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Record W4402965659 · doi:10.59204/2314-6788.3260

Role of Cyproheptadine as Appetite Stimulant in Cancer Associated Anorexia

2024· article· en· W4402965659 on OpenAlexaboutno aff
Yasser H Hassan, Suzan Alhassanin, Mohamed E Ahmed, Suzy Gohar

Bibliographic record

VenueMenoufia Medical Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsnot available
Fundersnot available
KeywordsAnorexiaMedicineCyproheptadineStimulantAppetiteCancerFenfluramineInternal medicineEndocrinologySerotoninReceptor

Abstract

fetched live from OpenAlex

Objectives: to assess the role of anti-histaminic serotonin antagonist cyproheptadine in treatment of cancer related appetite loss. Background: Patients with cancer often report changes in their appetite. Optimized nutritional intake together with pharmacological factors can be considered to improve food intake. Methods: One hundred thirty-eight patients with anorexia were randomized into two groups. Either to receive nutritional support only (control group) or to receive nutritional support with cyproheptadine. We used Edmonton symptom Assessment system (ESAS) and functional assessment of anorexia/cachexia therapy-anorexia cachexia scale (FAACT-ACS) scores for assessment of appetite and FAACT total scores for assessment of quality of life. Anthropometric measures, hemoglobin level and albumin were obtained at baseline. both the scores and measures were repeated every 3 months. Results: There was significant improvement in both FACCT- ACS and ESAS scores in both drug and control arms compared to baseline. The appetite scores were better in drug arm however, the difference was not statistically significant. The total FACCT quality of life scores were significantly lower than baseline scores in control arm (P value: Conclusion: Both Cyproheptadine with nutritional support improved appetite scores among the studied group of patients, however cyproheptadine helped patients in drug arm to retain body weight, BMI, albumin, and hemoglobin levels throughout the treatment period.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.324
Teacher spread0.310 · 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 teacher head, not a consensus.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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