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The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) present clinical criteria for the classification of patients with sepsis. We investigated incidence and long-term outcomes of patients diagnosed with these classifications, which are currently unknown. We did a retrospective analysis using data from 30 239 participants from the USA who were aged at least 45 years and enrolled in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. Patients were enrolled between Jan 25, 2003, and Oct 30, 2007, and we identified hospital admissions from Feb 5, 2003, to Dec 31, 2012, and applied three classifications: infection and systemic inflammatory response syndrome (SIRS) criteria, elevated sepsis-related organ failure assessment (SOFA) score from Sepsis-3, and elevated quick SOFA (qSOFA) score from Sepsis-3. We estimated incidence during the study period, in-hospital mortality, and 1-year mortality. Of 2593 first infection events, 1526 met SIRS criteria, 1080 met SOFA criteria, and 378 met qSOFA criteria. Incidence was 8·2 events (95% CI 7·8–8·7) per 1000 person-years for SIRS, 5·8 events (5·4–6·1) per 1000 person-years for SOFA, and 2·0 events (1·8–2·2) per 1000 person-years for qSOFA. In-hospital mortality was higher for patients with an elevated qSOFA score (67 [23%] of 295 patients died) than for those with an elevated SOFA score (125 [13%] of 960 patients died) or who met SIRS criteria (128 [9%] of 1392 patients died). Mortality at 1 year after discharge was also highest for patients with an elevated qSOFA score (29·4 deaths [95% CI 22·3–38·7] per 100 person-years) compared with those with an elevated SOFA score (22·6 deaths [19·2–26·6] per 100 person-years) or those who met SIRS criteria (14·7 deaths [12·5–17·2] per 100 person-years). SIRS, SOFA, and qSOFA classifications identified different incidences and mortality. Our findings support the use of the SOFA and qSOFA classifications to identify patients with infection who are at elevated risk of poor outcomes. These classifications could be used in future epidemiological assessments and studies of patients with infection. National Institute for Nursing Research, National Center for Research Resources, and National Institute of Neurological Disorders and Stroke.

AbstractObjectiveTo create and validate a simple and transferable machine learning model from electronic health record data to accurately predict clinical deterioration in patients with covid-19 across institutions, through use of a novel paradigm for model development and code sharing.DesignRetrospective cohort study.SettingOne US hospital during 2015-21 was used for model training and internal validation. External validation was conducted on patients admitted to hospital with covid-19 at 12 other US medical centers during 2020-21.Participants33 119 adults (≥18 years) admitted to hospital with respiratory distress or covid-19.Main outcome measuresAn ensemble of linear models was trained on the development cohort to predict a composite outcome of clinical deterioration within the first five days of hospital admission, defined as in-hospital mortality or any of three treatments indicating severe illness: mechanical ventilation, heated high flow nasal cannula, or intravenous vasopressors. The model was based on nine clinical and personal characteristic variables selected from 2686 variables available in the electronic health record. Internal and external validation performance was measured using the area under the receiver operating characteristic curve (AUROC) and the expected calibration error—the difference between predicted risk and actual risk. Potential bed day savings were estimated by calculating how many bed days hospitals could save per patient if low risk patients identified by the model were discharged early.Results9291 covid-19 related hospital admissions at 13 medical centers were used for model validation, of which 1510 (16.3%) were related to the primary outcome. When the model was applied to the internal validation cohort, it achieved an AUROC of 0.80 (95% confidence interval 0.77 to 0.84) and an expected calibration error of 0.01 (95% confidence interval 0.00 to 0.02). Performance was consistent when validated in the 12 external medical centers (AUROC range 0.77-0.84), across subgroups of sex, age, race, and ethnicity (AUROC range 0.78-0.84), and across quarters (AUROC range 0.73-0.83). Using the model to triage low risk patients could potentially save up to 7.8 bed days per patient resulting from early discharge.ConclusionA model to predict clinical deterioration was developed rapidly in response to the covid-19 pandemic at a single hospital, was applied externally without the sharing of data, and performed well across multiple medical centers, patient subgroups, and time periods, showing its potential as a tool for use in optimizing healthcare resources.

