Evidence map›Paper›PMID 41734238›Full record

ArticlePloS one2026

A two-tiered latent class and spatial analytical approach to identify clusters of neonatal mortality among very low birth weight infants: A population-based cohort study.

Daniela Testoni Costa-Nobre, Adriana Sanudo, Kelsy Nema Areco, Ana Sílvia Scavacini Marinonio, Milton Harumi Miyoshi, Tulio Konstantyner, Carina Nunes Vieira E Oliveira, Rita de Cassia Xavier Balda, Mandira Daripa Kawakami, Paulo Bandiera-Paiva and 6 more

Abstract read
In one paragraph

Article in PloS one, 2026. 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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Daniela Testoni Costa-NobreEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-7629-4904
Adriana SanudoEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-1187-0143
Kelsy Nema ArecoEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-7801-757X
Ana Sílvia Scavacini MarinonioEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-9845-6097
Milton Harumi MiyoshiEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.
Tulio KonstantynerEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-7931-9692
Carina Nunes Vieira E OliveiraEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0009-0003-7086-3696
Rita de Cassia Xavier BaldaEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-7553-466X
Mandira Daripa KawakamiEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-5230-1989
Paulo Bandiera-PaivaEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-9409-3970
Rosa Maria Viera FreitasFundação Sistema Estadual de Análise de Dados (SEADE Foundation), São Paulo, São Paulo, Brazil.
Mônica La Porte TeixeiraFundação Sistema Estadual de Análise de Dados (SEADE Foundation), São Paulo, São Paulo, Brazil.
Bernadette Cunha WaldvogelFundação Sistema Estadual de Análise de Dados (SEADE Foundation), São Paulo, São Paulo, Brazil.
Maria Fernanda de AlmeidaEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-5864-3808
Ruth GuinsburgEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-1967-9861
Carlos Roberto Veiga KifferEscola Paulista de Medicina - Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0003-1122-0693

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify and analyze patterns of neonatal deaths among very low birth weight (VLBW) infants in the most socioeconomically developed state of Brazil, from 2004 to 2020, using a two-tiered probabilistic approach that combines Latent Class Analysis (LCA) and spatial analysis. STUDY

designThis historical population-based cohort study included 137,224 live births with birthweight of 400-1499g to mothers residing in São Paulo State, using linked birth and death certificate data.

resultsAmong 42,230 neonatal deaths, five distinct latent classes were identified: infection-dominant, intrapartum event-dominant, malformation-dominant, respiratory-dominant, and other. Survival analysis showed differences in timing of death across classes, with intrapartum-related deaths concentrated in the first hours of life, and infection-related deaths occurring later. Spatial analysis revealed geographic clustering especially for infection, malformation, and respiratory-related deaths, primarily in southern municipalities of the State.

conclusionThe combined use of LCA and spatial analysis identified distinct patterns of neonatal mortality. LCA differentiated clinically meaningful profiles with specific timing of death, while spatial analysis revealed municipal-level clustering and overlap of these patterns. These findings showed how neonatal mortality is shaped by both diagnostic profiles and territorial context, providing actionable evidence to guide targeted improvements in perinatal and neonatal care to reduce preventable deaths among VLBW infants.

Indexed as

Infant MortalityInfant, Very Low Birth WeightBrazilCluster AnalysisCohort StudiesFemaleHumansInfantInfant, NewbornLatent Class AnalysisMaleSpatial Analysis

Identifiers

PMID41734238
PMCPMC12931791

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.