Development of a machine learning model to estimate length of stay in coronary artery bypass grafting.

Objective: To develop and validate a predictive model utilizing machine-learning techniques for estimating the length of hospital stay among patients who underwent coronary artery bypass grafting.

Methods: Three machine learning models (random forest, extreme gradient boosting and neural networks) and three traditional regression models (Poisson regression, linear regression, negative binomial regression) were trained in a dataset of 9,584 patients who underwent coronary artery bypass grafting between January 2017 and December 2021. The data were collected from hospital discharges from 133 centers in Brazil.

Covid-19 vaccination priorities defined on machine learning.

Objective: Defining priority vaccination groups is a critical factor to reduce mortality rates.

Methods: We sought to identify priority population groups for covid-19 vaccination, based on in-hospital risk of death, by using Extreme Gradient Boosting Machine Learning (ML) algorithm. We performed a retrospective cohort study comprising 49,197 patients (18 years or older), with RT-PCR-confirmed for covid-19, who were hospitalized in any of the 336 Brazilian hospitals considered in this study, from March 19th, 2020, to March 22nd, 2021.

Influence of maternal age and hospital characteristics on the mode of delivery.

Objectives: to analyze the relationship between maternal age and the source of healthcare payment with mode of delivery in public and private national hospitals between the years 2012 to 2017, and the length of hospital stay.

Methods: cross-sectional study of 91,894 women who had children in public and private hospitals between 2012 and 2017. Data were collected from the Diagnosis-Related Groups Brazil system and a comparative analysis was performed between patients in public care and those in supplementary healthcare.

Factors associated with the length of hospital stay of women undergoing cesarean section.

Objective: To evaluate whether age group, complications or comorbidities are associated with the length of hospitalization of women undergoing cesarean section.

Methods: A cross-sectional study was carried out between June 2012 and July 2017, with 64,437 women undergoing cesarean section and who did not acquire conditions during their hospital stay. Hospital discharge data were collected from national health institutions, using the Diagnosis-Related Groups system (DRG Brasil®).

Performance, revision, and extension of the National Nosocomial Infections Surveillance system's risk index in Brazilian hospitals.

Objective: To assess the benefit of using procedure-specific alternative cutoff points for National Nosocomial Infections Surveillance (NNIS) risk index variables and of extending surgical site infection (SSI) risk prediction models with a postdischarge surveillance indicator.

Design: Open, retrospective, validation cohort study.

Setting: Five private, nonuniversity Brazilian hospitals.

Accounting for incomplete postdischarge follow-up during surveillance of surgical site infection by use of the National Nosocomial Infections Surveillance system's risk index.

Objective: We examined the usefulness of a simple method to account for incomplete postdischarge follow-up during surveillance of surgical site infection (SSI) by use of the National Nosocomial Infections Surveillance (NNIS) system's risk index.

Design: Retrospective cohort study that used data prospectively collected from 1993 through 2006.

Setting: Five private, nonuniversity healthcare facilities in Belo Horizonte, Brazil.

Comparison of the risk of surgical site infection after laparoscopic cholecystectomy and open cholecystectomy.

We assessed the independent contributions of the surgical approach and other variables of the National Nosocomial Infections Surveillance System (NNIS) surgical patient component to the surgical site infection risk after cholecystectomy. Laparoscopic cholecystectomy was associated with a lower overall risk of surgical site infection and a lower risk of incisional infection but not a reduced risk of organ-space infection, compared with open cholecystectomy. The contribution of most of the variables of the NNIS surgical patient component to the risk of surgical site infection depended on the depth of the infection.

Factors influencing the risk of surgical site infection following diagnostic exploration of the abdominal cavity.

Objectives: We assessed the contribution of the surgical approach and the NNIS system's surgical component variables to surgical site infection (SSI) risk after diagnostic exploration of the abdominal cavity.

Methods: Retrospective cohort study with prospective data collection (1993-2006) in five private, non-universitary, secondary or tertiary healthcare facilities. Outcome variable was SSI development within 30 days after surgery.

C-reactive protein-guided approach may shorten length of antimicrobial treatment of culture-proven late-onset sepsis: an intervention study.

Late-onset sepsis (LOS) (i.e., sepsis in a neonate after 72 hours of life) is associated with high mortality and significantly prolonged antibiotic exposure and hospital stay in neonates admitted to intensive care units (ICU).

A 10-year prospective surveillance of nosocomial infections in neonatal intensive care units.

Background: We report on nosocomial infections (NIs), causative organisms, and antimicrobial susceptibility patterns in neonates who were admitted to neonatal intensive care units (NICUs), and assess the performance of birth weight (BW) as a variable for risk-stratified NI rate reporting.

Methods: A prospective, 10-year follow-up, open cohort study that involved six Brazilian NICUs was conducted. The NI incidence rates were calculated using different denominators.

Risk factors for nosocomial infection in a neonatal intensive care unit.

Objective: To determine risk factors for nosocomial infection in a neonatal intensive care unit (NICU).

Design: A prospective, open cohort study.

Setting: A 22-bed NICU.