Lean metabolic syndrome is associated with similar long-term prognosis as metabolic syndrome in overweight/obese patients. Analysis 47,399 Patients from nationwide LIPIDOGRAM 2004–2015 cohort studies
Notice bibliographique
Résumé
Abstract Background Obesity was once though as an indispensable component of metabolic syndrome. Therefore, there a lot of definitions of metabolic syndrome with only few not including obesity as a criterion. The necessity of the obesity criterion in the metabolic health assessment is being questioned, as similar metabolic disturbances can occur in normal weight individuals. This relatively new concept is often referred as lean metabolic syndrome. Data on long term prognosis is scarce. Purpose To evaluate association between metabolic health and long-term prognosis. Methods Lipidogram studies were carried out in Poland in 2004, 2006 and 2015 in the population representative for patients in primary care setting. Patients were recruited in all 16 administrative regions in Poland and physicians were proportionally to the number of inhabitants in a given administrative region. Each patient was given a questionnaire on chronic diseases, treatment and lifestyle. Questionnaire was administered by physician. The diagnosis of metabolic syndrome was based on the presence of at least two of the following: 1) systolic blood pressure (SBP) ≥130 mmHg or diastolic blood pressure (DBP) ≥85 mmHg, 2) triglycerides (TG) >150 mg/dl, 3) high-density lipoprotein cholesterol (HDL-C) <40 mg/dl men and <50 mg/dl in women, 4) total cholesterol (TC) >200 mg/dl, and 5) fasting glucose (FBG) >100 mg/dl. Basing on those criteria and BMI with a cut off value of 25 kg/m2, patients were divided into four categories: healthy slim, metabolically healthy overweight/obese, lean metabolic syndrome and overweight/obese metabolic syndrome. The median follow up was 5570. this analysis data were censored at 3650 days. Results The median age of the study participants was 56.4 years. 7901 (16.7%) fell into category healthy slim, 14607 (30.8%) were classified as metabolically healthy overweight/obese, 3827 (8.1%) fulfilled criteria for lean metabolic syndrome whilst the remaining 21063 (44.4%) patients were diagnosed with overweight/obese metabolic syndrome. There were 4065 deaths during 10 years follow-up. Patients with lean metabolic syndrome had similar risk as patients with overweight/obese metabolic syndrome (HR=1.33, 95% CI: 1.17–1.52, p<0.001 and HR=1.32, 95% CI: 1.20–1.45, p<0.001). Metabolically heathy overweight/obese patients had only slightly higher risk of dying than healthy slim patients but this difference was less pronounced (HR=1.11, 95% CI: 1.08–1.23, p=0.03). Conclusions Lean metabolic syndrome confers similar risk as metabolic syndrome in overweigh/obese patients. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): The present study was funded by an unrestricted educational grant from Valeant. As a supporter of the study, Valeant played no role in the study design, data analysis, data interpretation, or writing of the report. The present study was also supported by Silesian Analytical Laboratories (SLA, Katowice, Poland).
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».