Clinical characteristics and outcomes of healthcare workers with COVID-19 pre- and postvaccination.

Vaccines are the most effective strategy to control the spread of coronavirus disease-2019 (COVID-19). Data on COVID-19 among healthcare workers (HCW) pre- and postvaccination are limited. This study aims to evaluate the clinical characteristics and outcomes of HCW with COVID-19 pre- and postvaccination. Retrospective cohort study. All HCWs with suspected COVID-19 were included. Demographic data, occupation, symptoms, work in COVID-19 area, and vaccination status were collected. There were 22 267 HCW visits for suspected COVID-19; 7879 (35.4%) tested positive, and 14 388 (64.6%) tested negative. Fever, cough, fatigue, and dyspnea were positive predictors of COVID-19, and sore throat, headache, coryza, work in a COVID-19 area, and COVID-19 vaccination were negative predictors. Of the total number of visits, 41.2% were from vaccinated HCW and 58.8% were from unvaccinated HCW. Among HCWs with COVID-19, 84 (1.1%) required hospitalization, 11 (0.1%) in an intensive care unit (ICU), with three (0.04%) deaths. Six hospitalizations occurred in vaccinated HCWs, being of short duration, with no need for ICU admission and no deaths. SARS-CoV-2 infection prevalence was high among HCW, and vaccinated HCW had fewer hospitalizations, need for ICU, and deaths. Therefore, vaccines may attenuate COVID-19 severity, and efforts must be concentrated to ensure adequate vaccination for HCW.

Development and Validation of a Predictive Model of Success in Bariatric Surgery.

PURPOSE: There are no criteria to establish priority for bariatric surgery candidates in the public health system in several countries. The aim of this study is to identify preoperative characteristics that allow predicting the success after bariatric surgery. MATERIALS AND METHODS: Four hundred and sixty-one patients submitted to Roux-en-Y gastric bypass were included. Success of the surgery was defined as the sum of five outcome variables, assessed at baseline and 12 months after the surgery: excess weight loss, use of continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP) as a treatment for obstructive sleep apnea (OSA), daily number of antidiabetics, daily number of antihypertensive drugs, and all-cause mortality. Partial least squares (PLS) regression and multiple linear regression were performed to identify preoperative predictors. We performed a 90/10 split of the dataset in train and test sets and ran a leave-one-out cross-validation on the train set and the best PLS model was chosen based on goodness-of-fit criteria. RESULTS: The preoperative predictors of success after bariatric surgery included lower age, presence of non-alcoholic fatty liver disease and OSA, more years of CPAP/BiPAP use, negative history of cardiovascular disease, and lower number of antihypertensive drugs. The PLS model displayed a mean absolute percent error of 0.1121 in the test portion of the dataset, leading to accurate predictions of postoperative outcomes. CONCLUSION: This success index allows prioritizing patients with the best indication for the procedure and could be incorporated in the public health system as a support tool in the decision-making process.

Cost-utility Analysis of Opportunistic and Systematic Diabetic Retinopathy Screening Strategies from the Perspective of the Brazilian Public Healthcare System.

OBJECTIVE: To perform a cost-utility analysis of diabetic retinopathy (DR) screening strategies from the perspective of the Brazilian Public Healthcare System. METHODS: A model-based economic evaluation was performed to estimate the incremental costs per quality-adjusted life-year (QALY) gained between three DR screening strategies: (1) the opportunistic ophthalmology referral-based (usual practice), (2) the systematic ophthalmology referral-based, and (3) the systematic teleophthalmology-based. The target population included individuals with type 2 diabetes (T2D) aged 40 years, without retinopathy, followed over a 40-year time horizon. A Markov model was developed with five health states and a 1-year cycle. Model parameters were based on literature and country databases. One-way and probabilistic sensitivity analyses were performed to assess model parameters' uncertainty. WHO willingness-to-pay (WHO-WTP) thresholds were used as reference (i.e. one and three times the Brazilian per capita Gross Domestic Product of R$32747 in 2018). RESULTS: Compared to usual practice, the systematic teleophthalmology-based screening was associated with an incremental cost of R$21445/QALY gained ($9792/QALY gained). The systematic ophthalmology referral-based screening was more expensive (incremental costs = R$4) and less effective (incremental QALY = -0.012) compared to the systematic teleophthalmology-based screening. The probability of systematic teleophthalmology-based screening being cost-effective compared to usual practice was 0.46 and 0.67 at the minimum and the maximum WHO-WTP thresholds, respectively. CONCLUSION: Systematic teleophthalmology-based DR screening for the Brazilian population with T2D would be considered very cost effective compared to the opportunistic ophthalmology referral-based screening according to the WHO-WTP threshold. However, there is still a considerable amount of uncertainty around the results.

Heart Transplantation Cost Composition in Brazil: A Patient-Level Microcosting Analysis and Comparison With International Data.

BACKGROUND: Advanced heart failure (HF) therapies, such as heart transplantation, are resource intensive and costly. In Brazil, only one-fifth of the estimated population need is fulfilled. We examined cost expenditures of heart transplants in a public institution in Brazil. METHODS AND RESULTS: We used microcosting analysis (time-driven activity-based costing) to examine total costs and individual cost components related to the index transplant hospital admission of all consecutive heart transplant recipients at a single center from July 2015 to June 2017. Average total cost for the 27 patients included was US$ 74,341 which exceeds the reimbursement value per patient by 60%. Major cost drivers were hospital structure and personnel, similarly to what is observed in the United States (US) and other developed countries. Total costs for index transplant admission were ∼50% lower than in the US, but approximate to values reported in some European countries. Costs of heart transplantation in Brazil were lower than those reported for developed countries, and higher than national reimbursement values. CONCLUSIONS: Advanced microcosting methodologies represent an important quality contribution to economic studies in health care and may provide insights for transplant-related health care policies in developing countries.

