Health Care–Seeking Behaviors, Disease Progression, Medications, Knowledge of, and Attitudes Toward Systemic Lupus Erythematosus in China: Cross-sectional Survey Study
Notice bibliographique
Résumé
BACKGROUND: Systemic lupus erythematosus (SLE) is a systemic autoimmune disease involving multiple organs throughout the body. The health care-seeking behaviors, disease progression of SLE, and patients' knowledge of and attitudes toward SLE have not been characterized in China. OBJECTIVE: The aim of this study was to depict the health care-seeking behaviors, disease progression, and medications in patients with SLE and to examine the factors associated with their disease flares, knowledge, and attitudes toward SLE in China. METHODS: We conducted a cross-sectional survey in 27 provinces in China. Descriptive statistical methods were used to depict the demographic characteristics, health care-seeking behaviors, medications, and health status. Multivariable logistic regression models were used to identify the factors associated with disease flares, medication changes, and attitudes toward SLE. An ordinal regression model was used to examine the factors associated with the knowledge of the treatment guidelines. RESULTS: We recruited 1509 patients with SLE, and 715 had lupus nephritis (LN). Approximately 39.96% (603/1509) of the patients with SLE were primarily diagnosed with LN, and 12.4% (112/906) developed LN (mean time 5.2 years) from non-LN. Patients whose registered permanent residences or workplaces in other cities from the same province and adjacent provinces seeking health care accounted for 66.9% (569/850) and 48.8% (479/981) of the patients with SLE in the provincial capital cities, respectively. Mycophenolate mofetil was the most commonly used immunosuppressive drug in patients without LN (185/794, 23.3%) and patients with LN (307/715, 42.9%). Femoral head necrosis (71/228, 31.1%) and hypertension (99/229, 43.2%) were the most common adverse event (AE) and chronic disease during treatment, respectively. Change of hospitals for medical consultation (odds ratio [OR] 1.90, 95% CI 1.24-2.90) and development of 1 chronic disease (OR 3.60, 95% CI 2.04-6.24) and AE (OR 2.06, 95% CI 1.46-2.92) and more were associated with disease flares. A pregnancy plan (OR 1.58, 95% CI 1.18-2.13) was associated with changes in medication. Only 242 (16.03%) patients with SLE were familiar with the treatment guidelines, and patients with LN tended to be more familiar with the disease (OR 2.20, 95% CI 1.81-2.68). After receiving treatment, 891 (59.04%) patients changed their attitudes toward SLE from fear to acceptance, and patients with college education or higher (OR 2.09, 95% CI 1.10-4.04) were associated with a positive attitude toward SLE. CONCLUSIONS: A large proportion of patients seeking health care in the provincial capital cities of China migrated from other cities. Persistent monitoring of potential AEs and chronic diseases during SLE treatment and managing patients who changed hospitals for medical consultation are essential for controlling disease flares. Patients had insufficient knowledge about SLE treatment guidelines and would benefit from health education to maintain a positive attitude toward SLE.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 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 ».