Preoperative Treatment of Severe Diabetes Mellitus and Hypertension Mitigates Healthcare Disparities and Prevents Adverse Postoperative Discharge to a Nursing Home.

OBJECTIVE: To evaluate whether patients of Black race are at higher risk of adverse postoperative discharge to a nursing home, and if a higher prevalence of severe diabetes mellitus and hypertension are contributing. BACKGROUND: It is unclear whether a patient's race predicts adverse discharge to a nursing home after surgery, and if preexisting diseases are contributing. METHODS: A total of 368,360 adults undergoing surgery between 2007 and 2020 across 2 academic healthcare networks in New England were included. Patients of self-identified Black or White race were compared. The primary outcome was postoperative discharge to a nursing facility. Mediation analysis was used to examine the impact of preexisting severe diabetes mellitus and hypertension on the primary association. RESULTS: In all, 10.3% (38,010/368,360) of patients were Black and 26,434 (7.2%) patients were discharged to a nursing home. Black patients were at increased risk of postoperative discharge to a nursing facility (adjusted absolute risk difference: 1.9%; 95% confidence interval: 1.6%-2.2%; P <0.001). A higher prevalence of preexisting severe diabetes mellitus and hypertension in Black patients mediated 30.2% and 15.6% of this association. Preoperative medication-based treatment adherent to guidelines in patients with severe diabetes mellitus or hypertension mitigated the primary association ( P -for-interaction <0.001). The same pattern of effect mitigation by pharmacotherapy was observed for the endpoint 30-day readmission. CONCLUSIONS: Black race was associated with postoperative discharge to a nursing facility compared to White race. Optimized preoperative assessment and treatment of diabetes mellitus and hypertension improves surgical outcomes and provides an opportunity to the surgeon to help eliminate healthcare disparities.

Private High School Reopened-COVID Mitigation and Clinical Surveillance Using an Internet Application.

CONTEXT: Recommendations for COVID-safe, in-person, high school education have included masks and distancing between students but do not describe a scalable surveillance solution to rapidly identify and mitigate disease prevalence or exposure. METHODS: Through an Internet application, all school participants reported symptoms, illness, or exposure daily. Physician-supervised follow-up interviews were reviewed and recorded in daily rounds. Students and faculty were allowed or prohibited to enter school based on the results. RESULTS: From August 30, 2020, until April 13, 2021, a high school in Bergen County, New Jersey (an epicenter of high COVID prevalence), with 889 students and 214 faculty members, staff, and volunteers, generated 1497 assessments. Reasons for initial evaluation included 48 (3%) participants with positive COVID tests, 520 (34%) COVID-exposed, 178 (12%) exposed to someone with symptoms and unknown COVID status, 208 (14%) subjects with symptoms themselves, 525 (35%) exposed to a high-risk geography or air travel, and 12 (1%) contacts of a contact. Of the 61 subjects ultimately diagnosed with COVID, the sources of infection were 36 (57%) home exposure, 16 (27%) confirmed nonschool sources, 8 (13%) unknown, 1 (2%) travel to a high-risk area, and only one potential case of in-school transmission. CONCLUSIONS: Masks, distance, and aggressive contact tracing supported by an Internet application with consistent application of quarantine protocols successfully permitted in-school education without COVID spread in a high prevalence environment. This finding remains important to guide safety measures should vaccine-resistant strains-or new pandemics-challenge us in the future.

Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study.

