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1.
Front Public Health ; 8: 585850, 2020.
Article in English | MEDLINE | ID: mdl-33425835

ABSTRACT

Objectives: The present study is aimed at estimating patient flow dynamic parameters and requirement for hospital beds. Second, the effects of age and gender on parameters were evaluated. Patients and Methods: In this retrospective cohort study, 987 COVID-19 patients were enrolled from SMS Medical College, Jaipur (Rajasthan, India). The survival analysis was carried out from February 29 through May 19, 2020, for two hazards: Hazard 1 was hospital discharge, and Hazard 2 was hospital death. The starting point for survival analysis of the two hazards was considered to be hospital admission. The survival curves were estimated and additional effects of age and gender were evaluated using Cox proportional hazard regression analysis. Results: The Kaplan Meier estimates of lengths of hospital stay (median = 10 days, IQR = 5-15 days) and median survival rate (more than 60 days due to a large amount of censored data) were obtained. The Cox model for Hazard 1 showed no significant effect of age and gender on duration of hospital stay. Similarly, the Cox model 2 showed no significant difference of age and gender on survival rate. The case fatality rate of 8.1%, recovery rate of 78.8%, mortality rate of 0.10 per 100 person-days, and hospital admission rate of 0.35 per 100,000 person-days were estimated. Conclusion: The study estimates hospital bed requirements based on median length of hospital stay and hospital admission rate. Furthermore, the study concludes there are no effects of age and gender on average length of hospital stay and no effects of age and gender on survival time in above-60 age groups.


Subject(s)
COVID-19 , Length of Stay , Models, Statistical , Patient Discharge , Survival Rate , COVID-19/diagnosis , COVID-19/mortality , Decision Making , Female , Hospitalization , Humans , India , Retrospective Studies , Time Factors
2.
Hortic Res ; 3: 16066, 2016.
Article in English | MEDLINE | ID: mdl-28066557

ABSTRACT

Lycopene is a naturally occurring red carotenoid compound that is found in watermelon. Lycopene has antioxidant properties. Lycopene content, sugar content and hollowheart resistance are subject to significant genotype×environment interaction (G×E), which makes breeding for these fruit quality traits difficult. The objectives of this study were to (i) evaluate the influence of years and locations on lycopene content, sugar content and hollowheart resistance for a set of watermelon genotypes, and (ii) identify genotypes with high stability for lycopene, sugar, and hollowheart resistance. A diverse set of 40 genotypes was tested over 3 years and 8 locations across the southern United States in replicated, multi-harvest trials. Lycopene was tested in a subset of 10 genotypes. Data were analyzed using univariate and multivariate stability statistics (BLUP-GGE biplot) using SASGxE and RGxE programs. There were strong effects of environment as well as G×E interaction on watermelon quality traits. On the basis of stability measures, genotypes were classified as stable or unstable for each quality trait. 'Crimson Sweet' is an inbred line with high quality trait performance as well as trait stability. 'Stone Mountain', 'Tom Watson', 'Crimson Sweet' and 'Minilee' were among the best genotypes for lycopene content, sugar content and hollowheart resistance. We developed a stability chart based on marketable yield and average ranking generated from different stability measures for yield attributes and quality traits. The chart will assist in choosing parents for improvement of watermelon cultivars. See http://cuke.hort.ncsu.edu/cucurbit/wmelon/wmelonmain.html.

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