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Background A trial performed among unvaccinated, high-risk outpatients with COVID-19 during the delta period showed remdesivir reduced hospitalization. We used our real-world data platform to determine the effectiveness of remdesivir on reducing 28-day hospitalization among outpatients with mild-moderate COVID-19 during an Omicron period including BQ.1/BQ.1.1/XBB.1.5. Methods We did a propensity-matched, retrospective cohort study of non-hospitalized adults with SARS-CoV-2 infection between April 7, 2022, and February 7, 2023. Electronic healthcare record data from a large health system in Colorado were linked to statewide vaccination and mortality data. We included patients with a positive SARS-CoV-2 test or outpatient remdesivir administration. Exclusion criteria were other SARS-CoV-2 treatments or positive SARS-CoV-2 test more than seven days before remdesivir. The primary outcome was all-cause hospitalization up to day 28. Secondary outcomes included 28-day COVID-related hospitalization and 28-day all-cause mortality. Results Among 29,270 patients with SARS-CoV-2 infection, 1,252 remdesivir-treated patients were matched to 2,499 untreated patients. Remdesivir was associated with lower 28-day all-cause hospitalization (1.3% vs. 3.3%, adjusted hazard ratio (aHR) 0.39 [95% CI 0.23–0.67], p  < 0.001) than no treatment. All-cause mortality at 28 days was numerically lower among remdesivir-treated patients (0.1% vs. 0.4%; aOR 0.32 [95% CI 0.03–1.40]). Similar benefit of RDV treatment on 28-day all-cause hospitalization was observed across Omicron periods, aOR (95% CI): BA.2/BA2.12.1 (0.77[0.19–2.41]), BA.4/5 (0.50[95% CI 0.50–1.01]), BQ.1/BQ.1.1/XBB.1.5 (0.21[95% CI 0.08–0.57]. Conclusion Among outpatients with SARS-CoV-2 during recent Omicron surges, remdesivir was associated with lower hospitalization than no treatment, supporting current National Institutes of Health Guidelines.

Background Effectiveness of remdesivir (RDV) treatment on short-term mortality and other outcomes has been well-studied, yet the impact of RDV on long-term outcomes is less well-known. The objective of this study was to determine if inpatient RDV use in survivors of COVID-19 hospitalization is associated with reduced mortality after discharge. Methods This is a retrospective observational cohort study of patients hospitalized with COVID-19 between November 2020 and October 2022 in three health systems in Colorado and Utah. Real-world data were identified from electronic health records and state-level vaccination and mortality records. Our primary cohort were patients hospitalized with COVID-19, either treated or not treated with RDV, who survived to hospital discharge. Unadjusted and adjusted Cox proportional hazard models were used to estimate the hazard ratio of all-cause mortality following hospital discharge for those administered vs. not administered inpatient RDV. Sensitivity analyses included propensity-matching the primary cohort with in-hospital mortality as a competing risk. Secondary outcomes, including hospital and ED readmissions respectively, within 28 days after index hospitalization discharge, were also evaluated using Cox proportional hazard models. Results The primary cohort consisted of 9760 patients who survived index hospitalization and had between 6 and 29 months of post-hospital follow up. Of the primary cohort, 4771 (48.8%) were treated with inpatient RDV, inpatient RDV was associated with a decreased mortality hazard (aHR 0.73; 95% confidence interval (CI) 0.61–0.87) among survivors with up to two and a half years of follow-up. Results from a sensitivity analysis using in-hospital mortality as a competing risk were similar to the primary model (aHR 0.76; CI 0.63–0.92). RDV treatment was also associated with decreased re-hospitalization (aHR 0.77; CI 0.67–0.89) and ED readmission rates (aHR 0.79; CI 0.67–0.92). Most subgroups appear to benefit from RDV, with possible exceptions for patients infected during the first Omicron wave, having received at least 1 vaccine dose, and those not requiring supplemental oxygen during index hospitalization. Conclusions In this real-world analysis of three large health systems in Colorado and Utah, RDV use was associated with decreased long-term mortality among survivors of initial COVID-19 hospitalization. Inpatient RDV treatment may provide a mortality benefit after COVID-19 hospitalization.

