An interventional study of PM HeartIHD prediction in Ischemic Heart Disease, sponsored by Rigshospitalet, Denmark. Recruiting at 1 site in Denmark. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2024-01-22.
Sponsored by Rigshospitalet, Denmark · Not applicable, Interventional, and Other
The PM-Heart algorithm (PMHeartIHD) is an in-house developed software that predict the survival prognosis for the individual patient hospitalized with ischemic heart disease (IHD) after a coronary arteriography has been performed. The software is intended to be used as a clinical decision support system i.e. the calculated survival prognosis is expected to enhance the quality of the treating physician's therapeutic considerations concerning (minor) adjustments to the patients treatment and follow-up - all within the framework of the current medical guidelines. Thus, the algorithm does not "show the physician specifically what to do", but rather ensures a better knowledgebase for the overall interpretation and choice of management of the patient.
To investigate the clinical usefulness of the developed clinical decision support system - the PMHeartIHD algorithm - we wish to investigate whether the clinical use of the algorithm will;
compared to patients who are treated without the attending/treating physician knowing the algorithm's prognosis?
3,639 studies on the registry are indexed under Heart Diseases; 461 are open to participants now.
This study's planned enrollment of 8,000 is above the median of 100 across 1,778 interventional studies indexed under Heart Diseases.
Browse Heart Diseases studies →Rigshospitalet, Denmark is the lead sponsor of 1,017 studies on the registry; 183 are open to participants now.
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Exclusion Criteria:
The one-year mortality prediction, calculated by the PM Heart algorithm, will not be available to the physician.
The one-year mortality prediction, calculated by the PM Heart algorithm, will be available to the physician.
Other: PM HeartIHD prediction
The calculated prediction and the explainability factors will be made available to the physician, which the physician then can decide to take into his/hers evaluation about further treatment.
Number and duration of readmissions within one month after randomization
A composite outcome of a) readmissions within one month, and 2) all-cause mortality within one year - for patients randomized to the study. All the outcomes listed below will be assessed as a comparison between the "intervention group" and the "control group".
Time frame: From randomization to the study and up to 1 year hereafter
Number and cause of death (all-cause mortality) within one year after randomization
A composite outcome of a) readmissions within one month, and 2) all-cause mortality within one year - for patients randomized to the study.
Time frame: From randomization to the study and up to 1 year hereafter
Readmission(s) within 30 days of the randomization
Readmission(s) within 30 days of the randomization. Incl. information on the quantity, duration, cause, outcome etc.
Time frame: Up to 30 days after randomization to the study.
Cardiovascular readmission(s) within 30 days of the randomization
Cardiovascular readmission(s) within 30 days of the randomization. Incl. information on the quantity, duration, cause, outcome etc.
Time frame: Up to 30 days after randomization to the study.
Readmission(s) with acute coronary syndrome
Readmission(s) with acute coronary syndrome. Incl. information on the quantity, duration, cause, outcome etc.
Time frame: From randomization to the study and up to 1 year hereafter
One-year survival
One-year survival
Time frame: From randomization to the study and up to 1 year hereafter
Total number of days the primary hospitalization lasts
Length (i.e. total number of days) of the primary hospitalization (i.e. when the patient is randomized to the study).
Time frame: From randomization to the study and up to 1 year hereafter
Total number of days at the hospital incl. hospitalizations during the first year after inclusion
Total number of days in hospital during the first year after inclusion
Time frame: From randomization to the study and up to 1 year hereafter
Number of hospitalizations the first year
Number of hospitalizations the first year
Time frame: From randomization to the study and up to 1 year hereafter
Number and type of performed cardiac investigations
Number and type of performed cardiac investigations; i.e. TTE, KAG, Heart-CT, Holter/R-tests, ECG, blood samples, etc.
Time frame: From randomization to the study and up to 1 year hereafter
Number of cardiac follow-up consultations at the hospital
Number of cardiac follow-up consultations at the hospital
Time frame: From randomization to the study and up to 1 year hereafter
Number of check-ups for cardiovascular reasons at the general practitioner
Number of check-ups for cardiovascular reasons at the general practitioner.
Time frame: From randomization to the study and up to 1 year hereafter
Number of cardiovascular drugs at discharge
Number of cardiovascular drugs at discharge + after 1 year.
Time frame: From randomization to the study and up to 1 year hereafter
Dosages (DDD) of drugs at discharge
Dosages (DDD) of drugs at discharge + after 1 year.
Time frame: Up to 1 year after randomization to study.
Incidence of a) new ischemic events, b) arrhythmias, c) and/or heart failure
Incidence of a) new ischemic events, b) arrhythmias, c) and/or heart failure
Time frame: Up to 1 year after randomization to study.
Health economic analyses of implementing the algorithm
Health economic analyses: How does implementing the algorithm alter the overall costs and resource spending, incl. e.g. social benefits, compared with standard-of-care. i.e. does knowing a more precise 1-year mortality prediction reduce/increase the resource consumption. Will be based on economic analyses of the costs related to the abovementioned outcome measurements.
Time frame: Up to 1 year after randomization to study.
The algorithm's reception and introduction in clinical use
We wish to investigate how the algorithm is introduced and received in the clinic, both by the medical staff but also the patients. Will be investigated using interviews.
Time frame: Before start of clinical study and up to 1 year after randomization to study.
The usability of the algorithm
The usability of the algorithm i.e. is it easy to use/understand, any praise or criticisms, ideas for new features etc. Will be based on questionaires and feedback from users.
Time frame: Before start of clinical study and up to 1 year after randomization to study.
How, and to what extend, is the algorithm used by the medical staff.
We wish to investigate how, and to what extend, the algorithm is used by the medical staff, e.g. are the medical staff inclined to use the prediction, does it alter their treatment choices etc. Will be based on questionaires, interviews, feedback from users, and assessment of "look-ups".
Time frame: Before start of clinical study and up to 1 year after randomization to study.
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Rigshospitalet, Denmark