Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
According to studies in the US and the Netherlands, 33-40% of patients with chronic conditions receive care that does not follow guideline recommendations. These findings have also been demonstrated in the management of COPD. This leads to under- or over-treatment of patients and, in the case of COPD, to exacerbations and hospitalisations. These exacerbations are a significant clinical problem, affecting patient's lung function, quality of life and mortality. They are also a burden on the healthcare system. Technological advances in artificial intelligence offer the opportunity to address these issues in COPD management. In the past year, there have been remarkable innovations in the field of natural language processing, especially through large language models such as GPT-4 from OpenAI and Bard or Gemini from Google. These models offer an opportunity to improve the implementation of evidence-based care in clinical practice.
This study is a prospective, randomised trial that will compare therapy on discharge for patients with COPD. One arm will receive no intervention, while the other arm will receive a treatment recommendation from an LLM. The study will compare the percentage of patients treated according to the guideline.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| No Intervention | No Intervention | This arm will be treated as usual. No intervention will be performed. | |
| LLM Assessement | Active Comparator | During hospital stay and after written informed consent, an LLM is asked to indicate if the treatment the patient receives is guideline-concordant. The information is ascertained by two study physicians (human-in-the-loop) and later provided to the treating physician who can recommend a change in therapy to the patient (outside of the study). |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| LLM | Other | A LLM-based comparison between treatment and guideline. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Adherence to treatment guidelines at the time of hospital discharge | The primary endpoint will assess whether the treatment at the time of discharge is consistent with the guidelines' recommendations. This is a binary outcome measure of yes or no. | From date of admission (which is enrollment) to the date of discharge, assessed up to one month |
| Percentage of patients treated in concordance with treatment guidelines at the time of hospital discharge | This primary endpoint will assess the percentage of guideline-concordant treatments in each study arm. | From date of admission (which is enrollment) to the date of discharge, assessed up to one month |
Not provided
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Matthias Gröschel, MD PhD | Charité | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Charité University | Berlin | State of Berlin | 10117 | Germany |
Access to trial IPD can be requested by qualified researchers engaging in independent scientific research, and will be provided following review and approval of a research proposal and Statistical Analysis Plan (SAP) and execution of a Data Sharing Agreement (DSA).
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D029424 | Pulmonary Disease, Chronic Obstructive |
| ID | Term |
|---|---|
| D008173 | Lung Diseases, Obstructive |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D002908 | Chronic Disease |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| D020969 |
| Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |