Mortality after discharge from a public tertiary cardiovascular referral hospital.

It is critically important for stakeholders with distinct foci of attention on healthcare to understand patient evolution in the presence of an established diagnosis or with a suspected diagnosis of various diseases, specially considering death as an outcome. To study the long-term mortality of patients at a cardiovascular referral hospital. Deterministic binding (selection of pairs of registers from the hospital electronic health records and the mortality records of São Paulo state) from 2002 to 2017 was performed. Studied variables were: age, sex, hospital treatment unit where the first visit occurred (Emergency Unit, Outpatient Unit, Hospital Admissions, Diagnostics Services), treatment type, elapsed time between the first visit and death, diagnosis at first and last visits and variables related to death. Statistical Methods: descriptive, survival (with Kaplan-Meier method), correspondence and competitive risks analyses; in case of nonoccurrence of death until the end of 2017, the patients were considered alive. Statistical significance was set at values of P < .05. Median age at the first visit to the Hospital was 51.9 years. Birth locations included 4496 cities, 17.33% in São Paulo, 0.41% in Rio de Janeiro, 0.40% in Osasco, 24.04% in other cities. Sex included females (46.7%), males (44.2%), not defined (6.3%), and other (2.8%). We observed an association between diseases in ICD-10 Chapter 16 (certain conditions originating in the perinatal period) and Chapter 17 (congenital malformations, deformations, and chromosomal abnormalities), both as diagnoses and underlying causes of death, as well as between neoplasms as diagnoses and as the underlying cause of death. In this sample, there was an association between admission diagnoses and underlying causes of death, such as neoplasms, cardiovascular diseases, and congenital heart malformations. Additionally, patients who underwent a cardiac intervention had a smaller less mortality rate than those who were not operated on. There were also differences in cardiovascular mortality between distinct treatment units of the hospital ((Emergency Unit, Outpatient Unit, Hospital Admissions, Diagnostic Services).

Excess mortality in a cohort of Brazilian patients with a median follow-up of 11 years after the first psychiatric hospital admission.

PURPOSE: To estimate the mortality rates of a cohort of Brazilian patients after their first psychiatric admission and determine the possible risk factors associated with excess mortality. METHODS: The study included a cohort of psychiatric patients hospitalised from Jan 1, 2002 to Dec 31, 2007 in the catchment area of Ribeirão Preto, São Paulo state, Brazil. Data were linked to deaths that occurred between Jan 1, 2002 and Dec 31, 2016 from the SEADE Foundation (state data analysis system of São Paulo). The mortality rate (MR), age-sex-standardised mortality ratio (SMR), life expectancy at birth, and years of life lost (YLL) were computed. The factors associated with mortality were analysed by survival analysis using a Cox proportional hazards regression model. RESULTS: Of 4019 patients admitted (54.76% male), 803 died (69.74% male) during the follow-up (median = 11.25 years). Mortality rates were approximately three-fold higher than expected (SMR = 2.90, 95% CI 2.71-3.11). The highest mortality rate was noted in men with alcohol-related disorders (SMR = 5.50, 95% CI 4.87-6.19). Male sex (adjusted hazard ratio (aHR) = 1.62, 95% CI 1.37-1.92), higher age (aHR = 21.47, 95% CI 13.48-34.17), and unemployment (aHR = 1.22, 95% CI 1.05-1.43) significantly increased the mortality risk from all causes. The average YLL was 27.64 years with the highest YLL noted in nonalcohol substance-related disorders (39.22 years). The life expectancy at birth in this cohort was 47.27 years. Unnatural causes of death were associated with nonwhite skin colour and substance-related disorders. CONCLUSION: An excess of mortality and a significant reduction in life expectancy of mentally disordered patients who were first admitted to psychiatric beds was noted, particularly patients admitted for substance-related disorders, which should represent a priority in mental health policies.

Temporal Trend and Risk Factors for Respiratory Distress Syndrome-Associated Neonatal Mortality in Preterm Infants: A Population-Based Study in a Middle-Income Country.

