Effectiveness of the Modified WHO Labour Care Guide to Detect Prolonged and Obstructed Labour Among Women Admitted at Eight Publicly Funded, Midwife-Led Community Health Facilities in Rural Mbarara District, Southwestern Uganda: An Ambispective Cohort Study
Notice bibliographique
Résumé
Godfrey R Mugyenyi,1,2 Wilson Tumuhimbise,3 Esther C Atukunda,2,4 Leevan Tibaijuka,1 Joseph Ngonzi,1 Musa Kayondo,1 Micheal Kanyesigye,2 Angella Musimenta,3 Fajardo T Yarine,1 Josaphat K Byamugisha5 1Obstetrics and Gynaecology Department, Mbarara University of Science and Technology, Mbarara, Uganda; 2Support Mom’s Project, Mbarara University of Science and Technology, Mbarara, Uganda; 3Computing and Informatics Department, Mbarara University of Science and Technology, Mbarara, Uganda; 4Pharmacy department, Mbarara University of Science and Technology, Mbarara, Uganda; 5Obstetrics and Gynaecology department, Makerere University College of Health Sciences, Kampala, UgandaCorrespondence: Godfrey R Mugyenyi, Email gmugyenyi@must.ac.ugBackground: Obstructed labour, a sequel of prolonged labour, remains a significant contributor to maternal and perinatal deaths in low resource settings.Objective: We evaluated the modified WHO labour care guide (LCG) in detecting prolonged/obstructed labour compared to the traditional partograph at publicly funded maternity centers in Southwestern Uganda.Methods: LCG was deployed to monitor labour by trained health care providers in 2023. We reviewed all patient labour monitoring records for the first quarter of 2024 (LCG-intervention) and 2023 (partograph-before LCG introduction) from eight randomized maternity centers. Our primary outcome was the proportion of women diagnosed with prolonged and or obstructed labour. Secondary outcomes included: mode of delivery, labour augmentation, stillbirths, maternal deaths, Apgar score, uterine rupture, postpartum haemorrhage and tool completion. Data was collected in REDcap and analyzed using STATA v17; statistical significance was p < 0.05.Results: A total of 991 (49.3%) and 1020 (50.7%) women were monitored using the LCG and partograph, respectively. The mean maternal and gestation ages were similar between the two groups, reported at 25.9 (SD=5.6) years, and 39.4 (SD=1.8) weeks, respectively. Overall, 120 (12.4%) cases of prolonged/obstructed labour were diagnosed (100 for LCG versus 20 for partograph); LCG had six times higher odds of diagnosing prolonged/obstructed labour compared to the partograph (aOR = 5.94;CI 95%3.63– 9.73, P < 0.001). Detection of obstructed labour alone using LCG increased 12-fold compared to the partograph (aOR = 11.74;CI 95%3.55– 38.74, P < 0.001). We observed increased Caesarean section rates (aOR=6.12;CI 95%4.32– 8.67, P < 0.001), augmentation of labour (aOR = 3.11;CI 95%1.81– 5.35, P < 0.001), Apgar Score at 5 minutes (aOR = 2.29;CI 95%1.11– 5.77, P = 0.025) and tool completion rate (aOR = 2.11;CI 95%1.08– 5.44, P < 0.001). We observed no differences in stillbirths, maternal deaths, postpartum haemorrhage and uterine rupture.Conclusion: Our data shows that LCG diagnosed more cases of prolonged and obstructed labour compared to the partograph among women delivering at rural publicly funded midwife-led facilities in Southwestern Uganda. More controlled and powered studies should evaluate the two tools in different facilities and sub-populations.Trial Registration: This trial registration was registered with clinical trials.gov number NCT05979194 on 2023-08-07, and the protocol was published by BMJ open, as 10.1136/bmjopen-2023-079216 on 15 April 2024.21 Trial registration number NCT05979194 clinical trials.gov.Keywords: modified WHO LCG, partograph, effectiveness, labour monitoring, ambispective cohort study, Uganda
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 | 0,003 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| 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 ».