A whole-slide foundation model for digital pathology from real-world data.

Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1-3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.

Capturing the emotional and social experiences of COVID-19 through journal entries: A qualitative study of COVID-19 experiences over six weeks following infection.

COVID-19's wide-ranging effects on patients' physical health are well-documented, but comparatively less research has explored the impact on patients' emotional and social experiences. We examined how patients across a multi-state health system experience the emotional and social aspects of COVID-19 during the first six weeks of recovery from infection. We leveraged the larger My COVID Diary project to capture open-ended journal data from an app-based platform available to patients who test positive for COVID-19 within the health system. Our sample was limited to participants with multiple journal entries during the first six weeks after infection, with one entry in the top 5% of all participants for word count to ensure sufficient journal content was available for analysis. We randomly selected 100 eligible participants and coded and analyzed all of their journal entries in weeks 1-6 after infection, utilizing a thematic analysis approach. Despite journal entry prompts' orientation towards physical symptoms, the majority of participants discussed emotional experiences (such as anxiety, depression, and gratitude) and social factors (such as work and family) when describing their COVID-19-related experiences. Physical, emotional, and social experiences related to COVID-19 infection and recovery were often interconnected and overlapping. These findings demonstrate that a holistic understanding of the patient experience that extends beyond physical symptoms is necessary to fully support patient care and recovery.

Integrating patient-reported physical, mental, and social impacts to classify long COVID experiences.

Long COVID was originally identified through patient-reported experiences of prolonged symptoms. Many studies have begun to describe long COVID; however, this work typically focuses on medical records, instead of patient experiences, and lacks a comprehensive view of physical, mental, and social impacts. As part of our larger My COVID Diary (MCD) study, we captured patient experiences using a prospective and longitudinal patient-reported outcomes survey (PROMIS-10) and free-text narrative submissions. From this study population, we selected individuals who were still engaged in the MCD study and reporting poor health (PROMIS-10 scores < 3) at 6 months (n = 634). We used their PROMIS-10 and narrative data to describe and classify their long COVID experiences. Using Latent Class Analysis of the PROMIS-10 data, we identified four classifications of long COVID experiences: a few lingering issues (n = 107), significant physical symptoms (n = 113), ongoing mental and cognitive struggles (n = 235), and numerous compounding challenges (n = 179); each classification included a mix of physical, mental, and social health struggles with varying levels of impairment. The classifications were reinforced and further explained by patient narratives. These results provide a new understanding of the varying ways that long COVID presents to help identify and care for patients.

Patient-Reported Outcomes for Fully Vaccinated COVID-19 Patients Over 6 Weeks: The Experiences of Clinical Breakthrough Cases.

BACKGROUND: While coronavirus disease 2019 (COVID-19) vaccines have high rates of efficacy, fully vaccinated individuals can become infected with COVID-19. Among this population, symptoms tend to be less severe and shorter lasting. Less is known about how vaccinated individuals who contract COVID-19 experience the disease through patient-reported outcomes (PROs) and how this changes over time. OBJECTIVE: The aim of this study was to describe the physical, mental, and social health PROs for fully vaccinated individuals who contracted COVID-19 over a 6-week period. DESIGN: Prospective design using the Patient-Reported Outcomes Measurement Information System short-form (PROMIS-10) collected through a mobile application-based platform. PARTICIPANT: 1114 fully vaccinated patients who tested positive for COVID-19 at a large US health system and engaged with the study on or after 1 March 2021 and reported onset of illness prior to 1 November 2021. MAIN MEASURES: Global physical and mental health PROMIS-10 T-scores for the 6-week period, component PROMIS-10 questions for the 6-week period, and component PROMIS-10 questions restricted to a subset of participants for the first month to measure individual recovery were analyzed. KEY RESULTS: Mean global physical and mental health T-scores increased over time and remained within one standard deviation of the population mean. At baseline, at least 40% of participants reported good health for all component questions except Fatigue (25%), and the proportion reporting good health increased over time for all questions, with the largest improvements in Fatigue (25.5 to 67.5%), Pain (59.1 to 82.8%), and Emotional Problems (42.3 to 62.5%). Over the first month, the greatest positive changes in individual recovery were observed for Fatigue (65.0%), Pain (53.0%), and Emotional Problems (41.1%); at least 30% of respondents reported no change in at least one category, and the greatest decreases were for Usual Social Activities (23.9%), Social Satisfaction (23.2%), and Mental Health (21.8%). CONCLUSIONS: This study provides an important step towards better understanding the impact of 'breakthrough' COVID-19 infections on clinically engaged, fully vaccinated patients' physical and mental health to improve support for their treatment and recovery.

