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Record W2987709089

Lipid profile in schizophrenia: case control study.

2018· article· en· W2987709089 on OpenAlexaboutno aff
Ahmed Mhalla, Walid Bel Hadj Salah, Rim Mensi, Badii Amamou, Amal Messaoud, Leila Gassab, Wahiba Douki, Med Fadhel Najjar, Lotfi Gaha

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsDyslipidemiaSchizophrenia (object-oriented programming)Internal medicineLipid profileContext (archaeology)Positive and Negative Syndrome ScaleMedicineCholesterolDepression (economics)PopulationEndocrinologyGastroenterologyPsychiatryPsychosisBiologyEnvironmental healthObesity
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Cardiovascular diseases are common co morbidities of schizophrenia and constitute the main factors of high mortality in this pathology. Cardiovascular damages are favored by some risk factors, of which one of the most important is dyslipidemia. In this context, a study of lipid profile in schizophrenia is interesting. The aims of this study were to compare the lipid profile of patients with schizophrenia to healthy controls and to investigate the associations between lipid parameters and demographics, clinical and treatment characteristics of the patients. METHODS: We conducted a case-control study between April 2013 and March 2014 on 78 patients with schizophrenia and 68 healthy subjects who benefited from the dosage of four serum lipid parameters: total cholesterol (TC), triglycerides (TG), High-density lipoprotein Cholesterol (HDL-C) and Low-density lipoprotein cholesterol (LDL-C). For the socio-demographic and clinical assessments, we used an information sheet and the following psychometric scales: PANSS (Positive And Negative Syndrome Scale), CGI (Clinical Global Impressions), GAF (Global Assessment Functionning) and the Calgary scale for depression. RESULTS: The comparative study showed that serum concentrations of TC and LDL-C were significantly higher for patients compared to healthy controls respectively with (t=2,83 ; p=0,008) and (t=9,35; p<0,001), the cholesterol ratio (TC / HDL-C) was also significantly higher for patients (t=2,23; p=0,033). The patients had significantly higher prevalence of hypercholesterolemia (OR = 2.96) and low density hyperlipoproteinemia (OR = 18.79). The analytical study in the population of patients showed that the age ≥35 year-old, male gender and alcohol consumption were associated with disturbances in lipid parameters. Cannabis consumption was associated with significantly lower concentrations in TG. Concerning clinical features, paranoid schizophrenia was associated with less dyslipidemia unlike the depressive dimension assessed by the Calgary scale. There was a negative correlation between plasmatic TG concentrations and doses of antipsychotics. CONCLUSION: The vast majority of the literature confirms that patients with schizophrenia are at greater risk of dyslipidemia. This high risk appears to be more important with the consumption of alcohol and tobacco. It seems also that age and masculine gender are dyslipidemia risk factors for schizophrenic patients. The paranoid type of schizophrenia and positive symptoms seem to be associated with less dyslipidemia while depressive symptoms worsen lipid parameters. It then follows that, clinical and regular monitoring of lipid profile, lifestyle recommendations (smoking cessation, exercise and balanced diet) and appropriate therapeutic choices could help reduce morbidity and mortality among patients with schizophrenia. A special focus should be accorded to patients with high negative and depression symptoms.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.284
Teacher spread0.256 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2018
Admission routes1
Has abstractyes

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