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Record W2412462720

Endocrine and metabolic characteristics in polycystic ovary syndrome.

2016· article· en· W2412462720 on OpenAlex
Dorte Glintborg

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsIntertek (Canada)
Fundersnot available
KeywordsMedicinePolycystic ovaryAbdominal obesityInsulin resistancehirsutismInternal medicineDyslipidemiaEndocrine systemMetabolic syndromeEndocrinologyAndrogen ExcessAdipokineAdiponectinObesityDiabetes mellitusPhysiologyHormone
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.218
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it