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.

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.

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.

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.

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.

Nonimpact of Decolonization as an Adjunctive Measure to Contact Precautions for the Control of Methicillin-Resistant Staphylococcus aureus Transmission in Acute Care.

This was an observational study comparing methicillin-resistant Staphylococcus aureus (MRSA) transmission with no decolonization of medical patients to required decolonization of all MRSA carriers during two consecutive periods: baseline with no decolonization of medical patients (16 months) and universal MRSA carrier decolonization (13 months). The setting was a one-hospital, 156-bed facility with 9,200 annual admissions. Regression models were used to compare rates of MRSA acquisition. The chi-square test was used to compare event frequencies. We used rates of MRSA clinical disease as an outcome monitor of the program. Analysis was done on 15,666 patients who had admission and discharge tests; 27.9% of inpatient days were occupied by a MRSA-positive patient (colonized patient-days) who received decolonization while hospitalized during the baseline period (this 27.9% represented those who had planned surgery) compared to 76.0% during the intervention period (P < 0.0001). The rate of MRSA transmission was 97 events (1.0%) for 9,415 admissions (2.0 transmission events/1,000 patient-days) during baseline and was 87 (1.4%) for 6,251 admissions (2.7 transmission events/1,000 patient-days) during intervention (P = 0.06; rate ratio, 0.74; 95% confidence interval [CI], 0.55 to 1.00). The MRSA nosocomial clinical disease rate was 5.9 infections/10,000 patient-days in the baseline period and was 7.2 infections/10,000 patient-days for the intervention period (rate ratio, 0.82; 95% CI, 0.46 to 1.45; P = 0.49). Decolonization of MRSA patients does not add benefit when contact precautions are used for patients colonized with MRSA in acute (hospital) care.

Multicenter development and validation of a risk stratification tool for ward patients.

RATIONALE: Most ward risk scores were created using subjective opinion in individual hospitals and only use vital signs. OBJECTIVES: To develop and validate a risk score using commonly collected electronic health record data. METHODS: All patients hospitalized on the wards in five hospitals were included in this observational cohort study. Discrete-time survival analysis was used to predict the combined outcome of cardiac arrest (CA), intensive care unit (ICU) transfer, or death on the wards. Laboratory results, vital signs, and demographics were used as predictor variables. The model was developed in the first 60% of the data at each hospital and then validated in the remaining 40%. The final model was compared with the Modified Early Warning Score (MEWS) using the area under the receiver operating characteristic curve and the net reclassification index (NRI). MEASUREMENTS AND MAIN RESULTS: A total of 269,999 patient admissions were included, with 424 CAs, 13,188 ICU transfers, and 2,840 deaths occurring during the study period. The derived model was more accurate than the MEWS in the validation dataset for all outcomes (area under the receiver operating characteristic curve, 0.83 vs. 0.71 for CA; 0.75 vs. 0.68 for ICU transfer; 0.93 vs. 0.88 for death; and 0.77 vs. 0.70 for the combined outcome; P value < 0.01 for all comparisons). This accuracy improvement was seen across all hospitals. The NRI for the electronic Cardiac Arrest Risk Triage compared with the MEWS was 0.28 (0.18-0.38), with a positive NRI of 0.19 (0.09-0.29) and a negative NRI of 0.09 (0.09-0.09). CONCLUSIONS: We developed an accurate ward risk stratification tool using commonly collected electronic health record variables in a large multicenter dataset. Further study is needed to determine whether implementation in real-time would improve patient outcomes.

Predictive utility of prior positive urine cultures.

