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Record W2977995325 · doi:10.2196/13530

Clinical Impact of a Digital Dose Counter Pressurized Metered-Dose Inhaler on Uncontrolled Asthma: Cross-Sectional, Observational, Surveillance Study

2019· article· en· W2977995325 on OpenAlexvenueno aff
Randeep Guleria, Krishnaprasad Korukonda

Bibliographic record

VenueInteractive Journal of Medical Research · 2019
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAsthmaObservational studyCross-sectional studyInhalerMedical prescriptionClinical trialEmergency medicinePediatricsInternal medicinePharmacology

Abstract

fetched live from OpenAlex

BACKGROUND: In India, control of asthma with persistent symptoms remains a clinical enigma with likely incriminating factors including non- and pseudoadherence to the inhaled corticosteroids and long-acting beta2-agonists. The United States Food and Drug Administration guidance recommends the use of dose counter pressurized metered-dose inhalers (pMDIs) with further mechanisms to track adherence and pseudoadherence in real-world settings. OBJECTIVE: Digital dose counter pMDIs (dpMDIs) offer simplified, reliable tracking of individual "actuated" dosages with "END" display at completion of the labelled therapeutic aerosol spray. The translational impact on symptom persistence with likely unwarranted exposure to the "Step up" strategy is often prevented if not treated, as in the cases of "pseudo" severe asthma. To further assess the real-world acceptance and clinical impact of dpMDIs in bronchial asthma including poorly controlled or uncontrolled bronchial asthma cases, a noninterventional observational study was performed. METHODS: This cross-sectional, retrospective, case cohort, observational study-the Drug Utilization Surveillance-of dpMDIs in bronchial asthma was conducted in September 2016 in an outpatient setting in India. The retrospective analysis was initiated and conducted as per the International Conference on Harmonization Good Clinical Practice principles and Declaration of Helsinki, following approval from the local ethics committee and registration in the Clinical Trial Registry of India. RESULTS: Consecutive cases of moderate-to-severe asthma with poor control (n=4575), diagnosed as per the Global Initiative for Asthma symptom scale at baseline and follow-up, were included. Patients under treatment using dpMDIs were enrolled from 500 centers across India and assessed by respiratory care specialists. Baseline asthma control was assessed as partly controlled (n=4575) or poorly controlled (n=2942). Per protocol analyses showed that asthma was well controlled with dpMDIs at 8 weeks in 92.7% of the cases (2727/2942, P<.001). Adverse events (n=106, 2%) of mild-to-moderate intensity were reported. Nebulization was required in two patients with episodic breathlessness who were discharged with no consequent sequelae. Post hoc analyses for patients with baseline poorly controlled asthma who "switched" exclusively to dpMDI monotherapy or a combination with xanthines or long-acting beta2-agonists showed a "well controlled" asthma status in 85.9% (500/582, P=.04), 95.4% (395/414, P=.048), and 80.3% (106/132, P=.28) of the cases, respectively. The patient acceptability criteria for an "empty" canister was well correlated with the clinical strategy to identify and avoid pseudoadherence in poorly controlled or difficult-to-treat asthma cases, especially in patients who "switched" exclusively to dpMDIs (n=582) and demonstrated responses of "Use till twenty dose display" (65/156, 41.6%), "Use till END display" (83/156, 53.2%), and "Use till LAST spray" (8/156, 5.1%). CONCLUSIONS: dpMDIs offer simple, accurate, and reliable tracking of non- and pseudoadherence while highlighting incremental asthma-control rates in severe and pseudosevere asthma cases before risk assessment for further "add-on" therapy. TRIAL REGISTRATION: Clinical Trials Registry - India CTRI/2018/06/014595; http://www.ctri.nic.in/Clinicaltrials/pmaindet2.php? trialid=24583.

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)0.008
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.148
GPT teacher head0.533
Teacher spread0.386 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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