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Little is known regarding SARS-CoV-2 infection risk following SARS-CoV-2 exposures in hospitalized patients. Amongst 11,997 patients in 14 hospitals exposed 2020-2023, 6.5% tested positive (median 3d after exposure). Positivity rates were 6.7% vs 5.8% for Omicron vs pre-Omicron exposures ( P = 0.07) and 7.6% vs 4.6% for exposures before vs after admission ( P < 0.001).

Objective: To assess trends in antibiotic prescribing for patients hospitalized with COVID-19 with and without sepsis., Design: Retrospective cohort study using electronic health record (EHR) data., Setting: Five hospitals in eastern Massachusetts., Patients: Adults (≥18 years) hospitalized with community-onset SARS-CoV-2 infections between March 2020 and November 2022., Methods: We assessed quarterly trends in the use of prolonged initial antibiotic therapy (≥4 antibiotic days within one week of admission, including discharge antibiotics) amongst COVID-19 patients with and without sepsis, defined using clinical signs of organ dysfunction before hospital day 3. Poisson regression models were used to adjust for baseline characteristics and severity of illness., Results: Of 431,017 hospitalizations in the study period, 21,563 (5.0%) had community-onset COVID-19. 4,769/21,563 (20.5%) presented with sepsis. Prolonged antibiotics were prescribed in 2,323/4,769 (48.7%) COVID-19 patients with sepsis and 2,866/16,794 (17.1%) without sepsis despite low rates of positive bacterial cultures on admission (15.0% vs 6.3%, respectively). Quarterly rates of prolonged antibiotics declined between the first and second pandemic quarters for both sepsis (66.8% to 43.9%) and no-sepsis (31.8% to 24.4%) groups. However, there was no significant change thereafter through November 2022 in either group (quarterly aORs 1.02, 95% CI 0.99-1.05 and 1.01, 95% CI 0.99-1.03, respectively)., Conclusions: Prolonged antibiotics were common in hospitalized COVID-19 patients with and without sepsis during the first 33 months of the pandemic despite low rates of proven bacterial infection. Decreases in antibiotic utilization occurred primarily between the first and second pandemic quarter with no further reduction thereafter., Competing Interests: Dr Klompas reports personal fees from UpToDate outside the submitted work. Dr Rhee reports personal fees from UpToDate and Cytovale outside the submitted work. No other potential conflicts of interest relevant to the submitted work were reported., (© The Author(s) 2024.)