Background Neutralizing monoclonal antibodies (mAbs) are highly effective in reducing hospitalization and mortality among early symptomatic COVID-19 patients in clinical trials and real-world data. While resistance to some mAbs has since emerged among new variants, characteristics associated with treatment failure of mAbs remain unknown. Methods This multicenter, observational cohort study included patients with COVID-19 who received mAb treatment between November 20, 2020, and December 9, 2021. We utilized electronic health records from a statewide health system plus state-level vaccine and mortality data. The primary outcome was mAb treatment failure, defined as hospitalization or death within 28 days of a positive SARS-CoV-2 test. Results COVID-19 mAb was administered to 7406 patients. Hospitalization within 28 days of positive SARS-CoV-2 test occurred in 258 (3.5%) of all patients who received mAb treatment. Ten patients (0.1%) died within 28 days, and all but one were hospitalized prior to death. Characteristics associated with treatment failure included having two or more comorbidities excluding obesity and immunocompromised status (adjusted odds ratio [OR] 3.71, 95% confidence interval [CI] 2.52–5.56), lack of SARS-CoV-2 vaccination (OR 2.73, 95% CI 2.01–3.77), non-Hispanic black race/ethnicity (OR 2.21, 95% CI 1.20–3.82), obesity (OR 1.79, 95% CI 1.36–2.34), one comorbidity (OR 1.68, 95% CI 1.11–2.57), age ≥ 65 years (OR 1.62, 95% CI 1.13–2.35), and male sex (OR 1.56, 95% CI 1.21–2.02). Immunocompromised status (none, mild, or moderate/severe), pandemic phase, and type of mAb received were not associated with treatment failure (all p > 0.05). Conclusions Comorbidities, lack of prior SARS-CoV-2 vaccination, non-Hispanic black race/ethnicity, obesity, age ≥ 65 years, and male sex are associated with treatment failure of mAbs.

Nirmatrelvir is a protease inhibitor with in-vitro activity against SARS-CoV-2, and ritonavir-boosted nirmatrelvir can reduce the risk of progression to severe COVID-19 among individuals at high risk infected with delta and early omicron variants. However, less is known about the effectiveness of nirmatrelvir–ritonavir during more recent BA.2, BA2.12.1, BA.4, and BA.5 omicron variant surges. We used our real-world data platform to evaluate the effect of nirmatrelvir–ritonavir treatment on 28-day hospitalisation, mortality, and emergency department visits among outpatients with early symptomatic COVID-19 during a SARS-CoV-2 omicron (BA.2, BA2.12.1, BA.4, and BA.5) predominant period in Colorado, USA. We did a propensity-matched, retrospective, observational cohort study of non-hospitalised adult patients infected with SARS-CoV-2 between March 26 and Aug 25, 2022, using records from a statewide health system in Colorado. We obtained data from the electronic health records of University of Colorado Health, the largest health system in Colorado, with 13 hospitals and 141 000 annual hospital admissions, and with numerous ambulatory sites and affiliated pharmacies around the state. Included patients had a positive SARS-CoV-2 test or nirmatrelvir–ritonavir medication order. Exclusion criteria were an order for or administration of other SARS-CoV-2 treatments within 10 days of a positive SARS-CoV-2 test, hospitalisation at the time of positive SARS-CoV-2 test, and positive SARS-CoV-2 test more than 10 days before a nirmatrelvir–ritonavir order. We propensity score matched patients treated with nirmatrelvir–ritonavir with untreated patients. The primary outcome was 28-day all-cause hospitalisation. Among 28 167 patients infected with SARS-CoV-2 between March 26 and Aug 25, 2022, 21 493 met the study inclusion criteria. 9881 patients received treatment with nirmatrelvir–ritonavir and 11 612 were untreated. Nirmatrelvir–ritonavir treatment was associated with reduced 28-day all-cause hospitalisation compared with no antiviral treatment (61 [0·9%] of 7168 patients vs 135 [1·4%] of 9361 patients, adjusted odds ratio (OR) 0·45 [95% CI 0·33–0·62]; p<0·0001). Nirmatrelvir–ritonavir treatment was also associated with reduced 28-day all-cause mortality (two [<0·1%] of 7168 patients vs 15 [0·2%] of 9361 patients; adjusted OR 0·15 [95% CI 0·03–0·50]; p=0·0010). Using subsequent emergency department visits as a surrogate for clinically significant relapse, we observed a decrease after nirmatrelvir–ritonavir treatment (283 [3·9%] of 7168 patients vs 437 [4·7%] of 9361 patients; adjusted OR 0·74 [95% CI 0·63–0·87]; p=0·0002). Real-world evidence reported during a BA.2, BA2.12.1, BA.4, and BA.5 omicron surge showed an association between nirmatrelvir–ritonavir treatment and reduced 28-day all-cause hospitalisation, all-cause mortality, and visits to the emergency department. With results that are among the first to suggest effectiveness of nirmatrelvir–ritonavir for non-hospitalised patients during an omicron period inclusive of BA.4 and BA.5 subvariants, these data support nirmatrelvir–ritonavir as an ongoing first-line treatment for adults acutely infected with SARS-CoV-2. US National Institutes of Health.