Methicillin-resistant staphylococcus aureus nosocomial infection has a distinct epidemiological position and acts as a marker for overall hospital-acquired infection trends.

An ongoing healthcare debate is whether controlling hospital-acquired infection (HAI) from methicillin-resistant Staphylococcus aureus (MRSA) will result in lowering the global HAI rate, or if MRSA will simply be replaced by another pathogen and there will be no change in overall disease burden. With surges in drug-resistant hospital-acquired pathogens during the COVID-19 pandemic, this remains an important issue. Using a dataset of more than 1 million patients in 51 acute care facilities across the USA, and with the aid of a threshold model that models the nonlinearity in outbreaks of diseases, we show that MRSA is additive to the total burden of HAI, with a distinct 'epidemiological position', and does not simply replace other microbes causing HAI. Critically, as MRSA is reduced it is not replaced by another pathogen(s) but rather lowers the overall HAI burden. The analysis also shows that control of MRSA is a benchmark for how well all non-S. aureus nosocomial infections in the same hospital are prevented. Our results are highly relevant to healthcare epidemiologists and policy makers when assessing the impact of MRSA on hospitalized patients. These findings further stress the major importance of MRSA as a unique cause of nosocomial infections, as well as its pivotal role as a biomarker in demonstrating the measured efficacy (or lack thereof) of an organization's Infection Control program.

Odds of Hospitalization for COVID-19 After 3 vs 2 Doses of mRNA COVID-19 Vaccine by Time Since Booster Dose.

This study assesses the association between COVID-19 mRNA booster immunization compared with vaccination with the primary mRNA vaccination series alone and odds of hospitalization for COVID-19.

Decreased Risk of Coronavirus Disease 2019-Related Hospitalization Associated With the Omicron Variant of Severe Acute Respiratory Syndrome Coronavirus 2.

Among 134 223 patients with coronavirus disease 2019 (COVID-19), we assessed how risk of hospitalization changed at different intervals in the pandemic, controlling for prior COVID-19 immunity. In multivariable analysis, outpatients with COVID-19 during the Omicron-predominant time period had significantly lower odds of hospitalization compared to pre-Delta (adjusted odds ratio, 0.26 [95% confidence interval, .22-.32]).

Comparative vaccine effectiveness against severe COVID-19 over time in US hospital administrative data: a case-control study.

BACKGROUND: Research suggests the protection offered by COVID-19 vaccines might wane over time, prompting consideration of booster vaccinations. Data on which vaccines offer the most robust protection over time, and which patients are most vulnerable to attenuating protection, could help inform potential booster programmes. In this study, we used comprehensive hospitalisation data to estimate vaccine effectiveness over time. METHODS: In this case-control study, we used data from a large US health-care system to estimate vaccine effectiveness against severe SARS-CoV-2 infection and examined variation based on time since vaccination, vaccine type, and patients' demographic and clinical characteristics. We compared trends in attenuation of protection across vaccines and used a multivariable model to identify key factors associated with risk for severe breakthrough infection. Patients were considered to have severe COVID-19 if they were admitted to the hospital, had a final coded diagnosis of COVID-19 (according to International Classification of Diseases Tenth Revision code U07.1) or a positive nucleic acid amplification test for symptomatic SARS-CoV-2 during their hospitalisation, and were treated with remdesivir or dexamethasone during hospitalisation. FINDINGS: Between April 1, 2021, and Oct 26, 2021, we observed 9667 admissions for severe COVID-19 (ie, cases). Overall, 1293 (13·4%) of 9667 cases were fully vaccinated at the time of admission, compared with 22 308 (57·7%) of 38 668 controls, who were admitted to hospital for other reasons. The median time between vaccination and hospital admission among cases was 162 days (IQR 118-198). Overall vaccine effectiveness declined mostly over the course of the summer, from 94·5% (95% CI 91·4-96·5) in April, 2021 (pre-delta), to 84·0% (81·6-86·1) by October, 2021. Notably, vaccine effectiveness declined over time, from 94·0% (95% CI 92·8-95·0) at days 50-100 after vaccination to 80·4% (77·8-82·7) by days 200-250 after vaccination. After 250 days, vaccine effectiveness declines were even more notable. Among those who received the BNT162b2 (Pfizer-BioNTech) vaccine, vaccine effectiveness fell from an initial peak of 94·9% (93·2-96·2) to 74·1% (69·6-77·9) by days 200-250 after vaccination. Protection from the mRNA-1273 (Moderna) and Ad26.COV2 (Janssen) vaccines declined less over time, although the latter offered lower overall protection. Holding other factors constant, the risk of severe breakthrough infection was most strongly associated with age older than 80 years (adjusted odds ratio 1·76, 95% CI 1·43-2·15), vaccine type (Pfizer 1·39, 0·98-1·97; Janssen 14·53, 8·43-25·03; both relative to Moderna), time since vaccination (1·05, 1·03-1·07; per week after week 8 when protection peaks, technically), and comorbidities including organ transplantation (3·44, 95% CI 2·12-5·57), cancer (1·93, 1·60-2·33), and immunodeficiency (1·49, 1·13-1·96). INTERPRETATION: Vaccination remains highly effective against hospitalisation, but vaccine effectiveness declined after 200 days, particularly for older patients or those with specific comorbidities. Additional protection (eg, a booster vaccination) might be warranted for everyone, but especially for these populations. In addition to promoting general vaccine uptake, clinicians and policy makers should consider prioritising booster vaccinations in those most at risk of severe COVID-19. FUNDING: None.

