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Enregistrement W4416765101 · doi:10.1002/14651858.cd015376.pub2

Interventions for treating urinary incontinence in older women: a network meta-analysis

2025· review· en· W4416765101 sur OpenAlexaff
Giovana Vesentini, Nicole O’Connor, Mélanie Le Berre, Ashraf Nabhan, Adrian Wagg, S Wallace, Chantale Dumoulin

Notice bibliographique

RevueCochrane Database of Systematic Reviews · 2025
Typereview
Langueen
DomaineMedicine
ThématiquePelvic floor disorders treatments
Établissements canadiensUniversity of AlbertaUniversité de Montréal
Organismes subventionnairesnon disponible
Mots-clésUrinary incontinencePsychological interventionRandomized controlled trialMeta-analysisQuality of life (healthcare)Conservative treatmentIntervention (counseling)Clinical trial

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Urinary incontinence is highly prevalent among women 60 years and over, impacting their quality of life. The condition is often overlooked and untreated. Various treatments are available, but their benefits and harms in older women remain uncertain. OBJECTIVES: To compare the benefits and harms of conservative, pharmacological, and surgical treatments for urinary incontinence in terms of 'cure', 'cure or improvement', and serious adverse events (SAEs) in women 60 years and over using network meta-analyses (NMA), and to rank interventions within a single treatment network. SEARCH METHODS: We searched the Cochrane Incontinence Specialized Register, comprising trials from CENTRAL, MEDLINE, MEDLINE In-Process, MEDLINE Epub Ahead of Print, MEDLINE Daily, and two major international clinical trial registries, on 23 March 2025. We handsearched journals, conference proceedings, and reference lists of relevant articles. We placed no limitations on the searches. SELECTION CRITERIA: We included randomized controlled trials (RCTs) that examined the benefits and harms of conservative, pharmacological, and/or surgical treatments in women 60 years and over with urinary incontinence. Our primary outcomes were 'cure' and 'cure or improvement' of urinary incontinence symptoms. Secondary outcomes included the number of women with SAEs. DATA COLLECTION AND ANALYSIS: At least two review authors independently assessed trials for eligibility and risk of bias using Cochrane's risk of bias 2 (RoB 2) tool. A third author resolved any disagreements. We followed the guidance on undertaking NMA in Chapter 11 of the Cochrane Handbook for Systematic Reviews of Interventions. MAIN RESULTS: We included 43 RCTs involving 8506 participants, a mean of 198 per study (range 14 to 1438). Conservative treatments predominated (20/43, 46.5%) in the studies, followed by pharmacological (17/43, 39.5%), surgical (4/43, 9.3%), and mixed (2/43, 4.7%) treatments. The RCTs had variable risks of bias, often presenting 'some concerns' or 'high risk,' with poor reporting on randomization, blinding, and protocol details. Conservative and pharmacological treatments were often at a high risk of bias for all outcomes (cure, cure or improvement, and SAEs). For the 'cure' outcome, we excluded three studies to address network disconnections; hence, comparisons focused on conservative and pharmacological treatments. Results indicated that all treatments might be better than control, with physical therapies - mainly pelvic floor muscle training with or without complementary therapies or education - showing the best performance for 'cure': physical therapies combined with complementary therapies (odds ratio (OR) 17.79, 95% confidence interval (CI) 2.97 to 106.46; 1 study, 71 participants), physical therapies (OR 7.20, 95% CI 2.59 to 20.03; 4 studies, 310 participants), and physical therapies with education (OR 3.25, 95% CI 1.19 to 8.84; 4 studies, 364 participants), with the evidence for all three results being of very low certainty, followed by complementary therapies (OR 4.65, 95% CI 0.74 to 29.37; 1 study, 37 participants; very low-certainty evidence) and education (OR 2.68, 95% CI 0.61 to 11.73; 2 studies, 180 participants; low-certainty evidence). The mean ranks for best treatment, P scores, and surface under the cumulative ranking curve (SUCRA) values demonstrate the superiority of physical therapies, suggesting that the addition of complementary therapies may be the optimal treatment for 'cure' (SUCRA value ranged from 57% to 85% across the three interventions that included physical therapies). However, due to imprecision in effect estimates and sparse data, uncertainty regarding optimal treatment remains (low- to very low-certainty evidence). For 'cure or improvement of urinary incontinence', after adjusting for disconnected networks by excluding three studies, the analysis showed that physical therapies, with or without education, performed best compared with their controls, with very low-certainty evidence for all the following results (physical therapies: OR 3.98, 95% CI 2.02 to 7.82; 3 studies, 197 participants; physical therapies combined with education: OR 3.20, 95% CI 1.45 to 7.02; 3 studies, 236 participants; β3-adrenergic agonists: OR 2.44, 95% CI 1.28 to 4.62; 1 study, 360 participants) followed by education (OR 2.09, 95% CI 1.05 to 4.17; 2 studies, 213 participants) and antimuscarinic drugs (OR 1.90, 95% CI 1.19 to 3.03; 2 studies, 1469 participants). Both physical therapies, with or without an educational intervention, and β3-adrenergic agonists performed the best compared with their controls (physical therapies: SUCRA = 90%; physical therapies combined with education: SUCRA = 77%; β3-adrenergic agonists: SUCRA = 63%). However, the evidence was of very low certainty, suggesting the need for more trials. Notably, there were no SAEs in conservative treatments, and pharmacological treatments reported some. However, no treatment showed significantly less chance of SAEs, with very low-certainty evidence for all the following results (serotonin-noradrenaline uptake inhibitors: OR 0.40, 95% CI 0.10 to 1.59; 1 study, 264 participants; β3-adrenergic agonists: OR 0.61, 95% CI 0.04 to 10.19; 1 study, 404 participants; complementary therapies: OR 0.53, 95% CI 0.00 to 71.04; no direct evidence, 18 participants; antimuscarinic drugs: OR 0.81, 95% CI 0.46 to 1.42; 4 studies, 2731 participants; physical therapies combined with education: OR 0.99, 95% CI 0.10 to 9.80; 3 studies, 130 participants). AUTHORS' CONCLUSIONS: Due to the limited number of trials and generally small sample sizes, the precision of estimates regarding treatment benefits and harms was low. We successfully conducted an NMA, but there was insufficient evidence to support a robust overall analysis. To establish a connected treatment network, we excluded surgical intervention studies. As a result, the analysis focused on conservative and pharmacological treatment comparisons. For the outcome of 'cure', evidence rated as very low to low certainty suggests that physical therapies combined with complementary therapies may be the most effective option, followed by physical therapies alone or combined with education. For 'cure or improvement', both physical therapies (with or without education) and β3-adrenergic agonists showed potential benefits. SAEs were absent for conservative interventions, whereas most of the pharmacological treatment studies reported some. However, there was insufficient evidence to determine whether any treatment reduced the likelihood of SAEs. Overall, the number and quality of studies were insufficient to draw firm conclusions about the most effective treatment for urinary incontinence in older women. To strengthen the evidence base, larger, high-quality trials with clearly defined interventions and consistently reported outcomes are needed.

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)0,028
score de la tête « metaresearch » (Gemma)0,061
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: Méta-analyse
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,028
Score d'incertitude au seuil0,148

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0280,061
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0160,049
Bibliométrie0,0070,006
Études des sciences et des technologies0,0010,001
Communication savante0,0030,002
Science ouverte0,0030,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

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 Opus0,182
Tête enseignante GPT0,437
Écart entre enseignants0,255 · 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'étudeMéta-analyse
Domainenon disponible
GenreSynthèse

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

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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