Hospital-acquired infections surveillance: The machine-learning algorithm mirrors National Healthcare Safety Network definitions.

Background: Surveillance of hospital-acquired infections (HAIs) is the foundation of infection control. Machine learning (ML) has been demonstrated to be a valuable tool for HAI surveillance. We compared manual surveillance with a supervised, semiautomated, ML method, and we explored the types of infection and features of importance depicted by the model.

[Complications during the hospitalization of kidney transplant recipients].

The objective of the study was to identify the complications in patients that have received a renal transplant. A Historical cohort performed in a university hospital from January/2007 through January/2009 with a sample of 179 patients; data collected retrospectively from the medical history of patients and submitted to statistical analyses. Mean age of patients was 43 (SD=13.

Nursing diagnoses among kidney transplant recipients: evidence from clinical practice.

Purpose: Identify the nursing diagnoses applied to kidney transplant recipients at a Brazilian hospital.

Methods: Cross-sectional study with a study sample of 165 patients who underwent transplant from January 2007 through January 2009.

Conclusions: Six nursing diagnoses were most prevalent among kidney transplant recipients in the postoperative period: risk for infection, impaired urinary elimination, ineffective protection, bathing self-care deficit, impaired tissue integrity, and acute pain.

[Reasons that make individuals in a higher education institution to become or not to become smokers].

This is a cross-sectional study that aims to identify reasons that make individuals in a higher education institution to become or not to become smokers. The data were collected in 2009, with specific questionnaires analyzed statistically. The sample was of 426 subjects, of which 21 (5%) smokers, 26 (6.

Prevalence of smoking among employees of a university hospital.

This cross-sectional study aimed to identify the prevalence of smoking among employees of a university hospital in Southern Brazil. Data collection happened in 2008, during the periodic health exam, using a questionnaire, according to the smoking status of the employees. The sample consisted of 1,475 subjects, in which 979 (66.