BACKGROUND: A patient's prior urine cultures are often considered when choosing empiric antibiotic therapy for a suspected urinary tract infection. We sought to evaluate how well previous urine cultures predict the identity and susceptibility of organisms in a patient's subsequent urine cultures. METHODS: We conducted a multinational, multicenter, retrospective cohort study, including 22 019 pairs of positive urine cultures from 4351 patients across 2 healthcare systems in Toronto, Ontario, and Chicago, Illinois. We examined the probability of the same organism being identified from the same patient's positive urine culture as a function of time elapsed from the previous positive urine specimen; in cases where the same organism was identified we also examined the likelihood of the organism exhibiting the same or better antimicrobial susceptibility profile. RESULTS: At 4-8 weeks between cultures, the correspondence in isolate identity was 57% (95% confidence interval [CI], 55%-59%), and at >32 weeks it was 49% (95% CI, 48%-50%), still greater than expected by chance (P < .001). The susceptibility profile was the same or better in 83% (95% CI, 81%-85%) of isolate pairs at 4-8 weeks, and 75% (95% CI, 73%-77%) at >32 weeks, still greater than expected by chance (P < .001). Despite high local rates of ciprofloxacin resistance in urine isolates across all patients (40%; 95% CI, 39.5%-40.5%), ciprofloxacin resistance was <20% among patients with a prior ciprofloxacin sensitive organism and no subsequent fluoroquinolone exposure. CONCLUSIONS: A patient's prior urine culture results are useful in predicting the identity and susceptibility of a current positive urine culture. In areas of high fluoroquinolone resistance, ciprofloxacin can be used empirically when prior urine culture results indicate a ciprofloxacin-susceptible organism and there has been no history of intervening fluoroquinolone use.

Sensitivity of surveillance testing for multidrug-resistant Gram-negative bacteria in the intensive care unit.

We tested intensive care unit patients for colonization with multidrug-resistant Gram-negative bacilli (MDR GNB) and compared the results with those of concurrent clinical cultures. The sensitivity of the surveillance test for detecting MDR GNB was 58.8% (95% confidence interval, 48.6 to 68.5%). Among 133 patients with positive surveillance tests, 61% had no prior clinical culture with MDR GNB.

A technology-based quality innovation to identify undiagnosed hypertension among active primary care patients.

PURPOSE: The goal of this study was to develop a technology-based strategy to identify patients with undiagnosed hypertension in 23 primary care practices and integrate this innovation into a continuous quality improvement initiative in a large, integrated health system. METHODS: In phase 1, we reviewed electronic health records (EHRs) using algorithms designed to identify patients at risk for undiagnosed hypertension. We then invited each at-risk patient to complete an automated office blood pressure (AOBP) protocol. In phase 2, we instituted a quality improvement process that included regular physician feedback and office-based computer alerts to evaluate at-risk patients not screened in phase 1. Study patients were observed for 24 additional months to determine rates of diagnostic resolution. RESULTS: Of the 1,432 patients targeted for inclusion in the study, 475 completed the AOBP protocol during the 6 months of phase 1. Of the 1,033 at-risk patients who remained active during phase 2, 740 (72%) were classified by the end of the follow-up period: 361 had hypertension diagnosed, 290 had either white-coat hypertension, prehypertension, or elevated blood pressure diagnosed, and 89 had normal blood pressure. By the end of the follow-up period, 293 patients (28%) had not been classified and remained at risk for undiagnosed hypertension. CONCLUSIONS: Our technology-based innovation identified a large number of patients at risk for undiagnosed hypertension and successfully classified the majority, including many with hypertension. This innovation has been implemented as an ongoing quality improvement initiative in our medical group and continues to improve the accuracy of diagnosis of hypertension among primary care patients.

Abrupt emergence of a single dominant multidrug-resistant strain of Escherichia coli.