Predicting long-term outcomes in sepsis survivors remains a difficult task. Persistent inflammation post-sepsis is associated with increased risk for rehospitalization and death. As surrogate markers of inflammation, complete blood count parameters measured at hospital discharge may have prognostic value for sepsis survivors. To determine the incremental value of complete blood count parameters over clinical characteristics for predicting 90-day outcomes in sepsis survivors. Electronic health record data was used to identify sepsis hospitalizations at United States Veterans Affairs hospitals with live discharge and relevant laboratory data (2013 to 2018). We measured the association of eight complete blood count parameters with 90-day outcomes (mortality, rehospitalization, cause-specific rehospitalizations) using multivariable logistic regression models. We identified 155,988 eligible hospitalizations for sepsis. Anemia (93.6%, N=142,162) and lymphopenia (28.1%, N=29,365) were the most common blood count abnormalities at discharge. In multivariable models, all parameters were associated with the primary outcome of 90-day mortality or rehospitalization and improved model discrimination above clinical characteristics alone (likelihood ratio test, p<0.02 for all). A model including all eight parameters significantly improved discrimination (AUROC, 0.6929 v. 0.6756) and reduced calibration error for the primary outcome. Hemoglobin had the greatest prognostic separation with a 1.5 fold increased incidence of the primary outcome in the lowest quintile (7.2-8.9 g/dL) versus highest quintile (12.70-15.80 g/dL). Hemoglobin and neutrophil lymphocyte ratio provided the most added value in predicting the primary outcome and 90-day mortality alone, respectively. Absolute lymphocyte count added little value in predicting 90-day outcomes. The incorporation of discharge complete blood count parameters into prognostic scoring systems could improve prediction of 90-day outcomes. Hemoglobin had the greatest prognostic value for the primary composite outcome of 90-day rehospitalization or mortality. Absolute lymphocyte count provided little added value in multivariable model comparisons, including for infection- or sepsis-related rehospitalization.

Lumbar puncture (LP) is an important technique for assessing and treating neurological symptoms. The objective of this study was to describe the characteristics of diagnostic lumbar punctures performed on hospitalized patients in the United States. We analyzed data from the 2010 National Inpatient Sample (NIS) and the National Emergency Department Survey (NEDS). We included patients treated in the Emergency Department (ED) as well as those admitted to an inpatient bed through the ED. We identified patients undergoing LPs from ICD-9 procedural code 03.31 and CPT code 62270. We generated nationally weighted estimates of the total number of LPs. We also assessed patient and hospital characteristics of cases undergoing LP. Of an estimated 135 million hospitalizations (ED + admission, or ED only), there were an estimated 362,718 LPs (331,248-394,188), including 273,612 (251,850-295,375) among adults and 89,106 (71,870-106,342) among children (<18 years old). Of the 362,718 LPs, 136,764 (122,117-151,410) were performed in the ED without admission. The most common conditions associated with LP among children were fever of unknown origin, meningitis, seizures and other perinatal conditions. The most common conditions associated with LP among adults were headache and meningitis. Lumbar Puncture remains an important procedure for diagnostic and therapeutic uses in United States Hospitals.

Variation exists in cardiac arrest (CA) survival among institutions. We sought to determine institutional-level characteristics of academic medical centers (AMCs) associated with CA survival. We examined discharge data from AMCs participating with Vizient clinical database-resource manager. We identified cases using ICD-9 diagnosis code 427.5 (CA) or procedure code 99.60 (CPR). We estimated hospital-specific risk-standardized survival rates (RSSRs) using mixed effects logistic regression, adjusting for individual mortality risk. Institutional and community characteristics of AMCs with higher than average survival were compared with those with lower survival. We analyzed data on 3,686,296 discharges in 2012, of which 33,700 (0.91%) included a CA diagnosis. Overall survival was 42.3% (95% CI 41.8-42.9) with median institutional RSSR of 42.6% (IQR 35.7-51.0; Min-Max 19.4-101.6). We identified 28 AMCs with above average survival (median RSSR 61.8%) and 20 AMCs with below average survival (median RSSR 26.8%). Compared to AMCs with below average survival, those with high CA survival had higher CA volume (median 262 vs.119 discharges, p = 0.002), total beds (722 vs. 452, p = 0.02), and annual surgical volume (24,939 vs. 13,109, p<0.001), more likely to offer cardiac catheterization (100% vs. 72%, p = 0.007) or cardiac surgery (93% vs. 61%, p = 0.02) and cared for catchment areas with higher household income ($61,922 vs. $49,104, p = 0.004) and lower poverty rates (14.6% vs. 17.3%, p = 0.03). Using discharge data from Vizient, we showed AMCs with higher CA and surgical case volume, cardiac catheterization and cardiac surgery facilities, and catchment areas with higher socioeconomic status had higher risk-standardized CA survival.

