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Identifying patients with rare diseases like alpha-1 antitrypsin deficiency (AATD) is challenging. Machine-learning models may be trained to identify patients with rare diseases using large-scale, real-world databases, whereas electronic medical records have low numbers of confirmed cases and have limited use in training such models. We applied a machine-learning model to a large US claims database to identify undiagnosed symptomatic patients with AATD. Using deidentified data from the Komodo US claims database (April 26, 2016–January 31, 2023), a model was trained to identify symptomatic patients with high probability of AATD. Eighty claims records for high-probability candidates identified by the model were independently reviewed and validated by 2 clinical experts. The experts independently indicated that of the 80 high-probability candidate patients, 65 (81%) and 62 (78%) patients, respectively, should be tested for AATD. Feedback from this validation step informed model optimization. The optimized model was applied to claims data to identify symptomatic patients with probable AATD. Eleven and 14 “features” of the claims data were informative in distinguishing patients with AATD from patients with COPD without AATD and from unspecified chronic liver diseases. Moreover, patients with diagnosed AATD and COPD without AATD had unique cadences of similar medical events in their diagnostic journeys. Our work shows that a machine-learning model trained on a large US claims database can accurately identify symptomatic patients with AATD and provides useful insights into the diagnostic journey of patients with AATD.

Abstract Background and aims Some, but not all, prior studies have suggested that patients with chronic liver disease are at increased risk of contracting COVID-19 and developing more severe disease. However, nationwide data are lacking from well-phenotyped cohorts with liver histology and comparisons to matched general population controls. Methods We conducted a nationwide cohort study of all Swedish adults with chronic liver disease (CLD) confirmed by liver biopsy between 1966 and 2017 (n = 42,320), who were alive on February 1, 2020. CLD cases were matched to ≤ 5 population comparators by age, sex, calendar year and county (n = 182,147). Using Cox regression, we estimated multivariable-adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for COVID-19 hospitalization and severe COVID-19 (intensive care admission or death due to COVID-19). Results Between February 1 and July 31, 2020, 161 (0.38%) CLD patients and 435 (0.24%) general population controls were hospitalized with COVID-19 (aHR = 1.36, 95% CI = 1.11–1.66), while 65 (0.15%) CLD patients and 191 (0.10%) controls developed severe COVID-19 (aHR = 1.08, 95% CI = 0.79–1.48). Results were similar in patients with CLD due to alcohol use, nonalcoholic fatty liver disease, viral hepatitis, autoimmune hepatitis, and other etiologies. Among patients with cirrhosis (n = 2549), the aHRs for COVID-19 hospitalization and for severe COVID-19 were 1.08 (95% CI 0.48–2.40) and 1.23 (95% CI = 0.37–4.04), respectively, compared to controls. Moreover, among all patients diagnosed with COVID-19, the presence of underlying CLD was not associated with increased mortality (aHR = 0.85, 95% CI = 0.61–1.19). Conclusions In this nationwide cohort, patients with CLD had a higher risk of hospitalization for COVID-19 compared to the general population, but they did not have an increased risk of developing severe COVID-19.

Abstract Objective: To identify different Candida spp along with antifungal susceptibility pattern and risk factors associated with candidemia. Design, setting, and patients: This retrospective observational study was conducted in a tertiary-care academic hospital in Jaipur, Western India, for 3 years (July 2017–June 2020). Methods: Blood cultures were performed according to standard microbiological methods, and only 1 isolate per patient was included in the study. Isolates of Candida spp were identified using a VITEK-2 automated system and matrix-assisted laser desorption ionization-time of flight mass spectrometry. Antifungal susceptibility tests were performed using the broth microdilution assay according to the Clinical and Laboratory Standards Institute guidelines. Results: Of 3,443 blood cultures received from suspected sepsis cases, candidemia was identified in 95 (2.8%). In addition to Candida tropicalis (n = 36; 38%) and Candida parapsilosis (n = 17; 18%), 10 isolates of Candida auris comprised the fourth most common cause of candidemia. Presence of central venous catheter and diabetes were statistically significant risk factors for development of candidemia by NAC. Resistance to fluconazole was 36%, resistance to voriconazole was 20%, resistance to 5-flucytosine was 4%, and resistance to amphotericin-B was 7%. C. auris isolates were more resistant than other NAC spp. We detected no resistance among the echinocandins. Conclusions: The emergence of highly resistant isolates like C. auris emphasizes the need for constant monitoring of candidemia cases for species identification and routine antifungal susceptibility so that appropriate measures can be taken to reduce the related morbidity and mortality.

