Correlates of Coronavirus Disease 2019 Inpatient Mortality at a Southern California Community Hospital With a Predominantly Hispanic/Latino Adult Population

© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. Financial support. None.BACKGROUND: Studies of inpatient coronavirus disease 2019 (COVID-19) mortality risk factors have mainly used data from academic medical centers or large multihospital databases and have not examined populations with large proportions of Hispanic/Latino patients. In a retrospective cohort study of 4881 consecutive adult COVID-19 hospitalizations at a single community hospital in Los Angeles County with a majority Hispanic/Latino population, we evaluated factors associated with mortality. METHODS: Data on demographic characteristics, comorbidities, laboratory and clinical results, and COVID-19 therapeutics were abstracted from the electronic medical record. Cox proportional hazards regression modeled statistically significant, independently associated predictors of hospital mortality. RESULTS: Age ≥65 years (hazard ratio [HR] = 2.66; 95% confidence interval [CI] = 1.90-3.72), male sex (HR = 1.31; 95% CI = 1.07-1.60), renal disease (HR = 1.52; 95% CI = 1.18-1.95), cardiovascular disease (HR = 1.45; 95% CI = 1.18-1.78), neurological disease (HR = 1.84; 95% CI = 1.41-2.39), D-dimer ≥500 ng/mL (HR = 2.07; 95% CI = 1.43-3.0), and pulse oxygen level <88% (HR = 1.39; 95% CI = 1.13-1.71) were independently associated with increased mortality. Patient household with (1) multiple COVID-19 cases and (2) Asian, Black, or Hispanic compared with White non-Hispanic race/ethnicity were associated with reduced mortality. In hypoxic COVID-19 inpatients, remdesivir, tocilizumab, and convalescent plasma were associated with reduced mortality, and corticosteroid use was associated with increased mortality. CONCLUSIONS: We corroborate several previously identified mortality risk factors and find evidence that the combination of factors associated with mortality differ between populations.Peer reviewe

Unraveling the spectrum of KIT mutations in gastrointestinal stromal tumors: An Indian Tertiary Cancer Center Experience

Background: Primary mutations in the KIT gene are the driving force for gastrointestinal stromal tumors (GIST) tumorigenesis. Predictive role of KIT mutation status aids oncologists in patient management. There is a paucity of comprehensive data on the frequency of mutations in the KIT gene in GIST affecting Indian patients. The aims of this study were to determine the frequency and spectrum of molecular alterations affecting the KIT gene and assess their association with clinicopathologic features in a cohort of patients of GIST. Materials and Methods: Morphological and immunohistochemically confirmed GIST cases (n = 114) accessioned from August 2014-June 2015 were analyzed for mutations in KIT exons 9, 11, 13, and 17 and subjected to Sanger sequencing onto the ABI 3500 Genetic Analyzer. The sequences were analyzed using sequence analysis software: SeqScape® and Chromas Lite. Results: KIT mutations were seen in 70% of cases and the majority of KIT mutations involved exon 11 (57%), followed by exon 9 (10%), exon 13 (3%), and exon 17 (1%). Most common exon 11 mutations were in-frame deletions (61.4%) followed by substitution mutations (19.3%). Exon 9 mutations showed identical duplication of Ala-Tyr at codons 502–503. Simultaneous mutations affecting exon 11 and 13 were discovered. Novel variations, namely, p.Q556E (c.1666C>G), p.Q556dup (c.1666_1668dupCAG), p.K558_V559delinsS (c.1672_1677delAAGGTTinsAGT), p.Y503_F504insTY (c.1509_1510insACCTAT), and p.K642R (c.1925A>G) involving exons 11, 9, and 13, respectively, were observed. Interpretation and Conclusions: First study with complete analysis of all 4 exons of KIT (exons 9, 11, 13, and 17) in Indian GIST patients. Along with well-described KIT mutations, several rare double mutations as well as novel alterations were reported in this series

Risk factors for the development of triple-negative breast cancer versus non-triple-negative breast cancer: a case–control study

Abstract The risk factors for breast cancer have been defined in several studies but there is deficient data for specific subtypes. We report here the pathological characteristics of a breast cancer cohort and risk factors for patients with triple-negative disease. In this case–control study, a prospective breast cancer cohort was evaluated for demographic, reproductive, obesity-related and other risk factors using a validated questionnaire. Tumors were characterized for routine pathological characteristics and immunohistochemical markers of basal-like breast cancer. Patients with triple-negative breast cancer (TNBC) constituted cases and those with non-TNBC were controls. Odds ratios (OR) were calculated for each risk factor and independent associations were tested in an unconditional logistic regression analysis. Between 2011 and 2014, 1146 patients were recruited, of whom 912 [TNBC 266 (29.1%), non-TNBC 646 (70.9%)] with sufficient pathology material were analysed. Reproductive factors of parity, breastfeeding, age-at-menarche, age at first full-term pregnancy and oral contraceptive use were not significantly associated with TNBC. Higher body mass index (BMI > 24.9 vs ≤ 24.9, OR 0.89, 95%CI 0.63–1.24, p = 0.49) was not significantly associated while lesser waist circumference (> 80 cm vs ≤ 80 cm, OR 0.64, 95%CI 0.45–0.9, p = 0.012) and lower waist-to-hip ratio were significantly associated (> 0.85 vs ≤ 0.85, OR 0.72, 95%CI 0.51–1.0, p = 0.056), with TNBC. History of tobacco use was not significantly associated while lower socio-economic status was borderline associated with TNBC (socio-economic category > 5 versus ≤ 5, OR 0.73, 95%CI 0.50–1.06, p = 0.106). No factor was significant after adjustment for covariates. Central obesity seems to be preferentially associated with non-TNBC, and lower socio-economic status with TNBC in India, while most other conventional risk factors of breast cancer show no significant association with TNBC versus non-TNBC

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Fig 2 -

Survey response data from various participating centres depicting the impact of pandemic on routine diagnostics (A)Effect on kits, consumables and manpower (B) Effect on volume of test requisitions (C) Effect on revenue generated from diagnostics (D) Effect on work profile and pay (E) Effect on Turn-around time (TAT) for testing and discontinuation of tests (F) Response for participation in EQAS scheme.</p

Performance of participants who participated in Digi EQAS module for <i>RAS</i> and <i>BRAF</i> mutations.

Performance of participants who participated in Digi EQAS module for RAS and BRAF mutations.</p

Effect of pandemic on number of days required to submit the test results before and during pandemic.

Effect of pandemic on number of days required to submit the test results before and during pandemic.</p

Test schemes covered under MPQAP EQAS program for solid tumors.

Test schemes covered under MPQAP EQAS program for solid tumors.</p