To evaluate whether subcutaneous neutralizing monoclonal antibody (mAb) treatment given in the emergency department (ED) setting was associated with reduced hospitalizations, mortality, and severity of disease when compared to nontreatment among mAb‐eligible patients with coronavirus disease 2019 (COVID‐19). This retrospective observational cohort study of ED patients utilized a propensity score‐matched analysis to compare patients who received subcutaneous casirivimab and imdevimab mAb to nontreated COVID‐19 control patients in November–December 2021. The primary outcome was all‐cause hospitalization within 28 days, and secondary outcomes were 90‐day hospitalization, 28‐ and 90‐day mortality, and ED length of stay (LOS). Of 1340 patients included in the analysis, 490 received subcutaneous casirivimab and imdevimab, and 850 did not received them. There was no difference observed for 28‐day hospitalization (8.4% vs. 10.6%; adjusted odds ratio [aOR] 0.79, 95% confidence intervals [CI] 0.53–1.17) or 90‐day hospitalization (11.6% vs. 12.5%; aOR 0.93, 95% CI 0.65–1.31). However, mortality at both the 28‐day and 90‐day timepoints was substantially lower in the treated group (28‐day 0.6% vs. 3.1%; aOR 0.18, 95% CI 0.08–0.41; 90‐day 0.6% vs. 3.9%; aOR 0.14, 95% CI 0.06–0.36). Among hospitalized patients, treated patients had shorter hospital LOS (5.7 vs. 11.4 days; adjusted rate ratio [aRR] 0.47, 95% CI 0.33–0.69), shorter intensive care unit LOS (3.8 vs. 10.2 days; aRR 0.22, 95% CI 0.14–0.35), and the severity of hospitalization was lower (aOR 0.45, 95% CI 0.21–0.97) compared to untreated. Among ED patients who presented for symptomatic COVID‐19 during the Delta variant phase, ED subcutaneous casirivimab/imdevimab treatment was not associated with a decrease in hospitalizations. However, treatment was associated with lower mortality at 28 and 90 days, hospital LOS, and overall severity of illness.

OBJECTIVES/GOALS: The rates of computational phenotyping algorithm reuse across health systems are low, leading to a proliferation of algorithms for the same trait. We propose a framework for reusing computational phenotyping algorithms and describe the real-world deployment of this framework for the development of the Colorado Diabetes EHR Research Repository. METHODS/STUDY POPULATION: The novel phenotype reuse framework consists of 4 steps: select algorithms that are appropriate for reuse by assessing whether they are fit for purpose; extend the algorithm to account for changes in data and care practice standards; localize the algorithm to use local database standards and terminologies; optimize the algorithm by applying a data driven approach to achieve the desired local performance. To identify individuals with type 1 diabetes (T1D) or type 2 diabetes (T2D), we selected and implemented T2D algorithms in a cohort of adults with any diabetes or pre-diabetes related diagnosis code, medication, or abnormal glucose-related laboratory test in the clinical data warehouse for UCHealth and the University of Colorado. RESULTS/ANTICIPATED RESULTS: We included a total of 926,290 patients who were identified by initial filters. Patients were more likely to be female (53%), identify as non-Hispanic white (69%) and had a median age of 58 years (IQR: 41, 70). Implementation, extension, localization, & optimization through iterative chart review prioritized high sensitivity for all-cause diabetes and high specificity for T1D and T2D. Of the original cohort, 252,946 (27%) were identified by the all-cause diabetes algorithm. Of these 11,688 were identified as T1D and 135,588 as T2D. After optimization the all-cause diabetes algorithm had 88% sensitivity, 90% specificity, 74% positive predictive value (PPV), and 96% negative predictive value (NPV). Our algorithms for T1D and T2D had high specificity (100% and 99%, respectively) and PPV (100 and 96% respectively). DISCUSSION/SIGNIFICANCE: Developing computational phenotyping algorithms is expensive and time consuming, yet algorithm reuse is low due to a lack of practical approaches for reusing algorithms. We demonstrate application of a novel framework for algorithm reuse, yielding good alignment of algorithm performance with study goals for identifying individuals with diabetes.