Objectives: To characterize associations between race/ethnicity/sex, time-to-antibiotics, and mortality in patients with suspected sepsis or septic shock., Design: Retrospective cohort study, with race/ethnicity/sex as the exposure, and time-to-antibiotics (relative to emergency department arrival) and in-hospital mortality as the outcome., Setting: Five Massachusetts hospitals., Patients: Forty-nine thousand six hundred nine adults admitted 2015-2022 with suspected sepsis or septic shock (blood cultures drawn and IV antibiotics administered within 24 hr of arrival, plus evidence of organ dysfunction for sepsis, and hypotension or lactate ≥ 4.0 mmol/L for septic shock)., Interventions: None., Measurements and Main Results: Among included patients, 22,598 (46%) were women, 36,626 (75%) were White, and 4,483 (9.2%) were Black. Women had longer median time-to-antibiotics than men when presenting with either suspected sepsis (203 vs. 190 min) or septic shock (160 vs. 142 min). Differences in time-to-antibiotics for women vs. men persisted after adjusting for age, race, comorbidities, source of infection, and severity of illness (adjusted odds ratio [aOR] for 3-6 vs. < 3 hr; 1.16 [95% CI, 1.07-1.25] for sepsis and aOR, 1.09 [95% CI, 1.01-1.18] for septic shock). Median time-to-antibiotics was also longer for Black vs. White patients for both sepsis (215 vs. 194 min; aOR for 3-6 vs. < 3 hr; 1.24 [95% CI, 1.06-1.45]) and septic shock (median 159 vs. 148 min; aOR, 1.32 [95% CI, 1.12-1.55]). There was no association between race/ethnicity/sex and in-hospital mortality for sepsis without shock; however, women with septic shock had higher mortality (aOR, 1.16; 95% CI, 1.04-1.29) vs. men. Higher mortality for women with septic shock persisted when also adjusting for time-to-antibiotics (aOR, 1.16; 95% CI, 1.03-1.32)., Conclusions: In a large cohort of patients with sepsis, time-to-antibiotics was longer for both women and Black patients even after detailed risk-adjustment. Women with septic shock had higher adjusted in-hospital mortality than men, but this association was not moderated by time-to-antibiotics., Competing Interests: Dr. Pak’s institution received funding from the National Institute of Allergy and Infectious Diseases (T32AI007061); he received funding from IDWeek. Dr. Rhee reports royalties from UpToDate for chapters related to procalcitonin use. Dr. Klompas reports royalties from UpToDate for chapters related to hospital-acquired pneumonia. Drs. Rhee and Klompas report grant funding from the Centers for Disease Control and Prevention (CDC) to conduct research related to sepsis and grant funding from the Agency for Healthcare Research and Quality (AHRQ) (R01HS027170) to conduct research related to sepsis. Dr. Pak’s and Ms. McKenna’s institution received funding from the AHRQ. Drs. Pak and Rhee received support for article research from the National Institutes of Health. Ms. McKenna and Dr. Klompas received support for article research from the CDC and the AHRQ. Dr. Sánchez has disclosed that she does not have any potential conflicts of interest., (Copyright © 2024 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Objectives: To assess the impact of different methods of calculating Sequential Organ Failure Assessment (SOFA) scores using electronic health record data on the incidence, outcomes, agreement, and predictive validity of Sepsis-3 criteria., Design: Retrospective observational study., Setting: Five Massachusetts hospitals., Patients: Hospitalized adults, 2015 to 2022., Interventions: None., Measurements and Main Results: We defined sepsis as a suspected infection (culture obtained and antibiotic administered) with a concurrent increase in SOFA score by greater than or equal to 2 points (Sepsis-3 criteria). Our reference SOFA implementation strategy imputed normal values for missing data, used Pa o2 /F io2 ratios for respiratory scores, and assumed normal baseline SOFA scores for community-onset sepsis. We then implemented SOFA scores using different missing data imputation strategies (averaging worst values from preceding and following days vs. carrying forward nonmissing values), imputing respiratory scores using Sp o2 /F io2 ratios, and incorporating comorbidities and prehospital laboratory data into baseline SOFA scores. Among 1,064,459 hospitalizations, 297,512 (27.9%) had suspected infection and 141,052 (13.3%) had sepsis with an in-hospital mortality rate of 10.3% using the reference SOFA method. The percentage of patients missing SOFA components for at least 1 day in the infection window was highest for Pa o2 /F io2 ratios (98.6%), followed by Sp o2 /F io2 ratios (73.5%), bilirubin (68.5%), and Glasgow Coma Scale scores (57.2%). Different missing data imputation strategies yielded near-perfect agreement in identifying sepsis (kappa 0.99). However, using Sp o2 /F io2 imputations yielded higher sepsis incidence (18.3%), lower mortality (8.1%), and slightly lower predictive validity for mortality (area under the receiver operating curves [AUROC] 0.76 vs. 0.78). For community-onset sepsis, incorporating comorbidities and historical laboratory data into baseline SOFA score estimates yielded lower sepsis incidence (6.9% vs. 11.6%), higher mortality (13.4% vs. 9.6%), and higher predictive validity (AUROC 0.79 vs. 0.75) relative to the reference SOFA implementation., Conclusions: Common variations in calculating respiratory and baseline SOFA scores, but not in handling missing data, lead to substantial differences in observed incidence, mortality, agreement, and predictive validity of Sepsis-3 criteria., (Copyright © 2024 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Background: Crude and adjusted mortality rates for patients with non-ventilator hospital-acquired pneumonia (NV-HAP) are amongst the highest of all healthcare-associated infections, leading to calls for greater prevention. Patients prone to NV-HAP, however, tend to be severely ill at baseline making it unclear whether their high mortality rates are due to NV-HAP, underlying conditions, or both., Methods: Two infectious disease physicians conducted detailed medical record reviews on 150 randomly selected adults from 4 hospitals who died in-hospital following an NV-HAP event between April 2016 and May 2021. Reviewers abstracted risk factors, estimated the preventability of NV-HAP, identified causes of death, and adjudicated the preventability of death., Results: Patients' median age was 69.3 (IQR 60.7-77.4) and 43.3% were female. Comorbidities were common: 57% had cancer, 30% chronic kidney disease, 29% chronic lung disease, and 27% heart failure. At least one hospice-eligible condition was present before NV-HAP in 54% and "Do Not Resuscitate" orders in 24%. Most (99%) had difficult-to-modify NV-HAP risk factors: 76% altered mental status, 35% dysphagia, and 27% nasogastric/orogastric tubes. NV-HAP was deemed possibly or probably preventable in 21% and hospital death likely or very likely preventable in 8.6%., Conclusions: Most patients who die following NV-HAP have multiple, severe underlying comorbidities and difficult-to-modify risk factors for NV-HAP. Only 1 in 5 NV-HAPs that culminated in death and 1 in 12 deaths following NV-HAP were judged potentially preventable. This does not diminish the importance of NV-HAP prevention programs but informs expectations about the potential magnitude of their impact on hospital deaths., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Competing Interests: Disclosures: All relevant financial relationships have been mitigated. Disclosure forms are available with this article online.

