Endocrine and metabolic characteristics in polycystic ovary syndrome.
Notice bibliographique
Résumé
Hirsutism affects 5-25% women, and the condition is most often caused by polycystic ovary syndrome (PCOS). The initial evaluation of hirsute patients should include a thorough medical history, clinical evaluation, and standardized blood samples to diagnose the 5% hirsute patients with rare endocrine disorders. The majority of these examinations can be performed by the patient's general practitioner. PCOS is a diagnosis of exclusion and is a multiorgan disease affecting most endocrine organs including ovaries, adrenals, pituitary, fat cells, and endocrine pancreas. The manifestations of PCOS are diverse, and up to 50% patients are normal weight. In most cases, however, the severity of symptoms can be related to abdominal obesity. Increased inflammation in PCOS can be measured as decreased adiponectin levels and increased levels of adipokines, chemokines, and interleukins. In the present thesis the use of these inflammatory markers is reviewed, but more data including hard end points are needed to determine which of these markers that should be introduced to the daily clinic. Abdominal obesity and insulin resistance stimulates ovarian and adrenal androgen production, whereas SHBG levels are decreased. Increased testosterone levels may further increase abdominal obesity and inflammation, therefore describing PCOS as a vicious cycle. Abdominal obesity and increased activation of the inflammatory system is seen in both normal weight and obese PCOS patients leading to an increased risk of dyslipidemia, diabetes, and possibly cardiovascular disease. Patients diagnosed with PCOS therefore should be screened for elements in the metabolic syndrome including weight, waist, blood pressure, HbA1c, and lipid status. Our data supported that prolactin and HbA1c levels could be markers of cardiovascular risk and should be confirmed by prospective studies. PCOS is a life-long condition and treatment modalities involve lifestyle modification, insulin sensitizers such as metformin, or inhibition of testosterone levels with OCP. Treatment with pioglitazone supported that increased insulin sensitivity in PCOS is associated with improved inflammatory and cardiovascular risk markers. Our data supported that one year's metformin treatment was associated with a minor but significant weight loss in patients with PCOS irrespective of BMI at study inclusion. Treatment with OCP improved sex-hormone levels, but was associated with minor weight gain. Based on the study results, clinicians should consider the combined treatment with metformin and OCP also in normal weight patients with PCOS. The challenge in the future is to ensure sufficient evaluation and treatment of patients with hirsutism and PCOS and to determine which subgroups of patients should be treated by their general practitioner and which patients should be referred for hospital and/or gynecological evaluation and treatment. Furthermore more data are needed to determine the optimal follow-up program regarding metabolic risk in different subgroups of patients with PCOS.
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 | 0,000 | 0,001 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,005 | 0,001 |
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 ».