The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians · 2026
Understanding stillbirth causes in Brazil using the CODAC classification system.
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Metelus Sherly, Vieira Matias C, Brasileiro Mariana, Griggio Thayna B, Dias Marcos A B, Leite Débora F, Cunha Filho Edson V da, Schreiner Lucas, Ramos José Geraldo L, Haddad Samira M, Osanan Gabriel, Mayrink Jussara, de Jesús Guilherme R, Fernandes Karayna G, Pasupathy Dharmintra, Cecatti José G, Souza Renato T
Аннотация
OBJECTIVE: To evaluate the contribution of the Causes of Death and Associated Condition (CODAC) classification system in reducing the proportion of nonspecific and unspecified causes of stillbirths compared to the ICD-10 system and to assess maternal and pregnancy-related factors associated with stillbirth in Brazil.
METHODS: A retrospective cross-sectional study was conducted in ten tertiary obstetric care facilities in Brazil, including cases of stillbirths 2009 to 2018. Data were obtained from medical records, death certificates, and postmortem investigations. The CODAC system was applied to identify specific causes of death, and maternal and pregnancy characteristics were evaluated to find associations with stillbirth. Agreement between the two systems was assessed using the kappa coefficient, and McNemar's test was used to evaluate differences in the prevalence of unspecified causes.
RESULTS: Of the 3390 initially assessed cases, 2545 were included in the final analysis. The CODAC system reduced the proportion of unspecified stillbirths from 40.79% (ICD-10) to 22.00%. Regional disparities were evident. Cases with unspecified causes (ICD-10 P20/P95) were more prevalent in the northeast (56.4%), whereas other specific ICD-10 causes were predominant in the southeast (47.9%). Maternal conditions such as preeclampsia (24.0% vs. 18.6%, p = 0.004) and placental abruption (20.6% vs. 10.0%, p < 0.001) were significantly associated with cases in which a specific cause of stillbirth was assigned. The agreement between the classification systems was low (kappa = 0.376), and McNemar's test showed a significant difference (p < 0.001).
CONCLUSION: The CODAC improves the understanding of causes of death over the ICD-10 classification system currently used in Brazil. The CODAC was able to decrease the proportion of unexplained cases, which could potentially contribute to better informing maternal and perinatal health policies.
METHODS: A retrospective cross-sectional study was conducted in ten tertiary obstetric care facilities in Brazil, including cases of stillbirths 2009 to 2018. Data were obtained from medical records, death certificates, and postmortem investigations. The CODAC system was applied to identify specific causes of death, and maternal and pregnancy characteristics were evaluated to find associations with stillbirth. Agreement between the two systems was assessed using the kappa coefficient, and McNemar's test was used to evaluate differences in the prevalence of unspecified causes.
RESULTS: Of the 3390 initially assessed cases, 2545 were included in the final analysis. The CODAC system reduced the proportion of unspecified stillbirths from 40.79% (ICD-10) to 22.00%. Regional disparities were evident. Cases with unspecified causes (ICD-10 P20/P95) were more prevalent in the northeast (56.4%), whereas other specific ICD-10 causes were predominant in the southeast (47.9%). Maternal conditions such as preeclampsia (24.0% vs. 18.6%, p = 0.004) and placental abruption (20.6% vs. 10.0%, p < 0.001) were significantly associated with cases in which a specific cause of stillbirth was assigned. The agreement between the classification systems was low (kappa = 0.376), and McNemar's test showed a significant difference (p < 0.001).
CONCLUSION: The CODAC improves the understanding of causes of death over the ICD-10 classification system currently used in Brazil. The CODAC was able to decrease the proportion of unexplained cases, which could potentially contribute to better informing maternal and perinatal health policies.