Background: Many hospitals have scaled back measures to prevent nosocomial SARS-CoV-2 infection given large decreases in the morbidity and mortality of SARS-CoV-2 infections for most people. Little is known, however, about the morbidity and mortality of nosocomial SARS-CoV-2 infections for hospitalized patients in the Omicron era., Objective: To estimate the effect of nosocomial SARS-CoV-2 infection on hospitalized patients' outcomes during the pre-Omicron and Omicron periods., Design: Retrospective matched cohort study., Setting: 5 acute care hospitals in Massachusetts, December 2020 to April 2023., Patients: Adults testing positive for SARS-CoV-2 on or after hospital day 5, after negative SARS-CoV-2 test results on admission and on hospital day 3, were matched to control participants by hospital, service, time period, days since admission, and propensity scores that incorporated demographics, comorbid conditions, vaccination status, primary diagnosis category, vital signs, and laboratory test values., Measurements: Primary outcomes were hospital mortality and time to discharge. Secondary outcomes were intensive care unit (ICU) admission, need for advanced oxygen support, discharge destination, hospital-free days, and 30-day readmissions., Results: There were 274 cases of hospital-onset SARS-CoV-2 infection during the pre-Omicron period and 1037 cases during the Omicron period (0.17 vs. 0.49 cases per 100 admissions). Patients with hospital-onset SARS-CoV-2 infection were older and had more comorbid conditions than those without. During the pre-Omicron period, hospital-onset SARS-CoV-2 infection was associated with increased risk for ICU admission, increased need for high-flow oxygen, longer time to discharge (median difference, 4.7 days [95% CI, 2.9 to 6.6 days]), and higher mortality (risk ratio, 2.0 [CI, 1.1 to 3.8]) versus matched control participants. During the Omicron period, hospital-onset SARS-CoV-2 infection remained associated with increased risk for ICU admission and increased time to discharge (median difference, 4.2 days [CI, 3.6 to 5.0 days]). The association with increased hospital mortality was attenuated but still significant (risk ratio, 1.6 [CI, 1.2 to 2.3])., Limitation: Residual confounding may be present., Conclusion: Hospital-onset SARS-CoV-2 infection during the Omicron period remains associated with increased morbidity and mortality., Primary Funding Source: Harvard Medical School Department of Population Medicine., Competing Interests: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M24-0199.

Competing Interests: Drs. Klompas’s and Rhee’s institution received funding from the Centers for Disease Control and Prevention and the Agency for Healthcare Research and Quality; they received funding from UpToDate. Dr. Klompas’ institution received funding from the Massachusetts Department of Public Health. Dr. Polito has disclosed that she does not have any potential conflicts of interest.

