Evidence map›Paper›PMID 41124287›Full record

ArticlePloS one2025

Maternal morbidity profile in hospitalizations in the Unified Health System in São Paulo, Brazil: Analysis using data mining, 2014 to 2019.

Rejane Sobrino Pinheiro, Marcos Augusto Bastos Dias, Luís Guilherme Buteri Alves, Luís Carlos Torres Guillén, Lana Dos Santos Meijinhos, Natália Santana Paiva, Valeria Saraceni, Claudia Medina Coeli, Rosa Maria Soares Madeira Domingues

Abstract read
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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Rejane Sobrino PinheiroUniversidade Federal do Rio de Janeiro, Instituto de Estudos em Saúde Coletiva, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0002-3361-3626
Marcos Augusto Bastos DiasFundação Oswaldo Cruz, Instituto Nacional de Saúde da Mulher, da Criança e do Adolescente Fernandes Figueira, Rio de Janeiro, Brazil.
Luís Guilherme Buteri AlvesUniversidade Federal do Rio de Janeiro, Instituto de Estudos em Saúde Coletiva, Rio de Janeiro, Brazil.
Luís Carlos Torres GuillénSecretaria Municipal de Saúde de Niteroi, Rio de Janeiro, Brazil.
Lana Dos Santos MeijinhosSecretaria Municipal de Saúde do Rio de Janeiro, Rio de Janeiro, Brazil.
Natália Santana PaivaUniversidade Federal do Rio de Janeiro, Instituto de Estudos em Saúde Coletiva, Rio de Janeiro, Brazil.
Valeria SaraceniSecretaria Municipal de Saúde do Rio de Janeiro, Rio de Janeiro, Brazil.
Claudia Medina CoeliUniversidade Federal do Rio de Janeiro, Instituto de Estudos em Saúde Coletiva, Rio de Janeiro, Brazil.
Rosa Maria Soares Madeira DominguesFundação Oswaldo Cruz, Instituto Nacional de Infectologia Evandro Chagas, Rio de Janeiro, Brazil.ORCID https://orcid.org/0000-0001-5722-8127

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Brazil, approximately 80% of births are publicly funded and are registered in the Hospital Information System of the Unified Health System (SIH/SUS). The SIH/SUS has morbidity data, but its use for maternal morbidity surveillance is still limited. The objective of this study was to apply data mining techniques to identify diagnoses registered in the SIH/SUS that alone or together are associated with maternal death. Obstetric hospitalizations at SIH/SUS of women aged 10-49 years from the largest state in Brazil (São Paulo) from 2014 to 2019 were analysed. Diagnoses were classified into 12 groups, adapting the WHO's classification proposal of maternal deaths. Groups of diagnoses that were related to maternal death were identified using association rules with the Apriori algorithm. Of the 2,742,467 hospitalizations, 831 (0.03%) resulted in death. The most frequent diagnoses associated with death, alone or in combination, were non-obstetric complications (62.0%). Pregnancy-specific hypertensive complications (20.1%), pregnancy-related infections (19.9%) and haemorrhages (13.6%) were also present in hospitalizations resulting in death. The risk of death was more significant for non-obstetric complications, unknown causes and external causes, with lifts above 10. The risk of death was at least three times greater for groups of diagnoses related to the most frequent causes of maternal death in the country (complications of hypertension, infections, and haemorrhages). Uncomplicated abortion, gestational diabetes and other causes of non-obstetric hospitalization were only associated with maternal death when together with other diagnoses. The study reinforces the data mining technique as an innovative approach in the study of maternal mortality in the country. The results also reaffirm the importance of hypertensive, haemorrhagic and infectious causes for maternal death and highlight the relevance of non-obstetric causes for the surveillance of maternal morbidity since women with these diagnoses, alone or associated with other complications, had a higher risk of death.

Indexed as

Data MiningHospitalizationPregnancy ComplicationsAdolescentAdultBrazilChildFemaleHumansMaternal MortalityMiddle AgedMorbidityPregnancyYoung Adult

Identifiers

PMID41124287
PMCPMC12543157

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