Background: Aspirin, when used with concurrent anticoagulation, increases the risk of gastrointestinal bleeding (GIB). Therefore, multisociety guidelines recommend prophylactic proton-pump inhibitors (PPIs) for patients receiving aspirin and anticoagulation. We aimed to determine rates and predictors of adherence to these recommendations. Methods: All adult inpatients discharged from the hospital on aspirin and anticoagulation from July 2009 to June 2014 were retrospectively evaluated for PPI prescription on discharge instructions. We used univariate and multivariate logistic regression to test for predictors of PPI prescription. Results: A total of 2422 patients were discharged on aspirin and anticoagulation; the mean age was 68 years and 53.2% were male; 42.2% were prescribed a PPI at discharge. On univariate analysis, factors associated with discharge PPI prescription included increased age (47.1% versus 37.9%), white race (47.3% versus 37.1–40.2%), higher aspirin dose (55.1% versus 39.4%), being married (46.2% versus 39.4%) and preadmission PPI use (96.6% versus 23.4%). On multivariate analysis, significant predictors of discharge PPI prescription were age 60–69 years [odds ratio (OR) 1.61] and 70–79 years (OR 1.48), and preadmission PPI use (OR 120.03). Lower odds of discharge PPI prescription included Medicaid (OR 0.55) or Medicare (OR 0.71) insurance, Spanish language (OR 0.63), and lower dose aspirin (81 mg) (OR 0.40). Conclusions: A total of 42.2% of patients discharged on aspirin and anticoagulation were prescribed PPIs. Older age and preadmission PPI use were predictive of PPI prescription, while Medicaid/Medicare insurance, Spanish language, and lower dose aspirin decreased the likelihood of discharge PPI prescription. This creates an opportunity to improve primary GIB prevention through quality improvement interventions.

Ebola viruses have been identified as an emerging threat as it causes severe haemorrhagic fever in human with mortality rates ranging from 50 to 90%. In addition to being a global health concern, the virus also is considered a potential biological threat agent. As for now, no licensed vaccine is available for pre or post exposure treatment. Recent epidemic of this disease in South Africa has led to concern towards development of an effective vaccine on a priority basis. This review is an attempt to look upon current progress in the development of Ebola virus vaccines and highlights strategies that have the greatest potential for commercial development.

ABSTRACT BACKGROUND: Insulin resistance and diabetes mellitus are common extrahepatic manifestations of chronic hepatitis C (HCV). Insulin resistance assessed by HOMA-IR is associated with low rates of sustained virological response, especially in HCV genotype 1 positive patients treated with peginterferon/ribavirin. The effect of insulin resistance on sustained virologic response in HCV genotype 3 positive patients who were treated with peginterferon/ribavirin still remains unclear. OBJECTIVE: To evaluate the impact of insulin resistance on sustained virological response in HCV genotype 3 patients treated with peginterferon/ribavirin. METHODS: A retrospective multicenter study was performed to evaluate the impact of insulin resistance on sustained virological response in non-diabetic HCV genotype 3 positive patients treated with peginterferon and ribavirin. A total of 200 HCV genotype 3 positive patients were enrolled in the study. All patients were non-diabetic. Each patient had a HOMA-IR value measured before the initiation of HCV treatment with peginterferon/ribavirin. The treatment duration was at least 24 weeks. The HOMA-IR cut-off was defined in the study as ≥2.5 due to the coefficient of correlation with sustained virological response of 0.202 (P=0.004). RESULTS: Univariate analysis showed that age, aspartate aminotransferase, platelets, stage of fibrosis and HOMA-IR were predictors of sustained virological response. However multivariate analysis showed advanced fibrosis [OR=2.01 (95%CI: 0.986-4.119) P=0.05] and age [OR=1.06 (95%CI: 1.022-1.110) P=0.002] as negative predictors of sustained virological response. CONCLUSION: In this retrospective multicenter study of non-diabetic HCV genotype 3 positive patients, insulin resistance was not associated with the sustained virological response in patients who were treated with peginterferon/ribavirin.