BACKGROUND: Fluoroquinolone-resistant Escherichia coli are increasingly prevalent. Their clonal origins--potentially critical for control efforts--remain undefined. METHODS: Antimicrobial resistance profiles and fine clonal structure were determined for 236 diverse-source historical (1967-2009) E. coli isolates representing sequence type ST131 and 853 recent (2010-2011) consecutive E. coli isolates from 5 clinical laboratories in Seattle, Washington, and Minneapolis, Minnesota. Clonal structure was resolved based on fimH sequence (fimbrial adhesin gene: H subclone assignments), multilocus sequence typing, gyrA and parC sequence (fluoroquinolone resistance-determining loci), and pulsed-field gel electrophoresis. RESULTS: Of the recent fluoroquinolone-resistant clinical isolates, 52% represented a single ST131 subclonal lineage, H30, which expanded abruptly after 2000. This subclone had a unique and conserved gyrA/parC allele combination, supporting its tight clonality. Unlike other ST131 subclones, H30 was significantly associated with fluoroquinolone resistance and was the most prevalent subclone among current E. coli clinical isolates, overall (10.4%) and within every resistance category (11%-52%). CONCLUSIONS: Most current fluoroquinolone-resistant E. coli clinical isolates, and the largest share of multidrug-resistant isolates, represent a highly clonal subgroup that likely originated from a single rapidly expanded and disseminated ST131 strain. Focused attention to this strain will be required to control the fluoroquinolone and multidrug-resistant E. coli epidemic.

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.

Molecular epidemiology of Escherichia coli sequence type 131 and Its H30 and H30-Rx subclones among extended-spectrum-ß-lactamase-positive and -negative E. coli clinical isolates from the Chicago Region, 2007 to 2010.

We assessed Escherichia coli ST131 and its H30 and H30-Rx subclones for virulence genes, antimicrobial resistance, and extended-spectrum beta-lactamase (ESBL) type. Although both subclones were associated with ESBL production, H30-Rx isolates had higher resistance scores and were associated specifically with CTX-M-15. Three virulence genes (iha, sat, and iutA) were more prevalent among H30 than non-H30 ST131 isolates. Thus, the H30 and H30-Rx subclones are more antimicrobial resistant and have virulence profiles that are distinct from those of non-H30 ST131 isolates.

Utility of prior screening for methicillin-resistant Staphylococcus aureus in predicting resistance of S. aureus infections.

BACKGROUND: Screening for methicillin-resistant Staphylococcus aureus (MRSA) is intended to reduce nosocomial spread by identifying patients colonized by MRSA. Given the widespread use of this screening, we evaluated its potential clinical utility in predicting the resistance of clinical isolates of S. aureus. METHODS: We conducted a 2-year retrospective cohort study that included patients with documented clinical infection with S. aureus and prior screening for MRSA. We determined test characteristics, including sensitivity and specificity, of screening for predicting the resistance of subsequent S. aureus isolates. RESULTS: Of 510 patients included in the study, 53 (10%) had positive results from MRSA screening, and 79 (15%) of infecting isolates were resistant to methicillin. Screening for MRSA predicted methicillin resistance of the infecting isolate with 99% (95% confidence interval [CI] 98%-100%) specificity and 63% (95% CI 52%-74%) sensitivity. When screening swabs were obtained within 48 hours before isolate collection, sensitivity increased to 91% (95% CI 71%-99%) and specificity was 100% (95% CI 97%-100%), yielding a negative likelihood ratio of 0.09 (95% CI 0.01-0.3) and a negative predictive value of 98% (95% CI 95%-100%). The time between swab and isolate collection was a significant predictor of concordance of methicillin resistance in swabs and isolates (odds ratio 6.6, 95% CI 1.6-28.2). INTERPRETATION: A positive result from MRSA screening predicted methicillin resistance in a culture-positive clinical infection with S. aureus. Negative results on MRSA screening were most useful for excluding methicillin resistance of a subsequent infection with S. aureus when the screening swab was obtained within 48 hours before collection of the clinical isolate.

Fluoroquinolone-modifying enzyme: a new adaptation of a common aminoglycoside acetyltransferase.