Remdesivir and Mortality in Patients With Coronavirus Disease 2019.

BACKGROUND: The impact of remdesivir (RDV) on mortality rates in coronavirus disease 2019 (COVID-19) is controversial, and the mortality effect in subgroups of baseline disease severity has been incompletely explored. The purpose of this study was to assess the association of RDV with mortality rates in patients with COVID-19. METHODS: In this retrospective cohort study we compared persons receiving RDV with those receiving best supportive care (BSC). Patients hospitalized between 28 February and 28 May 2020 with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection were included with the development of COVID-19 pneumonia on chest radiography and hypoxia requiring supplemental oxygen or oxygen saturation ≤94% with room air. The primary outcome was overall survival, assessed with time-dependent Cox proportional hazards regression and multivariable adjustment, including calendar time, baseline patient characteristics, corticosteroid use, and random effects for hospital. RESULTS: A total of 1138 patients were enrolled, including 286 who received RDV and 852 treated with BSC, 400 of whom received hydroxychloroquine. Corticosteroids were used in 20.4% of the cohort (12.6% in RDV and 23% in BSC). Comparing persons receiving RDV with those receiving BSC, the hazard ratio (95% confidence interval) for death was 0.46 (.31-.69) in the univariate model (P < .001) and 0.60 (.40-.90) in the risk-adjusted model (P = .01). In the subgroup of persons with baseline use of low-flow oxygen, the hazard ratio (95% confidence interval) for death in RDV compared with BSC was 0.63 (.39-1.00; P = .049). CONCLUSION: Treatment with RDV was associated with lower mortality rates than BSC. These findings remain the same in the subgroup with baseline use of low-flow oxygen.

Excess Mortality Among Patients Hospitalized During the COVID-19 Pandemic.

BACKGROUND: The extent to which the COVID-19 pandemic has affected outcomes for patients with unplanned hospitalizations is unclear. OBJECTIVE: To examine changes in in-hospital mortality for patients without COVID-19 during the first 10 months of the pandemic (March 4, 2020 to December 31, 2020). DESIGN, SETTING, AND PARTICIPANTS: Observational study of adults with unplanned hospitalizations at 51 hospitals across 6 Western states. EXPOSURES: Unplanned hospitalizations occurring during the spring COVID-19 surge (March 4 to May 13, 2020; Period 1), an intervening period (May 14 to October 19, 2020; Period 2), and the fall COVID-19 surge (October 20 to December 31, 2020; Period 3) were compared with a pre-COVID-19 baseline period from January 1, 2019, to March 3, 2020. MAIN OUTCOMES AND MEASURES: We examined daily hospital admissions and in-hospital mortality overall and in 30 conditions. RESULTS: Unplanned hospitalizations declined steeply during Periods 1 and 3 (by 47.5% and 25% compared with baseline, respectively). Although volumes declined, adjusted in-hospital mortality rose from 2.9% in the pre-pandemic period to 3.5% in Period 1 (20.7% relative increase), returning to baseline in Period 2, and rose again to 3.4% in Period 3. Elevated mortality was seen for nearly all conditions studied during the pandemic surge periods. CONCLUSION: Pandemic COVID-19 surges were associated with higher rates of in-hospital mortality among patients without COVID-19, suggesting disruptions in care patterns for patients with many common acute and chronic illnesses.