BACKGROUND: During a pandemic, it is important for clinicians to stratify patients and decide who receives limited medical resources. Machine learning models have been proposed to accurately predict COVID-19 disease severity. Previous studies have typically tested only one machine learning algorithm and limited performance evaluation to area under the curve analysis. To obtain the best results possible, it may be important to test different machine learning algorithms to find the best prediction model. OBJECTIVE: In this study, we aimed to use automated machine learning (autoML) to train various machine learning algorithms. We selected the model that best predicted patients' chances of surviving a SARS-CoV-2 infection. In addition, we identified which variables (ie, vital signs, biomarkers, comorbidities, etc) were the most influential in generating an accurate model. METHODS: Data were retrospectively collected from all patients who tested positive for COVID-19 at our institution between March 1 and July 3, 2020. We collected 48 variables from each patient within 36 hours before or after the index time (ie, real-time polymerase chain reaction positivity). Patients were followed for 30 days or until death. Patients' data were used to build 20 machine learning models with various algorithms via autoML. The performance of machine learning models was measured by analyzing the area under the precision-recall curve (AUPCR). Subsequently, we established model interpretability via Shapley additive explanation and partial dependence plots to identify and rank variables that drove model predictions. Afterward, we conducted dimensionality reduction to extract the 10 most influential variables. AutoML models were retrained by only using these 10 variables, and the output models were evaluated against the model that used 48 variables. RESULTS: Data from 4313 patients were used to develop the models. The best model that was generated by using autoML and 48 variables was the stacked ensemble model (AUPRC=0.807). The two best independent models were the gradient boost machine and extreme gradient boost models, which had an AUPRC of 0.803 and 0.793, respectively. The deep learning model (AUPRC=0.73) was substantially inferior to the other models. The 10 most influential variables for generating high-performing models were systolic and diastolic blood pressure, age, pulse oximetry level, blood urea nitrogen level, lactate dehydrogenase level, D-dimer level, troponin level, respiratory rate, and Charlson comorbidity score. After the autoML models were retrained with these 10 variables, the stacked ensemble model still had the best performance (AUPRC=0.791). CONCLUSIONS: We used autoML to develop high-performing models that predicted the survival of patients with COVID-19. In addition, we identified important variables that correlated with mortality. This is proof of concept that autoML is an efficient, effective, and informative method for generating machine learning-based clinical decision support tools.

AKI in Hospitalized Patients with and without COVID-19: A Comparison Study.

BACKGROUND: Reports from centers treating patients with coronavirus disease 2019 (COVID-19) have noted that such patients frequently develop AKI. However, there have been no direct comparisons of AKI in hospitalized patients with and without COVID-19 that would reveal whether there are aspects of AKI risk, course, and outcomes unique to this infection. METHODS: In a retrospective observational study, we evaluated AKI incidence, risk factors, and outcomes for 3345 adults with COVID-19 and 1265 without COVID-19 who were hospitalized in a large New York City health system and compared them with a historical cohort of 9859 individuals hospitalized a year earlier in the same health system. We also developed a model to identify predictors of stage 2 or 3 AKI in our COVID-19. RESULTS: We found higher AKI incidence among patients with COVID-19 compared with the historical cohort (56.9% versus 25.1%, respectively). Patients with AKI and COVID-19 were more likely than those without COVID-19 to require RRT and were less likely to recover kidney function. Development of AKI was significantly associated with male sex, Black race, and older age (>50 years). Male sex and age >50 years associated with the composite outcome of RRT or mortality, regardless of COVID-19 status. Factors that were predictive of stage 2 or 3 AKI included initial respiratory rate, white blood cell count, neutrophil/lymphocyte ratio, and lactate dehydrogenase level. CONCLUSIONS: Patients hospitalized with COVID-19 had a higher incidence of severe AKI compared with controls. Vital signs at admission and laboratory data may be useful for risk stratification to predict severe AKI. Although male sex, Black race, and older age associated with development of AKI, these associations were not unique to COVID-19.

The relationship between adrenal incidentalomas and mortality risk.

OBJECTIVE: To determine all-cause mortality risk in patients with and without adrenal incidentaloma. METHODS: Retrospective cohort study of patients with CT abdomen performed within 24 h of emergency room presentation at an academic medical center from January 1, 2005, to December 31, 2009, without history of adrenal disease, adrenal lab testing, or cancer. Incidentaloma cohort identified by database query of imaging reports followed by manual review and matched to no-nodule controls at 3:1 on age ± 1 year and exam date ± 3 months. Mortality ascertained by in-hospital deaths and National Death Index query. Survival analysis performed with Kaplan-Meier curves and Cox proportional hazards models. RESULTS: Among 42,575 adults with abdominal CT exams, 969 adrenal incidentaloma patients and 2907 no-nodule controls were identified. All 3876 individuals entered survival analysis with 31,182 person-years at risk (median follow-up 8.9 years [IQR, 6.9-10.7]). All-cause mortality was significantly higher among those with adrenal incidentalomas (353/969, 36.4%) compared with those without (919/2907, 31.6%; mortality difference 7.6 per 1000 person-years; multivariable-adjusted hazard ratio [aHR] 1.14; 95% CI, 1.003-1.29). Exploratory analyses, limited by missing covariates, found that adrenal incidentalomas were associated with significantly increased incidence of malignancy (aHR 1.61; 95% CI, 1.22-2.12), diabetes (aHR 1.43; 95% CI, 1.18-1.71), heart failure (aHR 1.32; 95% CI, 1.07-1.63), peripheral vascular disease (aHR 1.28; 95% CI, 1.95-1.56), renal disease (aHR 1.21; 95% CI, 1.01-1.44), and chronic pulmonary disease (aHR 1.22; 95% CI, 1.01-1.46) compared with controls. CONCLUSIONS: Adrenal incidentalomas are associated with increased mortality and may represent a clinically valuable biomarker. KEY POINTS: • Adrenal incidentalomas are associated with increased mortality. • Adrenal incidentaloma size is not predictive of mortality. • On exploratory analyses, adrenal incidentalomas are associated with chronic illnesses.

