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Record W4411750677 · doi:10.63050/jpps.22.02.339

PATTERN OF PSYCHIATRIC DISORDERS AT HIGH ALTITUDE: A CROSS-SECTIONAL STUDY FROM SKARDU, PAKISTAN

2025· article· en· W4411750677 on OpenAlexaff
Mustajab Alam, Muhammad Shahnawaz Adil, Qasim Zia, Syed Noman Uddin

Bibliographic record

VenueJournal of Pakistan Psychiatric Society · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsBombardier (Canada)
Fundersnot available
KeywordsCross-sectional studyAltitude (triangle)PsychiatryMedicinePsychologyGeographyMathematicsPathology

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the frequency of different psychiatric disorders among patients reporting to psychiatry department and to study their association with age, marital status and education level. STUDY DESIGN: Descriptive cross-sectional study. PLACE AND DURATION OF STUDY: Department of Psychiatry, Combined Military Hospital (CMH) Skardu from September 2021 to February 2022. MATERIALS AND METHODS: A total of one hundred adult individuals, between 21 to 40 years of age, presenting to the Psychiatry department at CMH Skardu, were enrolled in this study after taking written informed consent. All the patients were interviewed by consultant psychiatrist and diagnosis was based on International Classification of Diseases (ICD) version 10. RESULTS: Out of a total of 100 patients, 81 (81%) were married and 19 (19%) were un-married. The mean age of the patients was 26.94 + 4.35 years. The most common psychiatric disorders among patients living at high altitude were depressive episode in 44 patients (44%), followed by adjustment disorders in 30 (30%), anxiety disorder in 12 (12%), dissociative disorder in 9 (9%) and mood disorder in 5 patients (5%). CONCLUSION: Depressive episode and adjustment disorder were the most prevalent psychiatric disorders at high altitude.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.312
Teacher spread0.306 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

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