OBJECTIVE: This article aimed to report a temporal series of respiratory distress syndrome (RDS)-associated neonatal mortality rates in preterm live births in São Paulo state, Brazil, and to identify social, maternal, and neonatal characteristics associated with these deaths. STUDY DESIGN: This is a population-based study of all live births with gestational age (GA) between 22 and 36 weeks, birth weight ≥400 g, without congenital anomalies from mothers living in São Paulo state during 2004 to 2015. RDS-associated neonatal mortality was defined as death up to 27 days after birth with ICD-10 codes P22.0 or P28.0. RDS-associated neonatal mortality rate (annual percent change [APC] with 95% confidence intervals [95% CIs]) was analyzed by Prais-Winsten. Kaplan-Meier estimator identified the time after birth that the RDS-associated neonatal death occurred. Poisson's regression model compared social maternal and neonatal characteristics between preterm live births that survived the neonatal period and those with RDS-associated neonatal deaths, with results expressed in incidence rate ratio and 95% CI. RESULTS: A total of 645,276 preterm live births were included in the study, of which 612,110 survived and 11,078 had RDS-associated neonatal deaths. RDS-associated neonatal mortality rate was 17.17 per thousand preterm live births, with a decreasing annual trend (APC: -6.50%; 95% CI: -9.11 to -3.82%). The median time of these deaths was 48 hours after birth. The following risk factors for RDS-associated neonatal death were identified: maternal schooling ≤7 years (1.18; 1.09-1.29), zero to three prenatal care visits (1.25; 1.18-1.32), multiple pregnancy (1.24; 1.16-1.33), vaginal delivery (1.29; 1.22-1.36), GA 22 to 27 weeks (106.35; 98.36-114.98), GA 28 to 31 weeks (20.12; 18.62-21.73), male sex (1.16; 1.10-1.22), and 5-minute Apgar scores of 0 to 3 (6.74; 6.08-7.47) and 4 to 6 (3.97; 3.72-4.23). CONCLUSION: During the study period, RDS-associated neonatal mortality rates showed significant reduction. The relationship between RDS-associated neonatal deaths and social, maternal, and neonatal factors suggests the need for perinatal strategies to reduce prematurity and to improve the initial management of preterm infants. KEY POINTS: · RDS is associated with preterm live births.. · Impact of RDS-associated neonatal mortality in middle-income countries is scarce.. · Qualified perinatal care can reduce RDS-associated neonatal mortality..

Clusters of preterm live births and respiratory distress syndrome-associated neonatal deaths: spatial distribution and cooccurrence patterns.

BACKGROUND: Prematurity and respiratory distress syndrome (RDS) are strongly associated. RDS continues to be an important contributor to neonatal mortality in low- and middle-income countries. This study aimed to identify clusters of preterm live births and RDS-associated neonatal deaths, and their cooccurrence pattern in São Paulo State, Brazil, between 2004 and 2015.  METHODS: Population-based study of all live births with gestational age ≥ 22 weeks, birthweight ≥ 400 g, without congenital anomalies from mothers living in São Paulo State, Brazil, during 2004-2015. RDS-associated neonatal mortality was defined as deaths < 28 days with ICD-10 codes P22.0 or P28.0. RDS-associated neonatal mortality and preterm live births rates per municipality were submitted to first- and second-order spatial analysis before and after smoothing using local Bayes estimates. Spearman test was applied to identify the correlation pattern between both rates. RESULTS: Six hundred forty-five thousand two hundred seventy-six preterm live births and 11,078 RDS-associated neonatal deaths in São Paulo State, Brazil, during the study period were analyzed. After smoothing, a non-random spatial distribution of preterm live births rate (I = 0.78; p = 0.001) and RDS-associated neonatal mortality rate (I = 0.73; p = 0.001) was identified. LISA maps confirmed clusters for both, with a negative correlation (r = -0.24; p = 0.0000). Clusters of high RDS-associated neonatal mortality rates overlapping with clusters of low preterm live births rates were detected. CONCLUSIONS: Asymmetric cluster distribution of preterm live births and RDS-associated neonatal deaths may be helpful to indicate areas for perinatal healthcare improvement.