in critically ill patients. Design The Surviving Sepsis Research Committee, a multiprofessional group of 17 international experts representing the European Society of Intensive Care Medicine and Society of Critical Care Medicine, was virtually convened during the coronavirus disease 2019 pandemic. The committee iteratively developed the recommendations and subsequent document. Methods Each committee member submitted a list of what they believed were the most important priorities for coronavirus disease 2019 research. The entire committee voted on 58 submitted questions to determine top priorities for coronavirus disease 2019 research. Results The Surviving Sepsis Research Committee provides 13 priorities for coronavirus disease 2019. Of these, the top six priorities were identified and include the following questions: 1) Should the approach to ventilator management differ from the standard approach in patients with acute hypoxic respiratory failure?, 2) Can the host response be modulated for therapeutic benefit?, 3) What specific cells are directly targeted by severe acute respiratory syndrome coronavirus 2, and how do these cells respond?, 4) Can early data be used to predict outcomes of coronavirus disease 2019 and, by extension, to guide therapies?, 5) What is the role of prone positioning and noninvasive ventilation in nonventilated patients with coronavirus disease?, and 6) Which interventions are best to use for viral load modulation and when should they be given? Conclusions Although knowledge of both biology and treatment has increased exponentially in the first year of the coronavirus disease 2019 pandemic, significant knowledge gaps remain. The research priorities identified represent a roadmap for investigation in coronavirus disease 2019.

Rationale: In 2017, the U.S. Centers for Disease Control and Prevention (CDC) developed a new surveillance definition of sepsis, the adult sepsis event (ASE), to better track sepsis epidemiology. The ASE requires evidence of acute organ dysfunction and defines baseline organ function pragmatically as the best in-hospital value. This approach may undercount sepsis if new organ dysfunction does not resolve by discharge. Objectives: To understand how sepsis identification and outcomes differ when using the best laboratory values during hospitalization versus methods that use historical lookbacks to define baseline organ function. Methods: We identified all patients hospitalized at 138 Veterans Affairs hospitals (2013–2018) admitted via the emergency department with two or more systemic inflammatory response criteria, were treated with antibiotics within 48 hours (i.e., had potential infection), and completed 4+ days of antibiotics (i.e., had suspected infection). We considered the following three approaches to defining baseline renal, hematologic, and liver function: the best values during hospitalization (as in the Centers for Disease Control and Prevention’s ASE), the best values during hospitalization plus the prior 90 days (3-mo baseline), and the best values during hospitalization plus the prior 180 days (6-mo baseline). We determined how many patients met the criteria for sepsis by each approach, and then compared characteristics and outcomes of sepsis hospitalizations between the three approaches. Results: Among 608,128 hospitalizations with potential infection, 72.1%, 68.5%, and 58.4% had creatinine, platelet, and total bilirubin measured, respectively, in the prior 3 months. A total of 86.0%, 82.6%, and 74.8%, respectively, had these labs in the prior 6 months. Using the hospital baseline, 100,568 hospitalizations met criteria for community-acquired sepsis. By contrast, 111,983 and 117,435 met criteria for sepsis using the 3- and 6-month baselines, for a relative increase of 11% and 17%, respectively. Patient characteristics were similar across the three approaches. In-hospital mortality was 7.2%, 7.0%, and 6.8% for sepsis hospitalizations identified using the hospital, 3-month baseline, and 6-month baseline. The 30-day mortality was 12.5%, 12.7%, and 12.5%, respectively. Conclusions: Among veterans hospitalized with potential infection, the majority had laboratory values in the prior 6 months. Using 3- and 6-month lookbacks to define baseline organ function resulted in an 11% and 17% relative increase, respectively, in the number of sepsis hospitalizations identified.

This study describes reasons for readmission, use of ICU interventions during readmission, and proportions of death after initial hospital discharge of COVID-19 patients from US Veterans Affairs (VA) hospitals in March-June 2020.