Mobility and function are important predictors of survival. However, their combined impact on mortality in adults ≥65 years with heart failure (HF) is not well understood. This study examined the role of gait speed and instrumental activities of daily living (IADL) in all-cause mortality in a cohort of 1,119 community-dwelling Cardiovascular Health Study participants ≥65 years with incident HF. Data on HF and mortality were collected through annual examinations or contact during the 10-year follow-up period. Slower gait speed (<0.8 m/s vs ≥0.8 m/s) and IADL impairment (≥1 vs 0 areas of dependence) were determined from baseline and follow-up assessments. A total of 740 (66%) of the 1,119 participants died during the follow-up period. Multivariate Cox proportional hazards models showed that impairments in either gait speed (hazard ratio 1.37, 95% confidence interval 1.10 to 1.70; p = 0.004) or IADL (hazard ratio 1.56, 95% confidence interval 1.29-1.89; p <0.001), measured within 1 year before the diagnosis of incident HF, were independently associated with mortality, adjusting for sociodemographic and clinical characteristics. The combined presence of slower gait speed and IADL impairment was associated with a greater risk of mortality and suggested an additive relation between gait speed and IADL. In conclusion, gait speed and IADL are important risk factors for mortality in adults ≥65 years with HF, but the combined impairments of both gait speed and IADL can have an especially important impact on mortality.

Sepsis is the syndrome of life-threatening organ dysfunction resulting from dysregulated host response to infection. Aspirin, an anti-inflammatory agent, may play a role in attenuating the inflammatory response during infection. We evaluated the association between aspirin use and long-term rates of sepsis as well as sepsis outcomes. We analyzed data from 30,239 adults ≥45 years old in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. The primary exposure was aspirin use, identified via patient interview. The primary outcome was sepsis hospitalization, defined as admission for infection with two or more systemic inflammatory response syndrome criteria. We fit Cox proportional hazards models assessing the association between aspirin use and rates of sepsis, adjusted for participant demographics, health behaviors, chronic medical conditions, medication adherence, and biomarkers. We used a propensity-matched analysis and a series of sensitivity analyses to assess the robustness of our results. We also examined risk of organ dysfunction and hospital mortality during hospitalization for sepsis. Among 29,690 REGARDS participants with follow-up data available, 43% reported aspirin use (n = 12,869). Aspirin users had higher sepsis rates (hazard ratio 1.35; 95% CI: 1.22-1.49) but this association was attenuated following adjustment for potential confounders (adjusted HR 0.99; 95% CI: 0.88-1.12). We obtained similar results in propensity-matched and sensitivity analyses. Among sepsis hospitalizations, aspirin use was not associated with organ dysfunction or hospital death. In the REGARDS cohort, baseline aspirin use was not associated with long-term rates of sepsis.

Background Prior studies associate steroid use with infection risk but were limited to select populations and short follow-up periods. The association of steroid use with long-term risk of community-acquired infections is unknown. We sought to determine the association of steroid risk with long-term risks of community- acquired infections and sepsis. Methods We used data on 30,239 adults aged ≥ 45 years old from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. The primary exposure was oral or injectable steroid use, determined from medication inventory obtained at baseline in-home visit. The primary outcome was time to first infection event during 2003–2012, determined through adjudicated review of hospital records. We determined associations between baseline steroid use and first infection hospitalization events using Cox proportional hazards models, adjusting for demographics, health behaviors, chronic medical conditions, and medication adherence. Among the first infection hospitalization events, we also determined the association between baseline steroid use and sepsis. Results Steroid use was reported in 2.24% (n = 677) of the study population. There were 2593 incident infection events during the 10-year follow-up period. Infection incidence rates were higher for steroid than non-steroid users (37.99 vs. 13.79 per 1000 person-years). Steroid use was independently associated with increased risk of infection (adjusted HR 2.10, 95% CI: 1.73–2.56). Among first-infection events, steroid use was associated with increased odds of sepsis (adjusted OR 2.11, 95% CI: 1.33–3.36). The associations persisted in propensity matched analyses as well as models stratified by propensity score and medication adherence. Conclusions In this population-based cohort study, baseline steroid use was associated with increased long-term risks of community-acquired infections and sepsis.

