Burden of Pertussis in Individuals with a Diagnosis of Asthma: A Retrospective Database Study in England
Bibliographic record
Abstract
Amit Bhavsar,1 Emmanuel Aris,2 Lauriane Harrington,3 Jason C Simeone,4 Anna Ramond,5 Dimitra Lambrelli,5 Alberto Papi,6 Louis-Philippe Boulet,7 Kinga Meszaros,8 Nicolas Jamet,8 Yan Sergerie,3 Piyali Mukherjee3 1Europe Medical Affairs, GSK, Wavre, Belgium; 2Real-World Analytics, GSK, Wavre, Belgium; 3Global Medical Affairs, GSK, Wavre, Belgium; 4Real-World Evidence, Evidera Inc., Waltham, MA, USA; 5Real-World Evidence, Evidera Ltd, London, UK; 6Respiratory Medicine, University of Ferrara, Ferrara, Italy; 7Department of Medicine, Laval University, Quebec City, Quebec, Canada; 8Value Evidence and Outcomes, GSK, Wavre, BelgiumCorrespondence: Amit Bhavsar Tel +32 10 85 51 11Email amit.b.bhavsar@gsk.comPurpose: The impact of pertussis in individuals with asthma is not fully understood. We estimated the incidence, health care resource utilization (HCRU), and direct medical costs (DMC) of pertussis in patients with asthma.Patients and Methods: In this retrospective cohort study, the incidence rate of pertussis (identified using diagnostic codes) among individuals aged ≥ 50 years with an asthma diagnosis was assessed during 2009– 2018 using Clinical Practice Research Datalink and Hospital Episode Statistics databases. HCRU and DMC were compared – between patients with diagnoses of asthma and pertussis (asthma+/pertussis+) and propensity score-matched patients with a diagnosis of asthma without pertussis (asthma+/pertussis–) – in the months around the pertussis diagnosis (– 6 to +11).Results: Among 687,105 individuals, 346 had a reported pertussis event (incidence rate: 9.6/100,000 person-years of follow-up; 95% confidence interval: 8.6– 10.7). HCRU and DMC were assessed among 314 asthma+/pertussis+ patients and 1256 matched asthma+/pertussis– controls. Baseline HCRU was similar in both cohorts, but increases were observed in the asthma+/pertussis+ cohort from – 6 to – 1 month before to 2– 5 months after diagnosis. Rates of accident and emergency visits, general practitioner (GP)/nurse visits, and GP prescriptions were 4.3-, 3.1-, and 1.3-fold, respectively, in the asthma+/pertussis+ vs asthma+/pertussis– cohorts during the month before diagnosis; GP/nurse visit rates were 2.0- and 1.2-fold during 0– 2 and 2– 5 months after diagnosis, respectively (all p< 0.001). DMC was 1.9- and 1.6-fold during the month before and 2 months from diagnosis, respectively, in the asthma+/pertussis+ vs asthma+/pertussis– cohorts (both p< 0.001). During months – 1 to +11, DMC in the asthma+/pertussis+ cohort was £ 370 higher than in the asthma+/pertussis– controls.Conclusion: A pertussis diagnosis among adults aged ≥ 50 years with asthma resulted in significant increases in HCRU and DMC across several months around diagnosis, suggesting lengthy diagnosis times and highlighting the need for prevention strategies.Keywords: asthma, direct medical costs, health care resource utilization, incidence, pertussis
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".