International virtual confidential reviews of infection-related maternal deaths and near-miss in 11 low- and middle-income countries – case report series and suggested actions
Notice bibliographique
Résumé
BACKGROUND: Obstetric infections are the third most common cause of maternal mortality, with the largest burden in low and middle-income countries (LMICs). We analyzed causes of infection-related maternal deaths and near-miss identified contributing factors and generated suggested actions for quality of care improvement. METHOD: An international, virtual confidential enquiry was conducted for maternal deaths and near-miss cases that occurred in 15 health facilities in 11 LMICs reporting at least one death within the GLOSS study. Facility medical records and local review committee documents containing information on maternal characteristics, timing and chain of events, case management, outcomes, and facility characteristics were summarized into a case report for each woman and reviewed by an international external review committee. Modifiable factors were identified and suggested actions were organized using the three delays framework. RESULTS: Thirteen infection-related maternal deaths and 19 near-miss cases were reviewed in 20 virtual meetings by an international external review committee. Of 151 modifiable factors identified during the review, delays in receiving care contributed to 71/85 modifiable factors in maternal deaths and 55/66 modifiable factors in near-miss cases. Delays in reaching a GLOSS facility contributed to 5/85 and 1/66 modifiable factors for maternal deaths and near-miss cases, respectively. Two modifiable factors in maternal deaths were related to delays in the decision to seek care compared to three modifiable factors in near-miss cases. Suboptimal use of antibiotics, missing microbiological culture and other laboratory results, incorrect working diagnosis, and infrequent monitoring during admission were the main contributors to care delays among both maternal deaths and near-miss cases. Local facility audits were conducted for 2/13 maternal deaths and 0/19 near-miss cases. Based on the review findings, the external review committee recommended actions to improve the prevention and management of maternal infections. CONCLUSION: Prompt recognition and treatment of the infection remain critical addressable gaps in the provision of high-quality care to prevent and manage infection-related severe maternal outcomes in LMICs. Poor uptake of maternal death and near-miss reviews suggests missed learning opportunities by facility teams. Virtual platforms offer a feasible solution to improve routine adoption of confidential maternal death and near-miss reviews locally.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,048 | 0,086 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».