Ventricular Myocardial Fat: An Unexpected Biomarker for Long-term Survival?

PURPOSE: To examine the association between myocardial fat, a poorly understood finding frequently observed on non-contrast CT, and all-cause mortality in patients with and without a history of prior MI. MATERIALS AND METHODS: A retrospective cohort from a diverse urban academic center was derived from chronic myocardial infarction (MI) patients (n = 265) and three age-matched patients without MI (n = 690) who underwent non-contrast chest CT between 1 January 2005-31 December 2008. CT images were reviewed for left and right ventricular fat. Electronic records identified clinical variables. Kaplan-Meier and Cox proportional hazard analyses assessed the association between myocardial fat and all-cause mortality. The net reclassification improvement assessed the utility of adding myocardial fat to traditional risk prediction models. RESULTS: Mortality was 40.1% for the no MI and 71.7% for the MI groups (median follow-up, 6.8 years; mean age, 73.7 ± 10.6 years). In the no MI group, 25.7% had LV and 49.9% RV fat. In the MI group, 32.8% had LV and 42.3% RV fat. LV and RV fat was highly associated (OR 5.3, p < 0.001). Ventricular fat was not associated with cardiovascular risk factors. Myocardial fat was associated with a reduction in the adjusted hazard of death for both the no MI (25%, p = 0.04) and the MI group (31%, p = 0.018). Myocardial fat resulted in the correct reclassification of 22% for the no MI group versus the Charlson score or calcium score (p = 0.004) and 47% for the MI group versus the Charlson score (p = 0.0006). CONCLUSIONS: Patients with myocardial fat have better survival, regardless of MI status, suggesting that myocardial fat is a beneficial biomarker and may improve risk stratification. KEY POINTS: • Myocardial fat is commonly found on chest CT, yet is poorly understood • Myocardial fat is associated with better survival in patients with and without prior MI and is not associated with traditional cardiovascular risk factors • This finding may provide clinically meaningful prognostic value in the risk stratification of patients.

Prospective study of a non-restrictive decision rule for acute aortic syndrome.

OBJECTIVES: To determine the impact of a non-restrictive clinical decision rule on CT utilization for Emergency Department patients suspected of having an acute aortic syndrome (AAS). METHODS: We prospectively assessed the performance of a previously described, collaboratively designed, non-restrictive clinical decision rule for AAS. Emergency Department patients with suspected AAS were stratified into low and high-risk groups based on decision rule results, from July 2013-August 2014. Patients with acute trauma, prior AAS or aortic surgery were excluded. CT dose reduction protocols were concurrently implemented as a quality improvement measure. Bivariate analysis was performed to compare the prospective cohort with the historical derivation cohort for CT utilization rates, results of CT, AAS incidence and radiation exposure. The performance of the clinical decision rule was evaluated. RESULTS: Compared with the historic cohort, the study cohort demonstrated a lower CT utilization rate [0.344% (427/124,093) versus 0.477% (1465/306,961), (p<0.001)], a trend toward higher CT diagnostic yield [4.4% (19/427) versus 2.7% (40/1465), (p=0.08)]. AAS incidence was similar [0.015% (19/124,093) versus 0.013% (40/306,961), (p=0.57)]. The mean effective radiation dose was markedly lower [12±5.5mSv versus 43±20mSv, (p<0.0001)]. The clinical decision rule correctly stratified only 56% (10/18) of patients with AAS as high-risk. CONCLUSIONS: A non-restrictive, collaboratively designed, clinical decision rule for Emergency Department patients with suspected AAS performed poorly in risk-stratifying patients for AAS. However, its implementation was associated with a significant and safe decrease in CT utilization.

Discharge service as a determinant of 30-day readmission in a cohort of maintenance hemodialysis patients: a retrospective cohort study.