Background: Sepsis is a life-threatening syndrome with complex pathophysiology and great clinical heterogeneity which complicates the delivery of personalized therapies. Our goals were to demonstrate that some biomarkers identified as regulatory immune checkpoints in preclinical studies could 1)improve sepsis prognostication based on clinical variables and 2)guide the stratification of septic patients in subgroups with shared characteristics of immune response or survival outcomes., Methods: We assayed the soluble counterparts of 12 biomarkers of immune response in 113 internal medicine patients with bacterial sepsis., Results: IL-1 receptor-associated kinase M (IRAK-M) exhibited the highest hazard ratios (HRs) for increased 7-day (1.94 [1.17-3.20]) and 30-day mortality (1.61 [1.14-2.28]). HRs of IRAK-M and Galectin-1 for predicting 1-year mortality were 1.52 (1.20-1.92) and 1.64 (1.13-2.36), respectively. A prognostic model including IRAK-M, Galectin-1, and clinical variables (Charlson Comorbidty Index, multiple source of sepsis, and SOFA score) had high discrimination for death at 7 days and 30 days (area under the curve 0.90 [0.82-0.99]) and 0.86 [0.79-0.94], respectively). Patients with elevated serum levels of IRAK-M and Galectin-1 had clinical traits of immune suppression and low survival rates. None of the 12 biomarkers were independent predictors of 2-year mortality., Conclusions: Two inhibitory immune checkpoint biomarkers (IRAK-M and Galectin-1) helped identify 3 distinct sepsis phenotypes with distinct prognoses. These biomarkers shed light on the interplay between immune dysfunction and prognosis in patients with bacterial sepsis and may prove to be useful prognostic markers, therapeutic targets, and biochemical markers for targeted enrollment in targeted therapeutic trials., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2024.)

Competing Interests: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M24-0400.

Lyme disease surveillance based on provider and laboratory reports underestimates incidence. We developed an algorithm for automating surveillance using electronic health record data. We identified potential Lyme disease markers in electronic health record data (laboratory tests, diagnosis codes, prescriptions) from January 2017-December 2018 in 2 large practice groups in Massachusetts, USA. We calculated their sensitivities and positive predictive values (PPV), alone and in combination, relative to medical record review. Sensitivities ranged from 57% (95% CI 47%-69%) for immunoassays to 87% (95% CI 70%-100%) for diagnosis codes. PPVs ranged from 53% (95% CI 43%-61%) for diagnosis codes to 58% (95% CI 50%-66%) for immunoassays. The combination of a diagnosis code and antibiotics within 14 days or a positive Western blot had a sensitivity of 100% (95% CI 86%-100%) and PPV of 82% (95% CI 75%-89%). This algorithm could make Lyme disease surveillance more efficient and consistent.