Antimicrobial-modifying resistance enzymes have traditionally been class specific, having coevolved with the antibiotics they inactivate. Fluoroquinolones, antimicrobial agents used extensively in medicine and agriculture, are synthetic and have been considered safe from naturally occurring antimicrobial-modifying enzymes. We describe reduced susceptibility to ciprofloxacin in clinical bacterial isolates conferred by a variant of the gene encoding aminoglycoside acetyltransferase AAC(6')-Ib. This enzyme reduces the activity of ciprofloxacin by N-acetylation at the amino nitrogen on its piperazinyl substituent. Although approximately 30 variants of this gene have been reported since 1986, the two base-pair changes responsible for the ciprofloxacin modification phenotype are unique to this variant, first reported in 2003 and now widely disseminated. An intense increase in the medical use of ciprofloxacin seems to have been accompanied by a notable development: a single-function resistance enzyme has crossed class boundaries, and is now capable of enzymatically undermining two unrelated antimicrobial agents, one of them fully synthetic.

The influence of context on antimicrobial prescribing for febrile respiratory illness: a cohort study.

BACKGROUND: Little is known about the influence of contextual factors on a physician's likelihood to prescribe antimicrobials for febrile respiratory illness (FRI). Context includes epidemiologic context (for example, a pandemic period) and personal context (for example, recent exposure to other patients with FRI). OBJECTIVE: To examine the association between contextual factors and antimicrobial prescribing for FRI. DESIGN: 5.5-year retrospective cohort study. SETTING: A network of Midwestern primary care providers. PATIENTS: All patients presenting with FRI during influenza seasons between 2006 and 2011. MEASUREMENTS: Antimicrobial prescribing for FRI during pandemic and seasonal influenza periods. RESULTS: 28 301 unique patient encounters for FRI with 69 physicians in 26 practices were included. An antibiotic was prescribed in 12 795 (45.2%) cases. The range of prescribing among physicians was 17.9% to 83.7%. Antibiotics were prescribed in 47.5% of encounters during the seasonal period and 39.2% during the pandemic period (P < 0.001). After multivariable adjustment for patient and physician characteristics, antibiotic prescribing was lower in the pandemic period (odds ratio [OR], 0.72 [95% CI, 0.68 to 0.77]) than in the seasonal period. The likelihood of prescribing an antibiotic decreased as the number of FRI cases that a physician had seen in the previous week increased (OR, 0.93 [CI, 0.86 to 1.01] for 2 to 3 patients with FRI seen in the previous week; OR, 0.84 [CI, 0.77 to 0.91] for 4 to 6 patients; OR, 0.71 [CI, 0.64 to 0.78] for 7 to 11 patients; and OR, 0.57 [CI, 0.51 to 0.63] for ≥12 patients compared with the reference range of 0 to 1 patients). Pandemic season and recent personal context were also associated with antiviral prescribing. LIMITATION: Retrospective study in a single geographic area. CONCLUSION: Epidemiologic context and the number of cases of FRI that a physician had recently seen were associated with his or her likelihood to prescribe antimicrobials for FRI. Interventions that enhance a physician's contextual awareness may improve antimicrobial use. PRIMARY FUNDING SOURCE: NorthShore University HealthSystem.

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.

Comparison of Escherichia coli ST131 pulsotypes, by epidemiologic traits, 1967-2009.

Escherichia coli sequence type 131 (ST131), an emerging disseminated public health threat, causes multidrug-resistant extraintestinal infections. Among 579 diverse E. coli ST131 isolates from 1967-2009, we compared pulsotypes (>94% similar XbaI pulsed-field gel electrophoresis profiles) by collection year, geographic origin, source, and antimicrobial drug-resistance traits. Of 170 pulsotypes, 65 had >2 isolates and accounted for 85% of isolates. Although extensively dispersed geographically, pulsotypes were significantly source specific (e.g., had little commonality between humans vs. foods and food animals). The most prevalent pulsotypes were associated with recent isolation, humans, and antimicrobial drug resistance. Predominant pulsotype 968 was associated specifically with fluoroquinolone resistance but not with extended-spectrum ß-lactamase production or bla(CTX-M-15). Thus, several highly successful antimicrobial drug-resistant lineages within E. coli ST131 have recently emerged and diffused extensively among locales while maintaining a comparatively restricted host/source range. Identification of factors contributing to this behavior of ST131 could help protect public health.