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Evaluating the Effectiveness of the Mozambique-Canada Maternal Health Abstraction Tool (MCMH Tool) in the Identification of Maternal Near Miss (MNM) Events

2023· dissertation· en· W7000347925 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Langueen
DomaineMedicine
ThématiqueMaternal and fetal healthcare
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIdentification (biology)YardstickNear missAbstractionMaternal morbidityMaternal death
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background: Maternal morbidity and mortality has long been of great developmental concern globally. In 2005, the WHO defined Maternal Near-Miss (MNM) as a woman who nearly dies from obstetrical complications during pregnancy or up to 42 days after birth but survives the event. It also developed an abstraction tool that identifies these events. The tool is divided into 3 criteria (Disease, Intervention, and Organ-dysfunction criteria). Earlier studies suggested that the Organ-dysfunction criterion was the best yardstick for identifying MNMs. However, growing research shows that this criterion is not as effective within LMICs due to the lack of necessary laboratory capacity and skilled personnel to diagnose organ system failures. Instead, countries are increasingly relying on the disease-based criterion and have adapted the original WHO tool to suit their local needs. The Mozambique-Canada Maternal Health Project near-miss abstraction tool (MCMH near-miss tool) was tailored for the local resource availability in Mozambique as part of a wider initiative aimed at reducing maternal and neonatal morbidity. The tool contains all three (3) criteria of the WHO tool in addition to two (2) additional clinical criteria, namely, “Expanded Disease” and “Co-morbidities”. It also contains important socio-demographic indicators concerning MNM patients. It is important to examine if the added clinical criteria improve the ability of the original disease criterion to identify MNMs. \nPurpose: The purpose of this study was to determine how the additional clinical criteria, namely, the “Expanded Disease” and “Co-morbidities” criteria of the MCMH abstraction tool improve the capacity of the Original WHO Disease criterion in the identification of MNM cases in the Inhambane province of Mozambique. It also aimed to examine how specific health system, geographic, and socio-demographic factors influence the identification of MNMs in Inhambane, Mozambique.\nMethods: The study utilized data obtained from the MNM 1.0 study, which was conducted across two (2) hospitals in the Inhambane province in Mozambique between August 2021 and February 2022 by researchers in the Mozambique-Canada Maternal Health Project. Approximately 2057 respondent samples were analyzed for this study. To estimate the association between the additional clinical criteria and the original disease criterion, both chi-square test of independence and kappa estimates were performed. Furthermore, multivariable logistic regression was performed to determine the \nassociation between various socio-demographic factors and the identification of MNMs based on all 3 clinical criteria.\nResults: Generally, the additional clinical criteria identified more MNMs than the original WHO Disease group. There were stronger associations between the Expanded Disease criterion markers and the WHO disease category. Out of this, hypertension was the most strongly associated and was the only marker with a moderate level of agreement with the original disease group. Contrastingly, the Co-morbidities group showed weak or no associations with the original disease group. Of note, HIV/AIDs had no significant overlap with the original WHO Disease criterion although it contributed the most to the Co-morbidities category. Concerning the socio-demographic indicators, distance from the health facility was consistently associated with MNMs regardless of the clinical criterion. Other factors like education, age, and type of hospital showed varying levels of association with MNMs depending on the clinical criterion. No associations were observed between MNMs and profession or religion. \nConclusion: In conclusion, the Expanded Disease criterion can be a useful category in expanding the ability of the original WHO Disease criterion to identify MNMs. Additionally, the study provides evidence that factors such as distance from the hospital, type of hospital, and age, could be strong predictors for recognizing MNMs especially in rural areas. Overall, this study provides information to help assess the effectiveness of MCMH near-miss tool within the Inhambane province of Mozambique. Further research is however needed to understand its usefulness across different provinces throughout Mozambique.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,030
score de la tête « metaresearch » (Gemma)0,090
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,665
Score d'incertitude au seuil0,675

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0300,090
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0020,002
Études des sciences et des technologies0,0020,001
Communication savante0,0020,001
Science ouverte0,0020,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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.

Tête enseignante Opus0,018
Tête enseignante GPT0,258
Écart entre enseignants0,240 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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