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.

Translucency of a Dental Porcelain Mixed by Two Ceramic Slurry Methods: A Bayesian Comparison.

Background: The ceramics industry produces porcelain pastes using a controlled ratio of water and porcelain powder. Two methods are used to produce a dental porcelain paste: one-step mixing or incremental mixing. Objective: To evaluate the optical properties of a feldspathic dental ceramic using two different ceramic paste preparation methods using a Bayesian approach. Materials and Methods: Two groups of feldspathic porcelain discs, an incremental mixing group (n = 40) and a one-step mixing group (n = 40), were assessed. Groups were evaluated using spectrophotometry, and the translucency parameter (TP) of each sample was calculated. Surfaces were characterized by AFM and SEM. Statistical analysis was performed using a Bayesian approach. Results: Translucency parameter values of the incremental mixing group ranged from 1.65 to 3.41, while values for the one-step mixing group ranged from 3.62 to 5.74, this difference being statistically significant. The lowest roughness was obtained on the surface of discs in the one-step mixing group. Conclusions: Feldspathic porcelain with lower translucency and higher roughness was obtained using the incremental mixture method.