During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (PLTs), to optimize the distribution of scarce therapeutics. To evaluate whether a machine learning PLT-based method of scarce resource allocation optimizes the treatment benefit of COVID-19 neutralizing monoclonal antibodies (mAbs) during periods of resource constraint. This retrospective cohort study used electronic health record data from October 1, 2021, to December 11, 2021, for the training cohort and data from June 1, 2021, to October 1, 2021, for the testing cohort. The cohorts included patients who had positive test results for SARS-CoV-2 and qualified for COVID-19 mAb therapy based on the US Food and Drug Administration's emergency use authorization criteria, ascertained from the patient electronic health record. Only some of the qualifying candidates received treatment with mAbs. Data were analyzed between from January 2023 to May 2024. The primary outcome was overall expected hospitalization, assessed as the potential reduction in overall expected hospitalization if the PLT-based allocation system was used. This was compared to observed allocation using risk differences. Among 9542 eligible patients in the training cohort (5418 female [56.8%]; age distribution: 18-44 years, 4151 [43.5%]; 45-64 years, 3146 [33.0%]; and ≥65 years, 2245 [23.5%]), a total of 3862 (40.5%) received mAbs. Among 6248 eligible patients in the testing cohort (3416 female [54.7%]; age distribution: 18-44 years, 2827 [45.2%]; 45-64 years, 1927 [30.8%]; and ≥65 years, 1494 [23.9%]), a total of 1329 (21.3%) received mAbs. Treatment allocation using the trained PLT model led to an estimated 1.6% reduction (95% CI, -2.0% to -1.2%) in overall expected hospitalization compared to observed treatment allocation in the testing cohort. The visual assessment showed that the PLT-based point system had a larger reduction in 28-day hospitalization compared with the Monoclonal Antibody Screening Score (maximum overall hospitalization difference, -1.0% [95% CI, -1.3% to -0.7%]) in the testing cohort. This retrospective cohort study proposes and tests a PLT method, which can be linked to a electronic health record data platform to improve real-time allocation of scarce treatments. Use of this PLT-based allocation method would have likely resulted in fewer hospitalizations across a population than were observed in usual care, with greater expected reductions than a commonly used point system.

We performed a multicenter, randomized, controlled clinical trial of therapeutic peritoneal lavage (2 liters per hour for three days) in 91 patients with severe acute pancreatitis. Patients were entered into the study if severe pancreatitis was indicated by multiple laboratory criteria or diagnostic peritoneal lavage. All patients received full supportive treatment. The median time between the onset of symptoms and randomization was 38 hours. Forty-six patients were assigned to the control group and 45 to the lavage group. There were 13 deaths (28 per cent) and 16 patients with major complications (35 per cent) in the control group, as compared with 12 deaths (27 per cent) and 17 patients with major complications (38 per cent) in the lavage group. Lavage did not appear to modify the length of survival, the incidence of pancreatic collections (pseudocysts or abscesses), or the plasma amylase concentration. Considering the statistical power of the design, we conclude that the outcome of severe pancreatitis was not greatly, if at all, influenced by the regimen of peritoneal lavage used in this study. (N Engl J Med 1985; 312:399–404.) DESPITE improvements in intensive medical care, the mortality rate for patients with early signs of acute pancreatitis remains as high as 40 to 60 per cent. 1 2 3 4 Experimental studies have suggested that biologically active compounds accumulate in peritoneal fluid and are responsible for the shock-like systemic illness that is characteristic of the acute phase of severe pancreatitis. 5 6 7 8 If this hypothesis is correct, it is reasonable to attempt to modify the natural history of the disease by removing the ascitic fluid by means of peritoneal lavage. Since Wall 9 and Gjessing 10 independently described clinical improvement in a few patients with acute pancreatitis in . . .

Background: The aim of this study was to look into our experience of resection for hepatocellular carcinomas (HCCs) in a tertiary Hepatobiliary and Liver Transplant Unit in the UK. Methods: A retrospective analysis of our prospective database was carried out. Results: 715 cases of HCC were seen. 100 (13.9%) underwent hepatic resection and 159 (22.2%) orthotopic liver transplant. The 1-, 3- and 5-year overall survival following resection was 75.3, 37.0 and 21.5% respectively. Factors affecting long-term survival included resection margin (p < 0.001), recurrence (p < 0.007), α-fetoprotein >50 (p < 0.001) and serum albumin (p < 0.03). On multivariate analysis, recurrence (p < 0.001) and histological grade (p < 0.044) were significant. The 1- and 3-year recurrence rates were 27.3 and 72.5% respectively. Histological grade (p < 0.007), α-fetoprotein >50 (p < 0.033), female gender (p < 0.016) and portal vein involvement (p < 0.016) were significant in recurrence. Conclusions: Resection data from the East may not be comparable to the West owing to the higher transplant activity in the latter. Liver function tests and imaging would be sufficient to assess liver function prior to hepatic resection. HCC with cirrhosis should be assessed by a transplant unit prior to any treatment. The MELD (Model for End-Stage Liver Disease) score would be a valuable preoperative tool in the assessment of cirrhotics.