BACKGROUND: The coronavirus disease 2019 pandemic continues to affect millions worldwide. Given the rapidly growing evidence base, we implemented a living guideline model to provide guidance on the management of patients with severe or critical coronavirus disease 2019 in the ICU. METHODS: The Surviving Sepsis Campaign Coronavirus Disease 2019 panel has expanded to include 43 experts from 14 countries; all panel members completed an electronic conflict-of-interest disclosure form. In this update, the panel addressed nine questions relevant to managing severe or critical coronavirus disease 2019 in the ICU. We used the World Health Organization's definition of severe and critical coronavirus disease 2019. The systematic reviews team searched the literature for relevant evidence, aiming to identify systematic reviews and clinical trials. When appropriate, we performed a random-effects meta-analysis to summarize treatment effects. We assessed the quality of the evidence using the Grading of Recommendations, Assessment, Development, and Evaluation approach, then used the evidence-to-decision framework to generate recommendations based on the balance between benefit and harm, resource and cost implications, equity, and feasibility. RESULTS: The Surviving Sepsis Campaign Coronavirus Diease 2019 panel issued nine statements (three new and six updated) related to ICU patients with severe or critical coronavirus disease 2019. For severe or critical coronavirus disease 2019, the panel strongly recommends using systemic corticosteroids and venous thromboprophylaxis but strongly recommends against using hydroxychloroquine. In addition, the panel suggests using dexamethasone (compared with other corticosteroids) and suggests against using convalescent plasma and therapeutic anticoagulation outside clinical trials. The Surviving Sepsis Campaign Coronavirus Diease 2019 panel suggests using remdesivir in nonventilated patients with severe coronavirus disease 2019 and suggests against starting remdesivir in patients with critical coronavirus disease 2019 outside clinical trials. Because of insufficient evidence, the panel did not issue a recommendation on the use of awake prone positioning. CONCLUSION: The Surviving Sepsis Campaign Coronavirus Diease 2019 panel issued several recommendations to guide healthcare professionals caring for adults with critical or severe coronavirus disease 2019 in the ICU. Based on a living guideline model the recommendations will be updated as new evidence becomes available.

OBJECTIVE: To evaluate the physical and psychosocial domains of health-related quality of life (HRQL) among children during the first year following community-acquired septic shock, and explore factors associated with poor physical and psychosocial HRQL outcomes. DESIGN: Secondary analysis of the Life after Pediatric Sepsis Evaluation (LAPSE). SETTING: Twelve academic PICUs in the United States. PATIENTS: Children ≥1 month and

This cohort study examined the number and type of outpatient health visits before and after hospitalization for pediatric severe sepsis.

Background Antibacterials may be initiated out of concern for bacterial coinfection in coronavirus disease 2019 (COVID-19). We determined prevalence and predictors of empiric antibacterial therapy and community-onset bacterial coinfections in hospitalized patients with COVID-19. Methods A randomly sampled cohort of 1705 patients hospitalized with COVID-19 in 38 Michigan hospitals between 3/13/2020 and 6/18/2020. Data were collected on early (within 2 days of hospitalization) empiric antibacterial therapy and community-onset bacterial coinfections (positive microbiologic test ≤3 days). Poisson generalized estimating equation models were used to assess predictors. Results Of 1705 patients with COVID-19, 56.6% were prescribed early empiric antibacterial therapy; 3.5% (59/1705) had a confirmed community-onset bacterial infection. Across hospitals, early empiric antibacterial use varied from 27% to 84%. Patients were more likely to receive early empiric antibacterial therapy if they were older (adjusted rate ratio [ARR]: 1.04 [1.00–1.08] per 10 years); had a lower body mass index (ARR: 0.99 [0.99–1.00] per kg/m2), more severe illness (eg, severe sepsis; ARR: 1.16 [1.07–1.27]), a lobar infiltrate (ARR: 1.21 [1.04–1.42]); or were admitted to a for-profit hospital (ARR: 1.30 [1.15–1.47]). Over time, COVID-19 test turnaround time (returned ≤1 day in March [54.2%, 461/850] vs April [85.2%, 628/737], P < .001) and empiric antibacterial use (ARR: 0.71 [0.63–0.81] April vs March) decreased. Conclusions The prevalence of confirmed community-onset bacterial coinfections was low. Despite this, half of patients received early empiric antibacterial therapy. Antibacterial use varied widely by hospital. Reducing COVID-19 test turnaround time and supporting stewardship could improve antibacterial use.