Investigating the Success Rate of Vaginal Delivery After Cesarean Section and Its Associated Factors in Afghan Women: Insights from a Maternity Hospital in Kabul
Notice bibliographique
Résumé
Parvin Golzareh,1 Halima Baha,2 Fahima Aram,3 Muhammad Haroon Stanikzai,4 Razia Rabizada,5 Massoma Jafari6 1Department of Advanced Midwifery Skills, School of Midwifery, Kabul University of Medical Sciences “Abu Ali Ibn Sina”, Kabul, Afghanistan; 2Department of Normal Midwifery, School of Midwifery, Kabul University of Medical Sciences “Abu Ali Ibn Sina”, Kabul, Afghanistan; 3Department of Gynecology, School of Midwifery, Kabul University of Medical Sciences “Abu Ali Ibn Sina”, Kabul, Afghanistan; 4Department of Public Health, Faculty of Medicine, Kandahar University, Kandahar, Afghanistan; 5Department of Oral Health, School of Stomatology, Kabul University of Medical Sciences “Abu Ali Ibn Sina”, Kabul, Afghanistan; 6Department of Health Profession Education Research, University of Toronto, Ontario, CanadaCorrespondence: Muhammad Haroon Stanikzai, Department of Public Health, Faculty of Medicine, Kandahar University, District # 10, Kandahar, 3801, Afghanistan, Tel +93704775578, Email haroonstanikzai1@gmail.comBackground: Vaginal Birth After Cesarean delivery (VBAC) is widely regarded as one of the most effective methods to reduce unnecessary Cesarean section and their complications. Despite its proven benefits, data on the success rate of VBAC and the associated factors remain scarce in Afghanistan. This study aimed to address this gap by determining the VBAC success rate and identifying its associated factors in a maternity hospital in Kabul, Afghanistan.Methods: This cross-sectional study was conducted at Malalai Obstetrics and Gynecology Hospital in Kabul, Afghanistan. The study sample included women with a history of previous cesarean section who visited the hospital between March 21 and September 22, 2023. Demographic and clinical information were collected from client files. Descriptive statistics were used to summarize the demographic and clinical characteristics of the study sample. The association between VBAC and various categorical variables were examined using chi-square tests, with a significance level set at p < 0.05. Logistic regression analysis was performed to identify independent predictors of VBAC, with VBAC as the outcome variable and multiple predictors included in the model.Results: Among the 567 women included in the study, 449 (79.2%) had a successful VBAC. Factors associated with successful VBAC and their adjusted odds ratio (95% CI) were lower gestational age: 1.25 (1.05– 1.48), absence of gestational hypertension: 2.71 (1.26– 5.85), cervical dilation of > 4 cm on admission: 2.77 (1.38– 5.55), effacement of ≥ 50% on admission: 2.13 (1.04– 4.35), and absence of fetal distress: 7.35 (4.29– 12.6).Conclusion: The rate of successful VBAC observed in this study is at a high level (79.2%). This study is the first study to determine the VBAC success rate and its associated factors in Afghanistan. Further research is needed to validate these findings and explore additional factors influencing VBAC success.Keywords: vaginal delivery after cesarean, dilatation, effacement, fetal distress, gestational age, Afghanistan
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 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) | 0,002 | 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 ».