Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care-An experience from South India.

BACKGROUND: We retrospectively data-mined the case records of Reverse Transcription Polymerase Chain Reaction (RT-PCR) confirmed COVID-19 patients hospitalized to a tertiary care centre to derive mortality predictors and formulate a risk score, for prioritizing admission. METHODS AND FINDINGS: Data on clinical manifestations, comorbidities, vital signs, and basic lab investigations collected as part of routine medical management at admission to a COVID-19 tertiary care centre in Chengalpattu, South India between May and November 2020 were retrospectively analysed to ascertain predictors of mortality in the univariate analysis using their relative difference in distribution among 'survivors' and 'non-survivors'. The regression coefficients of those factors remaining significant in the multivariable logistic regression were utilised for risk score formulation and validated in 1000 bootstrap datasets. Among 746 COVID-19 patients hospitalised [487 "survivors" and 259 "non-survivors" (deaths)], there was a slight male predilection [62.5%, (466/746)], with a higher mortality rate observed among 40-70 years age group [59.1%, (441/746)] and highest among diabetic patients with elevated urea levels [65.4% (68/104)]. The adjusted odds ratios of factors [OR (95% CI)] significant in the multivariable logistic regression were SaO2<95%; 2.96 (1.71-5.18), Urea ≥50 mg/dl: 4.51 (2.59-7.97), Neutrophil-lymphocytic ratio (NLR) >3; 3.01 (1.61-5.83), Age ≥50 years;2.52 (1.45-4.43), Pulse Rate ≥100/min: 2.02 (1.19-3.47) and coexisting Diabetes Mellitus; 1.73 (1.02-2.95) with hypertension and gender not retaining their significance. The individual risk scores for SaO2<95-11, Urea ≥50 mg/dl-15, NLR >3-11, Age ≥50 years-9, Pulse Rate ≥100/min-7 and coexisting diabetes mellitus-6, acronymed collectively as 'OUR-ARDs score' showed that the sum of scores ≥ 25 predicted mortality with a sensitivity-90%, specificity-64% and AUC of 0.85. CONCLUSIONS: The 'OUR ARDs' risk score, derived from easily assessable factors predicting mortality, offered a tangible solution for prioritizing admission to COVID-19 tertiary care centre, that enhanced patient care but without unduly straining the health system.

Reasons for spectacle reassessment in a tertiary eye care centre over a period of six years.

BACKGROUND: To determine the spectacle reassessment rates of dissatisfied patients returning to the optical services department of a tertiary eye centre in India over a period of six years. METHODS: A total of 169,567 spectacles were dispensed from the optical services department between January 2010 and December 2015. The spectacle reassessment forms of dissatisfied patients who returned to the optical services department with their spectacles were analysed. RESULTS: A total of 797 spectacle reassessment forms were analysed. The overall spectacle reassessment rate during the study period was found to be 0.5% (95% CI: 0.467-0.472). The mean age of patients returning back for spectacle reassessment was 48 years (SD 19.9, range 3-97 years). Error in refractive correction measurement was found to be the most common reason for spectacle reassessment (54.7%), followed by dispensing error (21.1%), documentation errors while writing the prescription from the medical records in the tertiary eye care centre (12.7%), transcription error occurring at the optical services department (10.8%) and ocular pathologies (0.8%). No statistically significant difference was observed in the year-wise spectacle reassessment rates during the study period (p = 0.14). CONCLUSIONS: The frequency of spectacle reassessment rate in a tertiary eye care centre was low, with errors in measuring refractive errors contributing the most to the reassessment and reorder of spectacles.