BACKGROUND: End stage renal disease (ESRD) patients on maintenance hemodialysis, are high utilizers of inpatient services. Because of data showing improved outcomes in medical patients admitted to hospitalist-run, non-teaching services, we hypothesized that discharge from a hospitalist-run, non-teaching service is associated with lower risk of 30-day re-hospitalization in a cohort of patients on hemodialysis. METHODS: One thousand and 84 consecutive patients with ESRD on maintenance hemodialysis who were admitted to Montefiore, a tertiary care center, in 2014 were analyzed using the electronic medical records. We evaluated factors associated with 30-day readmission in multivariable regression models. We then tested the association of care by a hospitalist-run, non-teaching service with 30-day readmission in a propensity score matched analysis. RESULTS: Patients cared for on the hospitalist-run, non-teaching service had lower socio-economic scores (SES) and had longer lengths of stay (LOS), as compared to a standard teaching service, but otherwise the populations were similar. In multivariable testing, severity of illness, (OR 2.40, (95%CI: 1.43-4.03) for highest quartile) number of previous hospitalizations (OR 1.22 (95%CI:1.16-1.28) for each admission), and discharge to a skilled nursing facility (SNF)(OR 1.56 (95%CI:1.01-2.43) were significantly associated with 30-day re-admissions. Care by the non-teaching service was associated with a lower risk of 30-day readmission, even after adjusting for clinical factors and matching based on propensity score (OR 0.65(95%CI:0.46-0.91) and 0.71(95%CI:0.66-0.77) respectively). CONCLUSIONS: Patients with ESRD on hemodialysis discharged from a hospitalist-run, non-teaching medicine service had lower odds of readmission as compared to those patients discharged from a standard teaching service.

Incidental pancreatic cystic lesions: is there a relationship with the development of pancreatic adenocarcinoma and all-cause mortality?

PURPOSE: To establish the effect of incidental pancreatic cysts found by using computed tomographic (CT) and magnetic resonance (MR) imaging on the incidence of pancreatic ductal adenocarcinoma and overall mortality in patients from an inner-city urban U.S. tertiary care medical center. MATERIALS AND METHODS: Institutional review board granted approval for the study and waived the informed consent requirement. The study population comprised cyst and no-cyst cohorts drawn from all adults who underwent abdominal CT and/or MR November 1, 2001, to November 1, 2011. Cyst cohort included patients whose CT or MR imaging showed incidental pancreatic cysts; no-cyst cohort was three-to-one frequency matched by age decade, imaging modality, and year of initial study from the pool without reported incidental pancreatic cysts. Patients with pancreatic cancer diagnosed within 5 years before initial CT or MR were excluded. Demographics, study location (outpatient, inpatient, or emergency department), dates of pancreatic adenocarcinoma and death, and modified Charlson scores within 3 months before initial CT or MR examination were extracted from the hospital database. Cox hazard models were constructed; incident pancreatic adenocarcinoma and mortality were outcome events. Adenocarcinomas diagnosed 6 months or longer after initial CT or MR examination were considered incident. RESULTS: There were 2034 patients in cyst cohort (1326 women [65.2%]) and 6018 in no-cyst cohort (3,563 [59.2%] women); respective mean ages were 69.9 years ± 15.1(standard deviation) and 69.3 years ± 15.2, respectively (P = .129). The relationship between mortality and incidental pancreatic cysts varied by age: hazard ratios were 1.40 (95% confidence interval [ CI confidence interval ]: 1.13, 1.73) for patients younger than 65 years and 0.97 (95% CI confidence interval : 0.88, 1.07), adjusted for sex, race, imaging modality, study location, and modified Charlson scores. Incidental pancreatic cysts had a hazard ratio of 3.0 (95% CI confidence interval : 1.32, 6.89) for adenocarcinoma, adjusted for age, sex, and race. CONCLUSION: Incidental pancreatic cysts found by using CT or MR imaging are associated with increased mortality for patients younger than 65 years and an overall increased risk of pancreatic adenocarcinoma.

Development of an electronic medical record-based algorithm to identify patients with unknown HIV status.

Individuals with unknown HIV status are at risk for undiagnosed HIV, but practical and reliable methods for identifying these individuals have not been described. We developed an algorithm to identify patients with unknown HIV status using data from the electronic medical record (EMR) of a large health care system. We developed EMR-based criteria to classify patients as having known status (HIV-positive or HIV-negative) or unknown status and applied these criteria to all patients seen in the affiliated health care system from 2008 to 2012. Performance characteristics of the algorithm for identifying patients with unknown HIV status were calculated by comparing a random sample of the algorithm's results to a reference standard medical record review. The algorithm classifies all patients as having either known or unknown HIV status. Its sensitivity and specificity for identifying patients with unknown status are 99.4% (95% CI: 96.5-100%) and 95.2% (95% CI: 83.8-99.4%), respectively, with positive and negative predictive values of 98.7% (95% CI: 95.5-99.8%) and 97.6% (95% CI: 87.1-99.1%), respectively. Using commonly available data from an EMR, our algorithm has high sensitivity and specificity for identifying patients with unknown HIV status. This algorithm may inform expanded HIV testing strategies aiming to test the untested.

