Hospital length of stay throughout bed pathways and factors affecting this time: A non-concurrent cohort study of Colombia COVID-19 patients and an unCoVer network project.

Predictions of hospital beds occupancy depends on hospital admission rates and the length of stay (LoS) according to bed type (general ward -GW- and intensive care unit -ICU- beds). The objective of this study was to describe the LoS of COVID-19 hospital patients in Colombia during 2020-2021. Accelerated failure time models were used to estimate the LoS distribution according to each bed type and throughout each bed pathway. Acceleration factors and 95% confidence intervals were calculated to measure the effect on LoS of the outcome, sex, age, admission period during the epidemic (i.e., epidemic waves, peaks or valleys, and before/after vaccination period), and patients geographic origin. Most of the admitted COVID-19 patients occupied just a GW bed. Recovered patients spent more time in the GW and ICU beds than deceased patients. Men had longer LoS than women. In general, the LoS increased with age. Finally, the LoS varied along epidemic waves. It was lower in epidemic valleys than peaks, and decreased after vaccinations began in Colombia. Our study highlights the necessity of analyzing local data on hospital admission rates and LoS to design strategies to prioritize hospital beds resources during the current and future pandemics.

Socioeconomic disparities associated with mortality in patients hospitalized for COVID-19 in Colombia.

Socioeconomic disparities play an important role in the development of severe clinical outcomes including deaths from COVID-19. However, the current scientific evidence in regard the association between measures of poverty and COVID-19 mortality in hospitalized patients is scant. The objective of this study was to investigate whether there is an association between the Colombian Multidimensional Poverty Index (CMPI) and mortality from COVID-19 in hospitalized patients in Colombia from May 1, 2020 to August 15, 2021. This was an ecological study using individual data on hospitalized patients from the National Institute of Health of Colombia (INS), and municipal level data from the High-Cost Account and the National Administrative Department of Statistics. The main outcome variable was mortality due to COVID-19. The main exposure variable was the CMPI that ranges from 0 to 100% and was categorized into five levels: (i) level I (0%-20%), (ii) level II (20%-40%), (iii) level III (40%-60%), (iv) level IV (60%-80%); and (v) level V (80%-100%). The higher the level, the higher the level of multidimensional poverty. A Bayesian multilevel logistic regression model was applied to estimate Odds Ratio (OR) and their corresponding 95% credible intervals (CI). In addition, a subgroup analysis was performed according to the epidemiological COVID-19 waves using the same model. The odds for dying from COVID-19 was 1.46 (95% CI 1.4-1.53) for level II, 1.41 (95% CI 1.33-1.49) for level III and 1.70 (95% CI 1.54-1.89) for level IV hospitalized COVID-19 patients compared with the least poor patients (CMPI level I). In addition, age and male sex also increased mortality in COVID-19 hospitalized patients. Patients between 26 and 50 years-of-age had 4.17-fold increased odds (95% CI 4.07-4.3) of death compared with younger than 26-years-old patients. The corresponding for 51-75 years-old patients and those above the age of 75 years were 9.17 (95% CI 8.93-9.41) and 17.1 (95% CI 16.63-17.56), respectively. Finally, the odds of death from COVID-19 in hospitalized patients gradually decreased as the pandemic evolved. In conclusion, socioeconomic disparities were a major risk factor for mortality in patients hospitalized for COVID-19 in Colombia.

Type 1 and type 2 diabetes mellitus: Clinical outcomes due to COVID-19. Protocol of a systematic literature review.

INTRODUCTION: Diabetes has been associated with an increased risk of complications in patients with COVID-19. Most studies do not differentiate between patients with type 1 and type 2 diabetes, which correspond to two pathophysiological distinct diseases that could represent different degrees of clinical compromise. OBJECTIVE: To identify if there are differences in the clinical outcomes of patients with COVID-19 and diabetes (type 1 and type 2) compared to patients with COVID-19 without diabetes. METHODS: Observational studies of patients with COVID-19 and diabetes (both type 1 and type 2) will be included without restriction of geographic region, gender or age, whose outcome is hospitalization, admission to intensive care unit or mortality compared to patients without diabetes. Two authors will independently perform selection, data extraction, and quality assessment, and a third reviewer will resolve discrepancies. The data will be synthesized regarding the sociodemographic and clinical characteristics of patients with diabetes and without diabetes accompanied by the measure of association for the outcomes. The data will be synthesized regarding the sociodemographic and clinical characteristics of patients with diabetes and without diabetes accompanied by the measure of association for the outcomes. EXPECTED RESULTS: Update the evidence regarding the risk of complications in diabetic patients with COVID-19 and in turn synthesize the information available regarding type 1 and type 2 diabetes mellitus, to provide keys to a better understanding of the pathophysiology of diabetics. SYSTEMATIC REVIEW REGISTRY: This study was registered at the International Prospective Registry for Systematic Reviews (PROSPERO)-CRD42021231942.

A Colombian diabetes risk score for detecting undiagnosed diabetes and impaired glucose regulation.

AIMS: (i) To develop a diabetes mellitus risk score model for the Colombian population (ColDRISC); and (ii) to evaluate the accuracy of the ColDRISC unknown Type 2 diabetes mellitus METHODS: Cross-sectional screening study of the 18-74 years-old population of a health-care insurance company (n=2060) in northern Colombia. Lifestyle habits and risk factors for diabetes mellitus were assessed by an interview using a questionnaire consisting of information regarding sociodemographic factors, history of diabetes mellitus, tobacco consumption, hypertension, nutritional and physical activity habits. Anthropometric measurements and an oral glucose tolerance test were taken. The sensitivity and the specificity, receiver-operating characteristic (ROC) curves, were calculated for the ColDRISC and FINDRISC. RESULTS: The area under the ROC curve for unknown Type 2 diabetes mellitus was 0.74 (95% CI: 0.70-0.79) for the ColDRISC and 0.73 for the FINDRISC (95% confidence intervals [CI] 0.69-0.78). Using the risk score cutoff value of 4 in the ColDRISC to detect Type 2 diabetes mellitus resulted in a sensitivity of 73% and specificity of 67%. CONCLUSIONS: The characteristics of the ColDRISC show that it can be used as a simple, safe, and inexpensive test to identify people at high risk for Type 2 diabetes mellitus in Colombia.