Socioeconomic factors are associated with differences in health outcomes, but their impact on surgical patients is still not well understood, especially in low- and middle-income countries. Social deprivation may affect perioperative outcomes through differences in access to healthcare, burden of comorbidities, timing of care, and hospital resources. However, few studies have evaluated this association in large and diverse surgical populations, and data from Brazil are limited.

This retrospective multicenter cohort study will evaluate the association between socioeconomic deprivation and perioperative outcomes among patients undergoing surgery in Brazil. The study will include patients aged 16 years or older who underwent elective or urgent surgical procedures in participating public and private hospitals between January 1 and December 31, 2024. Patients undergoing ophthalmologic procedures, diagnostic procedures, procedures performed under local anesthesia only, selected transplant procedures, and organ donors after brain death will be excluded.

Socioeconomic deprivation will be assessed using georeferenced area-level indices derived from each patient's residential address, including the Brazilian Deprivation Index, the Social Vulnerability Index, and the Municipal Human Development Index. The researchers will grou patients according to deprivation levels, and analyze the association between deprivation and postoperative outcomes.

The primary outcome will be 30-day in-hospital postoperative mortality. The study will also evaluate demographic, clinical, surgical, and hospital-level factors associated with mortality, including age, sex, ethnicity, American Society of Anesthesiologists physical status classification, surgical urgency, surgical magnitude, surgical specialty, and type of healthcare system. Multivariable logistic regression models will be used to assess whether socioeconomic deprivation is independently associated with postoperative mortality after adjustment for relevant clinical and surgical factors.

The results of this study may improve the understanding of how socioeconomic deprivation influences perioperative risk in Brazil. The findings may help identify vulnerable surgical patients, support risk prediction models that include social determinants of health, and inform strategies to reduce inequities in perioperative care.

Socioeconomic deprivation is a multidimensional determinant of health that may influence perioperative outcomes through several pathways, including differences in baseline health status, burden of comorbidities, access to timely healthcare, perioperative optimization, and hospital-level resources. Although previous studies have suggested an association between social deprivation and worse postoperative outcomes, most available evidence comes from high-income countries or from studies focused on specific surgical populations. Data from low- and middle-income countries, including Brazil, remain limited.

This study is a retrospective, multicenter cohort study designed to assess the association between socioeconomic deprivation and perioperative outcomes among surgical patients treated in Brazilian hospitals. Participating centers will include both public and private hospitals from different regions of the country. The study will use routinely collected institutional data from patients who underwent surgical procedures during the 2024 calendar year. No additional contact, intervention, or change in clinical care will occur as part of the study.

The main exposure of interest is socioeconomic deprivation, assessed through georeferenced area-level indicators based on each patient's residential address. Residential addresses will be geocoded to identify the corresponding census tract or human development unit. Socioeconomic deprivation will then be measured using validated Brazilian indices, including the Brazilian Deprivation Index, the Social Vulnerability Index, and the Municipal Human Development Index. These indices capture different dimensions of socioeconomic context, including income, education, household conditions, urban infrastructure, human capital, and vulnerability related to work and income.

The study database will include demographic, clinical, surgical, and structural variables routinely available in hospital electronic records. These variables include age, sex, ethnicity, American Society of Anesthesiologists physical status classification, educational level, occupation, surgical procedure, surgical urgency, date of surgery, date of hospital discharge or in-hospital death, surgical specialty, surgical magnitude, and type of healthcare system. Surgical procedures will be standardized using Brazilian procedural classification systems (Classificação Brasileira Hierarquizada de Procedimentos Médicos -CBHPM). If a patient undergoes more than one eligible surgical procedure during the study period, only the first procedure will be considered for outcome analysis.

Data will be extracted locally by the information technology teams of participating centers using structured database queries. Identifiable patient information will not be included in the analytical dataset. Residential addresses will be used only for geocoding and linkage to area-level socioeconomic indices. After geospatial processing, the final research dataset will exclude full residential addresses and other direct identifiers. Access to study data will be restricted to authorized members of the research team, and data will be stored in a secure institutional environment.

The primary analysis will evaluate whether higher levels of socioeconomic deprivation are associated with 30-day in-hospital postoperative mortality. Deprivation indices will be analyzed in categories, including quintiles, to assess gradients of risk across socioeconomic strata. Baseline characteristics will be summarized across deprivation groups using appropriate descriptive statistics. Multivariable logistic regression models will be used to estimate the association between socioeconomic deprivation and postoperative mortality after adjustment for relevant demographic, clinical, surgical, and hospital-level factors. Planned covariates include age, sex, ethnicity, ASA physical status, surgical urgency, surgical magnitude, surgical specialty, and healthcare system type.

Model performance will be assessed using calibration and discrimination measures. Calibration will be evaluated using the Hosmer-Lemeshow goodness-of-fit test, and discrimination will be assessed using the area under the receiver operating characteristic curve. Results will be reported as odds ratios with 95% confidence intervals. A significance level of 5% will be used for statistical analyses.

The study also aims to explore whether incorporating socioeconomic deprivation into perioperative risk assessment may improve the identification of vulnerable surgical patients. By evaluating social deprivation alongside established clinical and surgical risk factors, this study may contribute to a better understanding of inequities in perioperative care and support future strategies for risk stratification, resource allocation, and quality improvement in both public and private healthcare settings in Brazil.

Inclusion Criteria:

• Patients aged 16 years or older.
• Patients who underwent an elective or urgent surgical procedure in an operating room at a participating hospital.
• Surgical procedure performed between January 1, 2024, and December 31, 2024.

Exclusion Criteria:

• Patients who underwent ophthalmologic surgery, diagnostic procedures only and procedures performed under local anesthesia only.
• Patients who underwent liver, lung or heart transplantation.
• Patients diagnosed with brain death who were organ donor candidates.

Study participants will be selected from surgical patients treated at participating public and private hospitals in Brazil. The participating centers are Hospital São José in Criciúma, Santa Catarina; Hospital de Clínicas de Porto Alegre and Hospital Nossa Senhora da Conceição in Porto Alegre, Rio Grande do Sul; Hospital São Domingos in São Luís, Maranhão; Hospital Marcelino Champagnat in Curitiba, Paraná; Hospital São Paulo in São Paulo, São Paulo; and Hospital da Universidade Federal da Bahia in Salvador, Bahia.

These hospitals represent different geographic regions of Brazil and include both public and private healthcare settings.

Individual participant data will not be shared. This is a retrospective study using routinely collected hospital data from multiple participating centers, including sensitive clinical information and residential address data used for georeferencing. Although the final analytical dataset will be de-identified, sharing individual-level data could pose confidentiality risks and may not be permitted under local ethics approvals and institutional data governance agreements. Study results will be reported only in aggregate form.