Medication use evaluation of tocilizumab implementation in COVID-19 treatment guidelines: A causal inference approach.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Introduction of new medications to health-system formularies is often not accompanied by assessments of their clinical impact on the local patient population. The growing availability of electronic health record (EHR) data and advancements in pharmacoepidemiology methods offer institutions the opportunity to monitor the medication implementation process and assess clinical effectiveness in the local clinical context. In this study, we applied novel causal inference methods to evaluate the effects of a formulary policy introducing tocilizumab therapy for critically ill patients with coronavirus disease 2019 (COVID-19). METHODS: We conducted a medication use evaluation utilizing EHR data from patients admitted to a large medical center during the 6 months before and after implementation of a formulary policy endorsing the use of tocilizumab for treatment of COVID-19. The impact of tocilizumab on 28-day all-cause mortality was assessed using a difference-in-differences analysis, with ineligible patients serving as a nonequivalent control group, and a matched analysis guided by a target trial emulation framework. Safety endpoints assessed included the incidence of secondary infections and liver enzyme elevations. Our findings were benchmarked against clinical trials, an observational study, and a meta-analysis. RESULTS: Following guideline modification, tocilizumab was administered to 69% of eligible patients. This implementation was associated with a 3.1% absolute risk reduction in 28-day mortality (odds ratio, 0.86; number needed to treat to prevent one death, 32) attributable to the inclusion of tocilizumab in the guidelines and an additional 8.6% absolute risk reduction (odds ratio, 0.65; number needed to treat to prevent one death, 12) linked to its administration. These findings were consistent with estimates from published literature, although the effect estimates from the difference-in-differences analysis exhibited imprecision. CONCLUSION: Evaluating formulary management decisions through novel causal inference approaches offers valuable estimates of clinical effectiveness and the potential to optimize the impact of new medications on population outcomes.

Imaging Utilization and Cost of Substance Use in an Urban Academic Medical Center During the Contemporary Opioid Epidemic.

RATIONALE AND OBJECTIVES: To determine the recent impact of illicit substance use on imaging utilization and associated costs. METHODS: Retrospective study from an inner city urban multi-site academic medical center. Institutional Review Board (IRB) approval was obtained with a waiver of informed consent. A substance use cohort comprised patients 12 years old presenting to the Emergency Department (ED) January 2017 to June 2019 with a positive urine toxicology and an ICD code associated with substance use. The comparison cohort was randomly selected from a group of ED patients who presented with no or negative urine toxicology and no documented substance use ICD code. Data extracted from the EMR included demographics, number and type of imaging studies, Charlson comorbidity index, and in-hospital mortality during the study period. RESULTS: The substance use and comparison cohorts comprised 3191 and 3200 patients, respectively. The substance use cohort was older on average (mean age 45.67 ± 14.88 vs 43.91 ± 20.57 years), more often male (63% [2026/3191] vs. 39% [1255/3200]) and had a mean Charlson score 88% higher than the comparison cohort (3.33 vs 1.78). The majority of both cohorts were ethnic minorities (<10% white). The substance use cohort had significantly more imaging vs the comparison cohort, total 36,413 (mean 11.41 exams/patient) vs total 12,399 (mean 3.87 exams/patient), p < 0.0001, and was higher for all modalities except mammography. Average imaging costs per patient were nearly 300% higher for the substance use vs comparison cohort, ($1287.18 vs. $434.70). CONCLUSION: Imaging utilization and associated costs were substantially higher for patients with a positive urine toxicology and substance use related ICD codes compared to the broader ED population in an underserved urban population.

On-Site More Frequent Dialysis May Hasten Return Home for Nursing Home End-Stage Renal Disease Patients.

