Difficult airway in adult ICU in Quindío: a cross-sectional study

Introduction: The risk of complications and death related to difficult airway (DA) in critically ill patients is higher than in controlled settings such as the operating room. Statistics on DA in intensive care in Colombia are scarce, as are the intervention data and resources available in the units. The main objective was to determine the prevalence and characteristics of anatomical and physiological difficult airway. Methods: An observational, cross-sectional, multicentre study was conducted in adult Intensive Care Units (ICU) in Quindío. Links to two Google® forms were sent to the Coordinating Intensivists, one general and one specific related to DA anatomical factors (Mallampati, obstructive apnoea, stiff cervical spine, obesity, external appearance, Cormack-Lehane > 2, etc.) and physiological (oxygenation disorder, state of collapse, anaemia, etc.). Results: Four units participated, with 62 beds (83.9% of the beds in the department);56 hospitalized patients were found, 38 patients (67.8%) were intubated. Of the patients, 29% had some type of difficult airway. Of the patients with difficult airway, 100% had physiological DA parameters and 27.3% anatomical difficult airway: 18.2% Cormack-Lehane (CL) > 2, and 9.1% subglottic stenosis. Obesity was the best predictor of CL > 2. LR+: 4.5, LR−:. 001. Conclusions: Physiological DA is highly prevalent in the adult ICU, which represents a challenge for the intensivist, and a high risk of complications for patients. In this study, obesity was the main predictor of anatomical DA in critically ill patients. Intensive care units must have sufficient resources and personnel trained in the management of difficult airway. © 2022 Asociación Colombiana de Medicina Crítica y Cuidado lntensivo

COVID-19 mortality in an area of northeast Brazil: epidemiological characteristics and prospective spatiotemporal modelling.

This study aimed to analyse the spatial-temporal distribution of COVID-19 mortality in Sergipe, Northeast, Brazil. It was an ecological study utilising spatiotemporal analysis techniques that included all deaths confirmed by COVID-19 in Sergipe, from 2 April to 14 June 2020. Mortality rates were calculated per 100 000 inhabitants and the temporal trends were analysed using a segmented log-linear model. For spatial analysis, the Kernel estimator was used and the crude mortality rates were smoothed by the empirical Bayesian method. The space-time prospective scan statistics applied the Poisson's probability distribution model. There were 391 COVID-19 registered deaths, with the majority among ⩾60 years old (62%) and males (53%). The most prevalent comorbidities were hypertension (40%), diabetes (31%) and cardiovascular disease (15%). An increasing mortality trend across the state was observed, with a higher increase in the countryside. An active spatiotemporal cluster of mortality comprising the metropolitan area and neighbouring cities was identified. The trend of COVID-19 mortality in Sergipe was increasing and the spatial distribution of deaths was heterogeneous with progression towards the countryside. Therefore, the use of spatial analysis techniques may contribute to surveillance and control of COVID-19 pandemic.

Risk clusters of COVID-19 transmission in northeastern Brazil: prospective space-time modelling.

This study aimed to analyse the trend and spatial-temporal clusters of risk of transmission of COVID-19 in northeastern Brazil. We conducted an ecological study using spatial and temporal trend analysis. All confirmed cases of COVID-19 in the Northeast region of Brazil were included, from 7 March to 22 May 2020. We used the segmented log-linear regression model to assess time trends, and the local empirical Bayesian estimator, the global and local Moran indexes for spatial analysis. The prospective space-time scan statistic was performed using the Poisson probability distribution model. There were 113 951 confirmed cases of COVID-19. The average incidence rate was 199.73 cases/100 000 inhabitants. We observed an increasing trend in the incidence rate in all states. Spatial autocorrelation was reported in metropolitan areas, and 178 municipalities were considered a priority, especially in the states of Ceará and Maranhão. We identified 11 spatiotemporal clusters of COVID-19 cases; the primary cluster included 70 municipalities from Ceará state. COVID-19 epidemic is increasing rapidly throughout the Northeast region of Brazil, with dispersion towards countryside. It was identified high risk clusters for COVID-19, especially in the coastal side.