The Impact of Multiple Sclerosis on Work Productivity: A Preliminary Look at the North American Registry for Care and Research in Multiple Sclerosis
Notice bibliographique
Résumé
Objective: We aimed to quantify multiple sclerosis (MS)-related work productivity and to illustrate the longitudinal trends for relapses, disease progression, and utilization of health care resources in a nationally representative cohort of working North Americans living with MS. Background: The North American Registry for Care and Research in Multiple Sclerosis (NARCRMS) is a multicentered physician-reported registry which prospectively collects clinical information including imaging data over a long period of time from people with MS from sites across the U.S. and Canada. The Health Economics Outcomes Research (HEOR) Advisory Group has also incorporated Health-Related Productivity and Health Resource Utilization questionnaires, which collect information about health care economics of people with MS and its effects on daily life. Design/Methods: This is a prospective observational study utilizing data from NARCRMS. Socio-demographic, clinical, and health economic outcome data were collected through previously validated and structured questionnaires. Logistic regression was used to calculate the relative odds of symptom impact, with a generalized logit link for number of relapses. Cox proportional hazards regression was used to calculate hazard ratios for time to first relapse. Results: Six hundred and eighty-two (682) people with MS were enrolled in NARCRMS and had completed the HEOR questionnaires at the time of the analysis. Among the participants, 61% were employed full-time and 11% were employed part time. Fatigue was the leading symptom reported to impact both work and household chores. Among the employed participants, 13% reported having missed work with a median of 6.8 (IQR: 3.0–9.0) missed hours due to MS symptoms (absenteeism), while 35% reported MS having impacted their work output (presenteeism). The odds of higher disease severity (EDSS 2.0–6.5 vs. 0.0–1.5) were 2.29 (95% CI = 1.08, 4.88; p = 0.011) times higher for participants who identified reduction of work output. Fatigue was the most identified symptom attributed to work output reduction. Among all participants, 33% reported having missed planned household work with a median of 3.0 (IQR: 2.0–5.0) hours. The odds of higher disease severity were 2.49 (95% CI = 1.37, 4.53; p = 0.006) times higher for participants who identified reduction in household work output, and 1.70 (CI = 1.27, 2.49; p = 0.006) times higher for those whose fatigue affected housework output as compared to other symptoms. Conclusions: A preliminary review of the first 682 patients showed that people with MS had reduced work and housework productivity even at an early disease state. Multiple sclerosis (MS) can significantly impair individuals’ ability to function fully at work and at home, with fatigue overwhelmingly identified as the primary contributing factor. The economic value of finding an effective treatment for MS-related fatigue is substantial, underscoring the importance of these findings for policy development, priority setting, and the strategic allocation of healthcare resources for this chronic and disabling condition.
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 | 0,005 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| 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 ».