We evaluated agreement among trained emergency physicians assessing the degree of B-line presence on bedside ultrasound in patients presenting to the emergency department (ED) with acute undifferentiated dyspnea. We also determined which thoracic zones offered the highest level of interobserver reliability for sonographic B-line assessment. We evaluated a prospective convenience sample of adult patients presenting with dyspnea to an academic ED. Two consecutive bedside lung ultrasounds were performed on 91 patients by a pair of physician-sonographers. The lung ultrasounds were structured 10-zone thoracic sonograms, documented as videos. Sonographer pairs were expert/expert (>100 lung ultrasounds performed) or expert/novice pairs (novices performed 5 supervised examinations after structured training) and blinded to clinical data. Sonographers reported B-line concentration with 3 assessment methods: (1) normal (<3 B-lines) or abnormal (≥3 B-lines); (2) ordinal (normal, mild, moderate, or severe), and (3) counting B-lines (0-10; >10) in each zone. All statistical analyses were performed using SPSS version 18.0 (Chicago, IL) and Stata 12.1 (College Station, TX). We evaluated interrater and intrarater agreement using Intraclass correlation coefficients (ICCs). The right and left anterior/superior lung zones showed substantial agreement in all assessment methods and demonstrated best overall agreement (ICC for right: counting, ordinal, and normal/abnormal, 0.811 [0.714-0.875], 0.875 [0.810-0.917], and 0.729 [0.590-0.821], respectively). Furthermore, both expert/expert pairs and expert/novice pairs showed substantial agreement in the right and left anterior/superior thoracic zones (expert/expert, 0.904 and 0.777, respectively; expert/novice, 0.862, and 0.834, respectively). Second best agreement was found for the lateral/superior lung zones (right: counting, ordinal, and normal/abnormal, 0.744 [0.612-0.831], 0.686 [0.524-0.792], and 0.639 [0.453-0.761], respectively; and ICC left: counting, ordinal, and normal/abnormal, 0.671 [0.501-0.782], 0.615 [0.417-0.746], and 0.720 [0.577-0.815], respectively). When comparing agreement to distinguish “normal vs abnormal” B-line findings, our results showed significant agreement in all zones with the exception of the right and left inferior/lateral lung fields and left posterior lung. Reinterpretation by 2 experts of all their own randomized video clips at a later date showed agreement of 0.697 (n = 733 zones) and 0.647 (n = 266) zones for ordinal assessment of B-line concentration. Interrater agreement was best in the anterior/superior thoracic zones followed by the lateral/superior zones for both expert/expert and expert/novice pairs. Agreement in the lateral/inferior lung zones was overall inferior. Intrarater agreement was highest at extreme high or low numbers of B-lines.

Background Limited information exists on whether virtual training is equivalent to traditional in-person training in supporting the development of clinical providers. Methods A multi-site evaluation using survey methods was conducted with a multidisciplinary group of health professions trainees and supervisors within the Veterans Health Administration to assess the equivalence of two supervision modalities – exclusively in-person supervision and supervision incorporating at least some virtual supervision – on trainee clinical competency development, trainee preparedness to respond to patient emergencies, and effective trainee/supervisor working relationships. Results Trainees who experienced some virtual supervision rated their clinical competency levels as higher than trainees with only in-person supervision on competencies related to patient care, knowledge for practice, interpersonal and communication skills, practice-based learning and improvement, and systems-based practice. This trainee group also rated their level of preparation to respond to patient emergencies and several aspects of their supervisory working relationship more highly than in-person only trainees. Compared to those providing only in-person supervision, supervisors conducting some virtual supervision also rated their trainees as having higher levels of clinical competency on patient care, practice-based learning and improvement, and systems-based practice, as well as higher preparedness to respond to patient emergencies. Challenges and benefits to virtual supervision were also noted, though most trainees and supervisors who had participated in virtual supervision held a positive view of this modality. Conclusions These data constitute the first evaluation of the equivalency of some virtual and in-person only supervision in supporting trainee skill development and supervisory working relationships based on feedback from trainees and supervisors across multiple clinical disciplines. Trial registration Not applicable.