BACKGROUND: A direct outcome comparison between Skilled nursing facility (SNF) patients receiving on-site more frequent dialysis (MFD) targeting 14 hours of treatment over five sessions weekly compared to on-site conventional dialysis for death, hospitalization and speed of return home has not been reported. METHODS: From Jan 1, 2022, to July 1, 2023, in a retrospective prospective observational design, using an intent to treat and competing risk strategy, all new admissions to an on-site in SNF dialysis service admitted to nursing homes with on-site MFD dialysis were compared to admissions to nursing homes providing on-site conventional dialysis for the outcome goal of 90 day cumulative incidence of discharge to home, while monitoring safety issues represented by the competing risks of hospitalization and death. RESULTS: 10,246 MFD dialytic episodes and 3,451 conventional dialytic episodes were studied in 195 nursing homes in 12 states. At baseline the MFD population was consistently sicker than CONVENTIONAL dialysis population with a first systolic blood pressure in 23% vs 7.6% (p<.001), lower mean hemoglobin (9.3g/dl vs 10.4g/dl; p<.001), lower iron saturation (25.7% vs 26.6%; p=0.02), higher Charlson score (3.5 vs 3.0; p<.001), higher mean age (67.6 vs 66.7; p<.001). ), more complicated diabetes (31% vs 24%; P<.001), cerebrovascular disease ( 12.6% vs 6.8%:p<.001), and congestive heart failure (24% vs 18%). At 42 days, discharge to home was 25% greater in the MFD than conventional group (17.5% vs 14%) without worsened hospitalization or death. CONCLUSION: Despite a handicap of sicker patients at baseline, real-world application of MFD appears to hasten return home from SNFs compared to conventional dialysis. The findings suggests that MFD allows for SNF acceptance of sicker patients, presumably permitting earlier hospital discharge, without safety compromise as measured by death or rehospitalization benefitting hospitals, patients, and payers.

Preliminary development of a clinical decision rule for acute aortic syndromes.

OBJECTIVE: Patients with suspected acute aortic syndromes (AAS) often undergo computed tomography (CT) with negative results. We sought clinical and diagnostic criteria to identify low-risk patients, an initial step in developing a clinical decision rule. METHODS: We retrospectively identified all adults presenting to our emergency department (ED) from January 1, 2006, to August 1, 2010, who underwent CT angiography for suspected AAS without prior trauma or AAS. A total of 1465 patients met inclusion criteria; a retrospective case-controlled review (ratio 1:4) was conducted. Cases were diagnosed with aortic dissection, intramural hematoma, penetrating atherosclerotic ulcer, or ruptured aneurysm. RESULTS: Of the patients who underwent CT, 2.7% (40/1465) had an AAS; 2 additional cases were diagnosed after admission (ED miss rate, 5% [2/42]). Patients with AAS were significantly older than controls (66 vs 59 years; P = .008). Risk factors included abnormal chest radiograph (sensitivity, 79% [26/33]; specificity, 82% [113/137]) and acute chest pain (sensitivity, 83% [29/35]; specificity, 71% [111/157]). None of the 19 patients with resolved pain upon ED presentation had AAS. These data support a 2-step rule: first screen for ongoing pain; if present, screen for acute chest pain or an abnormal chest radiograph. This approach achieves a 54% (84/155) reduction in CT usage with a sensitivity for AAS of 96% (95% confidence interval, 89%-100%), negative predictive value of 99.8% (99.4%-100%), and a false-negative rate of 1.7% (1/84). CONCLUSIONS: Our results demonstrate a need to safely identify patients at low risk for AAS who can forgo CT. We developed a preliminary 2-step clinical decision rule, which requires validation.

Evaluating Pharmacist-Led Heart Failure Transitions of Care Clinic: Impact of Analytic Approach on Readmission Rate Endpoints.

Studies evaluating pharmacist-led transitions of care (TOC) services for heart failure patients reported profound decreases in hospital readmissions. Most studies restricted their analysis to clinic attendees (as-treated analysis), which can introduce selection and immortal time bias. In this study, we evaluated the impact of including only clinic attendees vs all clinic referrals in assessing the effectiveness of a pharmacist-led heart failure transitions of care (PharmD HF TOC) clinic program on 30-day readmissions. This is a retrospective, observational study of patients discharged from a heart failure hospitalization at a large urban academic medical center from August 2016 to December 2018. Primary exposure was the provision of a PharmD HF TOC clinic appointment in the intent-to-treat analysis and the attendance of the clinic in the as-treated analysis. Primary outcome was all-cause readmissions within 30 days of discharge. There were 766 and 1015 patients included in the as-treated and intent-to-treat analyses, respectively. In the as-treated analysis, 30-day all-cause readmissions were significantly lower in the intervention group compared to the control group (12.4% vs 19.6%, P = 0.018). In contrast, the intent-to-treat analysis did not reveal a significant difference in 30-day all-cause readmissions between the intervention group and the control group (18.2% vs 19.6%, P = 0.643). Pharmacist-led heart failure TOC program is associated with a reduction in 30-day all-cause readmissions only when restricting the analysis to clinic attendees. Future studies evaluating the effectiveness of post-discharge TOC services need to carefully consider the biases inherent in the evaluation methods employed.

