Demographic, biochemical, clinical, and cognitive symptom differences between smokers and non-smokers in Chinese older male patients with chronic schizophrenia
Notice bibliographique
Résumé
BACKGROUND: Several studies have suggested that smoking may impair cognitive function and worsen psychiatric symptoms in people with schizophrenia, but the results have not been consistent. There have been few studies to date that have examined the effects of smoking in older men with chronic schizophrenia. METHODS: The participants in our study consisted of 167 order Chinese males with chronic schizophrenia and 359 normal control subjects. We split them into smoking and non-smoking groups based on whether or not they smoked. Second, we compared their differences in terms of general demographic characteristics (such as age, education, body mass index, age of illness onset, and course of disease), disease information (such as hypertension, diabetes, and hyperlipidemia), lifestyle factors (such as physical exercise and lunch break), blood biochemical indicators (such as albumin, triglyceride, total cholesterol, high-density lipoprotein, low-density lipoprotein and fasting blood glucose), and medication usage (such as clozapine, olanzapine, risperidone, and chlorpromazine). Lastly, a neuropsychological test battery was used to assess their psychiatric and cognitive symptoms, for example, the Montreal Cognitive Assessment (MoCA) was used to assess their overall cognitive functioning. Their depressive symptoms were assessed by the geriatric depression scale (GDS). Activities of daily living (ADL) were used to assess their ability to lead a daily life, while the positive and negative syndrome scales (PANSS) were used to assess their psychiatric symptoms. RESULTS: Smokers who develop schizophrenia at older ages had a higher body mass index than non-smokers. We also found that plasma albumin, triglycerides, low-density lipoprotein, and fasting blood glucose concentrations were significantly higher in smokers. In contrast, smokers with schizophrenia also had lower PANSS total scores, negative symptom scores, and general psychopathology scores. A forward stepwise binary logistics regression analysis demonstrated a significant association between negative symptom scores and smoking status (B = 0.112, p < 0.001, OR = 1.119, 95% confidence interval: 1.059-1.181). Correlation analysis was carried out and it was found that the amount of cigarette consumption per day had a negative correlation with plasma albumin level(r = - 0.290, p = 0.004). However, no such association was found in normal controls. CONCLUSIONS: Elderly Chinese men with schizophrenia have a higher percentage of smokers, and although smoking can reduce their plasma albumin levels, it does contribute to the prevention of negative symptoms.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».