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Chart review of patients with chronic obstructive pulmonary disease, using medical records and artificial intelligence

Chart review of patients with COPD, using medical records and artificial intelligence

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ISRCTN
Registry ID
ISRCTN32473131
Enrollment
2500000
Registered
2020-01-24
Start date
2019-07-01
Completion date
Unknown
Last updated
2020-02-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Chronic obstructive pulmonary disease Respiratory

Interventions

The study is retrospective, non-interventional. It’s expected to collect data from the last 5 years. The study population comprises patients who were admitted in their respective medical centres invol

Sponsors

SEPAR (Spanish Society Pneumology and Thoracic Surgery)
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Subjects aged = 35 years old, smokers or former smokers of more than 10 pack-years 2. Had a diagnosis of COPD (a post-bronchodilator ratio forced expiratory volume in the first second [FEV1] / forced vital capacity [FVC] < 0.70, and the presence of respiratory symptoms such as cough, sputum, and dyspnoea) 3. Admitted for ‘‘respiratory disease’’ [respiratory infection or pleural effusion (OR) respiratory failure (OR) right/left heart failure (OR) chronic bronchitis (OR) bronchospasms (AND) [historical diagnosis of COPD (OR) a documented FEV1/FVC < 0.70 in the absence of other obstructive diseases, such as asthma or bronchiolitis]

Exclusion criteria

Exclusion criteria: Patients with a specific diagnosis upon admission of pulmonary oedema, pneumonia, radiological infiltration, pulmonary embolism, pneumothorax, rib fractures, aspiration, or any other associated respiratory or of non-respiratory condition, such as major cardiopathy with chronic heart failure, extended neoplasia, liver or kidney failure.

Design outcomes

Primary

MeasureTime frame
Given that this is a Big Data-based study, the potential number of variables that may be included is only limited to the information contained in the EMRs. All mentioned variables will be included if they are found correctly in the text. It is therefore understood that it is impossible to guarantee that all the desired variables will be included in the final study. On the other hand, this technology enables to create new variables, which can neither be described in advance. The following variables will be extracted to meet the objectives of the study: 1. Age 2. Sex 3. Smoking status: current smoker, ex-smoker 3.1. Use of E-cigarettes, iQOS 3.2. Pack-years index 4. History of alcohol and/or drug abuse 5. Exacerbation history: number of exacerbations in the previous 12 months 6. Previous hospital admissions 7. Symptoms on admission: dyspnoea, cough, sputum, chest tightness, or wheezing 8. Clinical phenotypes 8.1. Chronic bronchitis 8.2. Emphysema 8.3. Bronchiectasis 8.4. Asthma-COPD overlap (ACO) 8.5.Frequent exacerbator 9. Pre-existing asthma 10. GOLD stage 11. Airflow obstruction 11.1. FVC 11.2. FEV1 11.3. FEV1/FVC ratio 12. mMRC dyspnea grade, if available 13. COPD Assessment Test 14. Influenza vaccination in the previous year 15. Previous pneumococcal vaccination 16. Previous microbiological isolation in sputum 17. Home oxygen therapy 18. Non-invasive mechanical ventilation (at home) 19. Mechanical ventilation (invasive and/or non-invasive) during hospital stay 20. Medication

Secondary

MeasureTime frame
There are no secondary outcome measures

Countries

Austria, Belgium, France, Germany, Luxembourg, Spain, Switzerland, United Kingdom

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: Feb 4, 2026