Improved nursing home end-stage renal disease patient participation in physical therapy with onsite, more frequent dialysis.

INTRODUCTION: For end-stage renal disease (ESRD) patients residing in skilled nursing facilities (SNFs), the logistics and physical exhaustion of life-saving hemodialysis therapy often conflict with rehabilitation goals. Integration of dialysis care with rehabilitation programs in a scalable and cost-efficient manner has been a significant challenge. SNF-resident ESRD patients receiving onsite, more frequent hemodialysis (MFD) have reported rapid post-dialysis recovery. We examined whether such patients have improved Physical Therapy (PT) participation. METHODS: We conducted a retrospective electronic medical records review of SNF-resident PT participation rates within a multistate provider of SNF rehabilitation care from January 1, 2022 to June 1, 2022. We compared three groups: ESRD patients receiving onsite MFD (Onsite-MFD), ESRD patients receiving offsite, conventional 3×/week dialysis (Offsite-Conventional-HD), and the general non-ESRD SNF rehabilitation population (Non-ESRD). We evaluated physical therapy participation rates based on a predefined metric of missed or shortened (<15 min) therapy days. Baseline demographics and functional status were assessed. FINDINGS: Ninety-two Onsite-MFD had 2084 PT sessions scheduled, 12,916 Non-ESRD had 225,496 PT sessions scheduled, and 562 Offsite-Conventional-HD had 9082 PT sessions scheduled. In mixed model logistic regression, Onsite-MFD achieved higher PT participation rates than Offsite-Conventional-HD (odds ratio: 1.8, CI: 1.1-3.0; p < 0.03), and Onsite-MFD achieved equivalent PT participation rates to Non-ESRD (odds ratio: 1.2, CI: 0.3-1.9; p < 0.46). Baseline mean ± SD Charlson Comorbidity score was significantly higher in Onsite-MFD (4.9 ± 2.0) and Offsite-Conventional-HD (4.9 ± 1.8) versus Non-ESRD (2.6 ± 2.0; p < 0.001). Baseline mean self-care and mobility scores were significantly lower in Onsite-MFD versus Non-ESRD or Offsite-Conventional-HD. DISCUSSION: SNF-resident ESRD patients receiving MFD colocated with rehabilitation had higher PT participation rates than those conventionally dialyzed offsite and equivalent PT participation rates to the non-ESRD SNF-rehabilitation general population, despite being sicker, less independent, and less mobile. We report a scalable program integrating dialysis and rehabilitation care as a potential solution for ESRD patients recovering from acute hospitalization.

Pulmonary embolism diagnosis and mortality with pulmonary CT angiography versus ventilation-perfusion scintigraphy: evidence of overdiagnosis with CT?

OBJECTIVE: The purposes of this study were to determine whether pulmonary emboli diagnosed with pulmonary CT angiography (CTA) represent a milder disease spectrum than those diagnosed with ventilation-perfusion (V/Q) scintigraphy, to determine the trends in incidence and mortality among patients with the diagnosis of pulmonary embolism from 2000 to 2007, and to correlate incidence and mortality trends with imaging modality trends. MATERIALS AND METHODS: Diagnoses of pulmonary embolism from 2000 to 2007 at an urban academic medical center were retrospectively identified. Patient data were collected from the hospital database and the Social Security Death Index. Incident diagnoses, type of imaging used, and date of death were documented. Bivariate and multivariate analyses were used to explore the relations between imaging use and the incidence and mortality of pulmonary embolism. Logistic regression analysis was used to estimate the odds of death of pulmonary embolism diagnosed with pulmonary CTA versus V/Q scintigraphy. RESULTS: The cases of 2087 patients (1361 women, 726 men; mean age, 61.8 years) with pulmonary embolism were identified. From 2000 to 2007 the incidence of pulmonary embolism increased from 0.69 to 0.91 per 100 admissions in strong correlation with increased use of pulmonary CTA. There was no change in mortality, but the case-fatality rate decreased from 5.7% to 3.3%. On average, pulmonary emboli diagnosed with pulmonary CTA were one half as lethal as those diagnosed with V/Q scintigraphy (odds ratio, 0.538; 95% CI, 0.314-0.921). CONCLUSION: The results of this study are evidence that the shift in imaging from V/Q scintigraphy to pulmonary CTA resulted in increased diagnosis of a less fatal spectrum of pulmonary embolic disease, raising the possibility of overdiagnosis. Outcome-based clinical trials with long-term follow-up would be helpful to further guide management.