From Testing to Decision-Making: A Data-Driven Analytics COVID-19 Response.

In March 2020, NorthShore University Health System laboratories mobilized to develop and validate polymerase chain reaction based testing for detection of SARS-CoV-2. Using laboratory data, NorthShore University Health System created the Data Coronavirus Analytics Research Team to track activities affected by SARS-CoV-2 across the organization. Operational leaders used data insights and predictions from Data Coronavirus Analytics Research Team to redeploy critical care resources across the hospital system, and real-time data were used daily to make adjustments to staffing and supply decisions. Geographical data were used to triage patients to other hospitals in our system when COVID-19 detected pavilions were at capacity. Additionally, one of the consequences of COVID-19 was the inability for patients to receive elective care leading to extended periods of pain and uncertainty about a disease or treatment. After shutting down elective surgeries beginning in March of 2020, NorthShore University Health System set a recovery goal to achieve 80% of our historical volumes by October 1, 2020. Using the Data Coronavirus Analytics Research Team, our operational and clinical teams were able to achieve 89% of our historical volumes a month ahead of schedule, allowing rapid recovery of surgical volume and financial stability. The Data Coronavirus Analytics Research Team also was used to demonstrate that the accelerated recovery period had no negative impact with regard to iatrogenic COVID-19 infection and did not result in increased deep vein thrombosis, pulmonary embolisms, or cerebrovascular accident. These achievements demonstrate how a coordinated and transparent data-driven effort that was built upon a robust laboratory testing capability was essential to the operational response and recovery from the COVID-19 crisis.

Surge effects and survival to hospital discharge in critical care patients with COVID-19 during the early pandemic: a cohort study.

BACKGROUND: The early months of the COVID-19 pandemic were fraught with much uncertainty and some resource constraint. We assessed the change in survival to hospital discharge over time for intensive care unit patients with COVID-19 during the first 3 months of the pandemic and the presence of any surge effects on patient outcomes. METHODS: Retrospective cohort study using electronic medical record data for all patients with laboratory-confirmed COVID-19 admitted to intensive care units from February 25, 2020, to May 15, 2020, at one of 26 hospitals within an integrated delivery system in the Western USA. Patient demographics, comorbidities, and severity of illness were measured along with medical therapies and hospital outcomes over time. Multivariable logistic regression models were constructed to assess temporal changes in survival to hospital discharge during the study period. RESULTS: Of 620 patients with COVID-19 admitted to the ICU [mean age 63.5 years (SD 15.7) and 69% male], 403 (65%) survived to hospital discharge and 217 (35%) died in the hospital. Survival to hospital discharge increased over time, from 60.0% in the first 2 weeks of the study period to 67.6% in the last 2 weeks. In a multivariable logistic regression analysis, the risk-adjusted odds of survival to hospital discharge increased over time (biweekly change, adjusted odds ratio [aOR] 1.22, 95% CI 1.04-1.40, P = 0.02). Additionally, an a priori-defined explanatory model showed that after adjusting for both hospital occupancy and percent hospital capacity by COVID-19-positive individuals and persons under investigation (PUI), the temporal trend in risk-adjusted patient survival to hospital discharge remained the same (biweekly change, aOR 1.18, 95% CI 1.00-1.38, P = 0.04). The presence of greater rates of COVID-19 positive/PUI as a percentage of hospital capacity was, however, significantly and inversely associated with survival to hospital discharge (aOR 0.95, 95% CI 0.92-0.98, P < 0.01). CONCLUSIONS: During the early COVID-19 pandemic, risk-adjusted survival to hospital discharge increased over time for critical care patients. An association was also seen between a greater COVID-19-positive/PUI percentage of hospital capacity and a lower survival rate to hospital discharge.

A Randomized Controlled Trial of an Electronic Clinical Decision Support Tool for Inpatient Antimicrobial Stewardship.

BACKGROUND: The weighted incidence syndromic combination antibiogram (WISCA) is an antimicrobial stewardship tool that utilizes electronic medical record data to provide real-time clinical decision support regarding empiric antibiotic prescription in the hospital setting. The aim of this study was to determine the impact of WISCA utilization for empiric antibiotic prescription on hospital length of stay (LOS). METHODS: We performed a crossover randomized controlled trial of the WISCA tool at 4 hospitals. Study participants included adult inpatients receiving empiric antibiotics for urinary tract infection (UTI), abdominal-biliary infection (ABI), pneumonia, or nonpurulent cellulitis. Antimicrobial stewardship (ASP) physicians utilized WISCA and clinical guidelines to provide empiric antibiotic recommendations. The primary outcome was LOS. Secondary outcomes included 30-day mortality, 30-day readmission, Clostridioides difficile infection, acquisition of multidrug-resistant gram-negative organism (MDRO), and antibiotics costs. RESULTS: In total, 6849 participants enrolled in the study. There were no overall differences in outcomes among the intervention versus control groups. Participants with cellulitis in the intervention group had significantly shorter mean LOS compared to participants with cellulitis in the control group (coefficient estimate = 0.53 [-0.97, -0.09], P = .0186). For patients with community acquired pneumonia (CAP), the intervention group had significantly lower odds of 30-day mortality compared to the control group (adjusted odds ratio [aOR] .58, 95% confidence interval [CI], .396, .854, P = .02). CONCLUSIONS: Use of WISCA was not associated with improved outcomes for UTI and ABI. Guidelines-based interventions were associated with decreased LOS for cellulitis and decreased mortality for CAP.

Clinical Sensitivity of Severe Acute Respiratory Syndrome Coronavirus 2 Nucleic Acid Amplification Tests for Diagnosing Coronavirus Disease 2019.

Utilizing 34 348 severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) nucleic acid amplification test (NAAT) results from 2 health systems, we estimated the clinical sensitivity of a single SARS-CoV-2 NAAT. We found that SARS-CoV-2 NAAT has 82%-97% sensitivity for diagnosing coronavirus disease 2019 among symptomatic patients.

Electronic Syndromic Surveillance for Influenza-Like Illness Across Treatment Settings.

OBJECTIVE Syndromic surveillance for influenza-like illness (ILI) is predominantly performed in the outpatient setting. The objective of this study was to compare patterns of ILI activity in outpatient, emergency department (ED), and inpatient settings using an electronic syndromic surveillance algorithm. DESIGN Retrospective cohort study over 7.5 years. SETTING A large community health system comprised of 5 hospitals and >50 clinics. METHODS We applied an electronic syndromic surveillance algorithm for ILI to all primary-care outpatient visits, inpatient encounters, and ED encounters at our health system. Comparisons of ILI activity over time were performed using Spearman's rank correlation coefficient. Cross correlation was used to compare the timing of ILI activity among treatment settings. RESULTS Overall, 4,447,769 patient encounters occurred during the study period; 152,607 of these (3.4%) were consistent with ILI. The correlation coefficient for ILI activity in the outpatient versus ED setting was 0.877, and for the outpatient versus inpatient setting, the correlation coefficient was 0.699. ILI activity among outpatients preceded ILI activity among inpatients by 1 week. ILI activity among children in the outpatient setting preceded ILI activity among adults in all 3 settings by 1 week. CONCLUSIONS Syndromic surveillance for ILI in the outpatient setting yields similar results to surveillance in the ED setting, but it produces less similar results than ILI surveillance in the inpatient setting. ILI activity in the pediatric outpatient population is a potential predictor of future ILI activity in the general population. Infect Control Hosp Epidemiol 2017;38:393-398.

Reduction of methicillin-resistant Staphylococcus aureus infection in long-term care is possible while maintaining patient socialization: A prospective randomized clinical trial.

BACKGROUND: Antibiotic resistance is a challenge in long-term care facilities (LTCFs). The objective of this study was to demonstrate that a novel, minimally invasive program not interfering with activities of daily living or socialization could lower methicillin-resistant Staphylococcus aureus (MRSA) disease. METHODS: This was a prospective, cluster-randomized, nonblinded trial initiated at 3 LTCFs. During year 1, units were stratified by type of care and randomized to intervention or control. In year 2, all units were converted to intervention consisting of universal decolonization using intranasal mupirocin and a chlorhexidine bath performed twice (2 decolonization-bathing cycles 1 month apart) at the start of the intervention period. Subsequently, after initial decolonization, all admissions were screened on site using real-time polymerase chain reaction, and those MRSA positive were decolonized, but not isolated. Units received annual instruction on hand hygiene. Enhanced bleach wipe cleaning of flat surfaces was done every 4 months. RESULTS: There were 16,773 tests performed. The MRSA infection rate decreased 65% between baseline (44 infections during 365,809 patient days) and year 2 (12 infections during 287,847 patient days; P <.001); a significant reduction was observed at each of the LTCFs (P <.03). CONCLUSIONS: On-site MRSA surveillance with targeted decolonization resulted in a significant decrease in clinical MRSA infection among LTCF residents.