Introduction: Electronic health records (EHRs) are increasingly being leveraged for public health surveillance. EHR-based small area estimates (SAEs) are often validated by comparison to survey data such as the Behavioral Risk Factor Surveillance System (BRFSS). However, survey and EHR-based SAEs are expected to differ. In this cross-sectional study, SAEs were generated using MDPHnet, a distributed EHR-based surveillance network, for all Massachusetts municipalities and zip code tabulation areas (ZCTAs), compared to BRFSS PLACES SAEs, and reasons for differences explored., Methods: This study delineated reasons a priori for how SAEs derived using EHRs may differ from surveys by comparing each strategy's case classification criteria and reviewing the literature. Hypertension, diabetes, obesity, asthma, and smoking EHR-based SAEs for 2021 in all ZCTAs and municipalities in Massachusetts were estimated with Bayesian mixed effects modeling and poststratification in the summer/fall of 2023. These SAEs were compared to BRFSS PLACES SAEs published by the U.S. Centers for Disease Control and Prevention., Results: Mean prevalence was higher in EHR data versus BRFSS in both municipalities and ZCTAs for all outcomes except asthma. ZCTA and municipal symmetric mean absolute percentages ranged from 12.0 to 38.2% and 13.1 to 39.8%, respectively. There was greater variability in EHR-based SAEs versus BRFSS PLACES in both municipalities and ZCTAs., Conclusions: EHR-based SAEs tended to be higher than BRFSS and more variable. Possible explanations include detection of undiagnosed cases and over-classification using EHR data, and under-reporting within BRFSS. Both EHR and survey-based surveillance have strengths and limitations that should inform their preferred uses in public health surveillance., (Copyright © 2024 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Among 495 patients who were immunocompromised and tested positive for SARS-CoV-2, polymerase chain reaction cycle thresholds remained <33 beyond 20 days more frequently in patients with hematologic malignancies, particularly those receiving B-cell-depleting or Bruton tyrosine kinase inhibitor therapy, as compared with those with solid organ malignancy (26% vs 5%)., Competing Interests: Potential conflicts of interest. M. K.: grants from Centers for Disease Control and Prevention, Agency for Healthcare Research and Quality, and Massachusetts Department of Public Health (MDPH) and royalties from UpToDate, none related to this study. C. R.: grants from Centers for Disease Control and Prevention and Agency for Healthcare Research and Quality unrelated to this study; royalties from UpToDate; payments from the Infectious Diseases Society of America for the role as associate editor for Clinical Infectious Diseases. M. A. B.: grants from Centers for Disease Control and Prevention. All other authors report no potential conflicts., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

The COVID-19 pandemic has had an unprecedented impact on population health and hospital operations. Over 7 million patients have been hospitalized for COVID-19 thus far in the United States alone. Mortality rates for hospitalized patients during the first wave of the pandemic were > 30%, but as we enter the fifth year of the pandemic hospitalizations have fallen and mortality rates for hospitalized patients with COVID-19 have plummeted to 5% or less. These gains reflect lessons learned about how to optimize respiratory support for different kinds of patients, targeted use of therapeutics for patients with different manifestations of COVID-19 including immunosuppressants and antivirals as appropriate, and high levels of population immunity acquired through vaccines and natural infections. At the same time, the pandemic has helped highlight some longstanding sources of harm for hospitalized patients including hospital-acquired pneumonia, ventilator-associated events (VAEs), and hospital-acquired respiratory viral infections. We are, thankfully, on the leeside of the pandemic at present; but the large increases in ventilator-associated pneumonia (VAP), VAEs, bacterial superinfections, and nosocomial respiratory viral infections associated with the pandemic beg the question of how best to prevent these complications moving forward. This paper reviews the burden of hospitalization for COVID-19, the intersection between COVID-19 and both VAP and VAEs, the frequency and impact of hospital-acquired respiratory viral infections, new recommendations on how best to prevent VAP and VAEs, and current insights into effective strategies to prevent nosocomial spread of respiratory viruses., Competing Interests: Dr Klompas discloses relationships with Centers for Disease Control and Prevention, AHRQ, and UpToDate., (Copyright © 2024 by Daedalus Enterprises.)

Introduction: Surveillance modernization efforts emphasize the potential use of electronic health record (EHR) data to inform public health surveillance and prevention. However, EHR data streams vary widely in their completeness, accuracy, and representativeness., Methods: We developed a validation process for the Multi-State EHR-Based Network for Disease Surveillance (MENDS) pilot project to identify and resolve data quality issues that could affect chronic disease prevalence estimates. We examined MENDS validation processes from December 2020 through August 2023 across 5 data-contributing organizations and outlined steps to resolve data quality issues., Results: We identified gaps in the EHR databases of data contributors and in the processes to extract, map, integrate, and analyze their EHR data. Examples of source-data problems included missing data on race and ethnicity and zip codes. Examples of data processing problems included duplicate or missing patient records, lower-than-expected volumes of data, use of multiple fields for a single data type, and implausible values., Conclusion: Validation protocols identified critical errors in both EHR source data and in the processes used to transform these data for analysis. Our experience highlights the value and importance of data validation to improve data quality and the accuracy of surveillance estimates that use EHR data. The validation process and lessons learned can be applied broadly to other EHR-based surveillance efforts.