Does comorbidity burden explain the higher COVID-19 mortality risk among men? A retrospective cross-sectional analysis of a well-defined cohort of patients in Bronx, New York.

OBJECTIVES: Men have a higher mortality rate and more severe COVID-19 infection than women. The mechanism for this is unclear. We hypothesise that innate sex differences, rather than comorbidity burden, drive higher male mortality. DESIGN: Retrospective cohort. SETTING: Montefiore Health System (MHS) in Bronx, New York, USA. PARTICIPANTS: A cohort population of 364 992 patients at MHS between 1 January 2018 and 1 January 2020 was defined, from which individuals hospitalised during the pre-COVID period (1 January 2020-15 February 2020) (n=5856) and individuals hospitalised during the COVID-19 surge (1 March 2020-15 April 2020) (n=4793) were examined for outcomes. A subcohort with confirmed COVID-19+ hospitalisation was also examined (n=1742). PRIMARY AND SECONDARY OUTCOME MEASURES: Hospitalisation and in-hospital mortality. RESULTS: Men were older, had more comorbidities, lower body mass index and were more likely to smoke. Unadjusted logistic regression showed a higher odds of death in hospitalised men than women during both the pre-COVID-19 and COVID-19 periods (pre-COVID-19, OR: 1.66 vs COVID-19 OR: 1.98). After adjustment for relevant clinical and demographic factors, the higher risk of male death attenuated towards the null in the pre-COVID-19 period (OR 1.36, 95% CI 1.05 to 1.76) but remained significantly higher in the COVID-19 period (OR 2.02; 95% CI 1.73 to 2.34).In the subcohort of COVID-19+ hospitalised patients, men had 1.37 higher odds of in-hospital death (95% CI 1.09 to 1.72), which was not altered by adjustment for comorbidity (OR remained at 1.38 (95% CI 1.08 to 1.76)) but was attenuated with addition of initial pulse oximetry on presentation (OR 1.26, 95% CI 0.99 to 1.62). CONCLUSIONS: Higher male mortality risk during the COVID-19 period despite adjustment for comorbidity supports the role of innate physiological susceptibility to COVID-19 death. Attenuation of higher male risk towards the null after adjustment for severity of lung disease in hospitalised COVID-19+ patients further supports the role of higher severity of COVID-19 pneumonia in men.

Post-dialysis recovery time in ESRD patients receiving more frequent hemodialysis in skilled nursing facilities.

INTRODUCTION: Post-dialysis recovery time (DRT) has an important relationship to quality of life and survival, as identified in studies of ESRD patients on conventional dialysis. ESRD patients are often discharged from hospitals to skilled nursing facilities (SNFs) where on-site treatment using home hemodialysis technology is increasingly offered, but nothing is known about DRT in this patient population. METHODS: From November 4, 2019 to June 11, 2021, within a dialysis organization providing service across 12 states and 154 SNFs, patients receiving in-SNF, more frequent dialysis (MFD) (modeled to deliver 14 treatment hours minimum per week and stdKt/V ≥2.0) were asked to describe their post-dialysis recovery time following their previous treatment, within predefined categoric choices: 0-½, ½-1, 1-2, 2-4, 4-8, 8-12 h, by next morning, or not even by next morning. Patients reporting DRT following at least one full-week treatment opportunity were included in a mixed model logistic regression of rapid recovery (DRT ≤2 h). FINDINGS: Two thousand three hundred and nine patients met the statistical modeling inclusion criteria, providing DRT on 108,876 dialysis sessions, while receiving mean (SD) 4.3 (0.96) weekly dialysis treatments. 2118 (92%) reported DRT ≤2 h. Results appeared biologically plausible, as lower odds of rapid DRT were observed for patients who were older, missed their previous treatment, or experienced intradialytic hypotension. Greater odds of rapid DRT were observed in patients receiving five dialyses in the previous week or having 160-179 mmHg pre-hemodialysis systolic blood pressure. Rapid recovery was associated with reduced mortality or hospitalization. DISCUSSION: SNF dialysis patients receiving 5x per week MFD report rapid recovery time ≤2 h in 92% of dialyses despite advanced age, frailty, and comorbidities. Future studies will assess the practical ramifications of rapid DRT perception/experience on nursing home rehabilitation programs, which could impact patient health beyond the nursing home stay.