Who Uses Osteopathic Manipulative Treatment? A Prospective, Observational Study Conducted by DO-Touch.NET
Notice bibliographique
Résumé
CONTEXT: Information about the characteristics of patients who use osteopathic manipulative treatment (OMT) is limited. OBJECTIVE: To determine the scope of conditions being managed with OMT and describe the characteristics of patients who receive OMT. METHODS: Researchers conducted a longitudinal, observational study on the use and effectiveness of OMT at 17 clinics where clinicians (ie, osteopathic and allopathic physicians and Canadian-trained osteopaths) provided OMT. Adult patients receiving OMT completed questionnaires immediately before, immediately after, and daily for 7 days after treatment. Data collected from patients included demographic information, chief complaint(s) and their severity, and health-related quality of life. Physical examination findings, treatment, and medical diagnosis documentation were extracted from medical records. Census data were used to assess whether patients were representative of the population of the county where the clinic was located. RESULTS: Data were collected from 927 patients at 1924 office visits. A majority of patients were women (690 [75%]), white (854 [96%]), and not Hispanic or Latinx (707 [95%]). The mean (SD) age was 51.9 (15.9) years. When compared with census data, the sample had higher percentages of women, people aged 65 years and older, people who identified as white, people who were high school and college graduates, and people with higher household incomes than that of the county population. The most common chief complaints from patients were pain or discomfort in the lower back (311 [34%]) and neck (277 [30%]), which corresponded with the most common medical diagnoses. Patients reported that OMT, surgery, and medications were the most helpful treatments they had used previously for their chief complaint(s). Before receiving OMT, patients' health-related quality of life was significantly worse (P≤.05) than that of the general US population. CONCLUSIONS: Adult patients receiving OMT are being treated primarily for musculoskeletal pain conditions, are not representative of the population of the county where the clinic was located, and have worse health-related quality of life than that of the general population. Information about the characteristics of patients who use OMT is important for defining osteopathic distinctiveness and identifying potential areas for increasing the use of OMT. (ClinicalTrials.gov number NCT02395965).
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 tête enseignante, 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 ».