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Effect of long-term inhaled corticosteroids therapy on cognitive function in patients with bronchial asthma and chronic obstructive pulmonary disease

2024· article· en· W4402088899 on OpenAlexaboutno aff
Suikriti Sharma, Deepika Karki, Kanivi Julitta

Bibliographic record

VenueLung India · 2024
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAsthmaCOPDInhaled corticosteroidsInternal medicineCognitionPulmonary diseasePulmonary function testingCorticosteroidDiseasePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Inhaled corticosteroids (ICS) are prominent therapies for managing both asthma and chronic obstructive pulmonary disease (COPD). It has been noted that cognitive impairment is usually linked to high levels of corticosteroids in the blood. OBJECTIVE: This investigation aims to ascertain how long-term inhaled corticosteroid treatment affects individuals with bronchial asthma and COPD's cognitive performance. METHODOLOGY: A total of 139 inpatients diagnosed with COPD and bronchial asthma were enrolled in the study of which 43 were newly diagnosed (group 1), 34 were taking ICS for 0.5-1 year (group 2) and 62 were on long-term ICS, that is, for >2 years (group 3). Patients with a score of at least 24 were considered to have normal cognitive function as prescribed by the Montreal Cognitive Assessment scale. RESULT: It was observed that 56 patients (90.3%) were on long-term ICS treatment, 25 patients (73.5%) were on intermediate therapy and 27 patients (62.7%) who were newly diagnosed had cognitive impairment. CONCLUSION: In conclusion, the duration of ICS therapy was significantly associated with a decline in cognitive function.

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)0.003
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.241
Teacher spread0.238 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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