MétaCan
Menu
Back to cohort
Record W4406177558 · doi:10.4081/monaldi.2025.3213

Addressing inhaler technique challenges in cognitively impaired chronic obstructive pulmonary disease patients: the impact of customized training programs

2025· article· en· W4406177558 on OpenAlexaboutno aff
Vaishnavi V Gaonkar, V Shanbhag, Shreya S Kajave, Mahek R Mattikop

Bibliographic record

VenueMonaldi Archives for Chest Disease · 2025
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsnot available
FundersMedical Research Council
KeywordsInhalerCOPDMedicinePulmonary diseasePhysical therapyPulmonary function testingEmergency medicineInternal medicineAsthma

Abstract

fetched live from OpenAlex

Individuals with chronic obstructive pulmonary disease (COPD) and cognitive impairment (CI) often face difficulties accurately administering inhalers, which are essential for managing their respiratory condition. Many elderly individuals make major errors that prevent proper medication administration. Maintaining proper inhaler use skills is critical in controlling COPD. Our goal was to examine and evaluate the inhaler use skills of CI patients with COPD during both the initial evaluation and subsequent appointments. The Respiratory Department of KLEs Dr. Prabhakar Kore Hospital and Medical Research Centre, Nehru Nagar, Belagavi, Karnataka, India, was the site of this prospective interventional study. Based on the Montreal Cognitive Assessment Scale (MoCA), a subset of patients with COPD exhibited mild CI. Patients exhibiting improper inhaler-using skills were detected, corrected, and trained. Inhaler techniques were reassessed immediately and at follow-up visits. The modified Medical Research Council scale score (mMRC), COPD Assessment Test (CAT) score, St. George Respiratory Questionnaire (SGRQ), and pulmonary function tests were reassessed. A total of 56 COPD and CI patients who had made at least one significant mistake when using an inhaler device were added to the study. The mean age was 66.89±9.85 years. When evaluated with MoCA, the mean score was 17.02±3.91. At baseline, the mean number of mistakes was 1.38±0.93, which decreased to 0.54±0.57 after face-to-face demonstration of correct inhaler techniques. Correlational analysis revealed MoCA scores were negatively associated with the number of mistakes (r=-0.344). At follow-up, the CAT score (25±5.61 vs. 18.48±5.24 p=0.001), SGRQ score (53.82±20.59 vs. 37.61±22.17 p=0.001), mMRC score (3.21±0.76 vs. 3.20±0.75 p=0.001), and forced expiratory volume in 1 second/forced vital capacity score (66.86±9.35 vs. 70.08±9.07 p=0.001) had significantly improved in patients demonstrating the correct technique. Pharmacist-led interventions demonstrated improvements in health-associated quality of life and therapeutic outcomes for individuals with COPD and CI. The study highlighted the importance of cognitive evaluation in routine COPD therapy, identifying potential impediments to effective therapy, and offering face-to-face presentations of inhaler techniques. The best inhalers and methods for COPD patients experiencing CI should be further investigated, according to the study.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.075
GPT teacher head0.330
Teacher spread0.255 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMonaldi Archives for Chest DiseaseSame topicInhalation and Respiratory Drug DeliveryFrench-language works237,207