Text mining approach to predict hospital admissions using early medical records from the emergency department.

OBJECTIVE: Emergency department (ED) overcrowding is a serious issue for hospitals. Early information on short-term inward bed demand from patients receiving care at the ED may reduce the overcrowding problem, and optimize the use of hospital resources. In this study, we use text mining methods to process data from early ED patient records using the SOAP framework, and predict future hospitalizations and discharges. DESIGN: We try different approaches for pre-processing of text records and to predict hospitalization. Sets-of-words are obtained via binary representation, term frequency, and term frequency-inverse document frequency. Unigrams, bigrams and trigrams are tested for feature formation. Feature selection is based on χ2 and F-score metrics. In the prediction module, eight text mining methods are tested: Decision Tree, Random Forest, Extremely Randomized Tree, AdaBoost, Logistic Regression, Multinomial Naïve Bayes, Support Vector Machine (Kernel linear) and Nu-Support Vector Machine (Kernel linear). MEASUREMENTS: Prediction performance is evaluated by F1-scores. Precision and Recall values are also informed for all text mining methods tested. RESULTS: Nu-Support Vector Machine was the text mining method with the best overall performance. Its average F1-score in predicting hospitalization was 77.70%, with a standard deviation (SD) of 0.66%. CONCLUSIONS: The method could be used to manage daily routines in EDs such as capacity planning and resource allocation. Text mining could provide valuable information and facilitate decision-making by inward bed management teams.

Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis.

BACKGROUND: Meta-analyses are necessary to synthesize data obtained from primary research, and in many situations reviews of observational studies are the only available alternative. General purpose statistical packages can meta-analyze data, but usually require external macros or coding. Commercial specialist software is available, but may be expensive and focused in a particular type of primary data. Most available softwares have limitations in dealing with descriptive data, and the graphical display of summary statistics such as incidence and prevalence is unsatisfactory. Analyses can be conducted using Microsoft Excel, but there was no previous guide available. FINDINGS: We constructed a step-by-step guide to perform a meta-analysis in a Microsoft Excel spreadsheet, using either fixed-effect or random-effects models. We have also developed a second spreadsheet capable of producing customized forest plots. CONCLUSIONS: It is possible to conduct a meta-analysis using only Microsoft Excel. More important, to our knowledge this is the first description of a method for producing a statistically adequate but graphically appealing forest plot summarizing descriptive data, using widely available software.

Efficacy of isolated home blood pressure monitoring for blood pressure control: randomized controlled trial with ambulatory blood pressure monitoring - MONITOR study.

BACKGROUND: Rates of control of hypertension remain unsatisfactory worldwide and simple methods to encourage patients to adhere to treatments are still necessary. In this randomized controlled trial, we evaluated the efficacy of a protocol of home blood pressure monitoring (HBPM), without medication titration, to improve BP assessed by ambulatory BPM (ABPM). METHODS: Patients with hypertension under drug treatment and with uncontrolled BP at office and by 24-h ABPM were randomly assigned to HBPM or usual care. The treatment was not modified during the trial. Follow-up visits were conducted at 7 and 30 days after randomization, and at 60 days to assess the outcome. Deltas between baseline and final ABPM measurements were calculated for 24-h, nightly and daily ambulatory SBP and DBP. RESULTS: Of 558 patients screened, 136 fulfilled the eligibility criteria and were randomized, and 121 (89%) completed the trial. The between groups deltas (95% confidence interval) of variation of 24 h, nightly and daily SBP were 5.4 (0.9-9.8) (P = 0.018), 10.9 (2.9-18.9) (P = 0.012) and 4.4 mmHg (-0.1 to 8.8) (P = 0.055), respectively; the corresponding deltas for DBP were 4.5 (1.6-7.4) (P = 0.003), 3.4 (0.4-6.3) (P = 0.025) and 5.8 mmHg (2.5-9.0) (P = 0.001), respectively. At the end of the trial, 32.4% of patients of the HBPM groups and 16.2% of the control group had 24-h SBP less than 130/80 mmHg (P = 0.03). CONCLUSION: A protocol of HBPM without medication titration enhances the control of BP assessed by ABPM.

Cardiovascular risk attributable to diabetes in southern Brazil: a population-based cohort study.

OBJECTIVE: To analyze the effect of diabetes on general and cardiovascular disease (CVD) mortality and morbidity in southern Brazil. RESEARCH DESIGN AND METHODS: A population-based cohort study of 1,091 individuals was conducted. Diabetes was ascertained by medical history. The vital status of 982 individuals and the incidence of events were ascertained during another visit and through hospital records, death certificates, and verbal necropsy with relatives. RESULTS: The mean +/- SD age of participants was 43.1 +/- 17 years, and 55.7% were women. The prevalence of diabetes was 4.2%, and the mean follow-up time was 5.3 +/- 0.07 years. Mortality was 36.3% and 6.6% in participants with or without diabetes, respectively; the incidence of CVD was 20.8% and 3.0%, with an adjusted hazard ratio of 4.4 (95% CI 2.4-7.9). Diabetic population-attributable risk (PAR) for CVD mortality was 10.1% and 13.1% for total CVD. CONCLUSIONS: Diabetes is responsible for a large PAR for overall mortality and cardiovascular events in Brazil.