Cross-sectional study evaluating the effectiveness of the Mozambique–Canada maternal health project abstraction tool for maternal near miss identification in Inhambane province, Mozambique
Notice bibliographique
Résumé
OBJECTIVES: The objectives of this study are to determine whether the additional clinical criteria of the Mozambique maternal near miss abstraction tool enhance the effectiveness of the original WHO abstraction tool in identifying maternal near miss cases and also evaluate the impact of sociodemographic factors on maternal near miss identification. DESIGN: Cross-sectional study. SETTING: Two secondary referral hospitals in Inhambane province, Mozambique from 2021 to 2022. PARTICIPANTS: From August 2021 to February 2022, 2057 women presenting at two hospitals in Inhambane Province, Mozambique, were consecutively enrolled. Eligible participants included women admitted during pregnancy, labour, delivery, or up to 42 days post partum. Selection criteria focused on women experiencing obstetric complications, while those without complications or with incomplete medical records were excluded. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was identifying maternal near miss cases using the original WHO Disease criterion and the additional clinical criteria from the Mozambique-Canada Maternal Health Project abstraction tool. Secondary outcomes included the association between sociodemographic factors and maternal near miss identification. All outcomes were measured as planned in the study protocol. RESULTS: The new Mozambique-Canada abstraction tool identified more maternal near miss cases (28.2% for expanded disease and 21.1% for comorbidities) compared with the original WHO tool (16.2%). Hypertension and anaemia from the newer criteria were strongly associated with the original WHO Disease criterion (p<0.001), with kappa values of 0.58 (95% CI 0.53 to 0.63) and 0.21 (95% CI 0.16 to 0.26), respectively. Distance to health facilities was significantly associated, with women living over 8 km away having higher odds (OR=2.47, 95% CI 1.92 to 3.18, p<0.001). Type of hospital also influenced identification, with lower odds at Vilankulo Rural Hospital for Expanded Disease criterion (OR=0.70, 95% CI 0.57 to 0.87, p=0.001), but higher odds for comorbidities criterion (OR=3.13, 95% CI 2.40 to 4.08, p<0.001). Finally, older age was associated with higher odds of identification under the comorbidities criterion, particularly for women aged 30-39 (OR=3.06, 95% CI 2.15 to 4.36) as well as those 40 years or older (OR=4.73, 95% CI 2.43 to 9.20, p<0.001). CONCLUSIONS: The Mozambique-Canada Maternal Health Project tool enhances maternal near miss identification over the original WHO tool by incorporating expanded clinical criteria, particularly for conditions like hypertension and anaemia. Sociodemographic factors, including healthcare access, hospital type and maternal age, significantly impact near miss detection. These findings support integrating the expanded criteria into the WHO tool for improved identification of maternal near misses in Mozambique and similar low-resource settings. Future research should examine the tool's effectiveness across varied healthcare contexts and populations.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».