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September 25, 2023European journal of medical researchOpen Access

A clinical prediction model incorporating age, HbA1c, ankle-brachial index, and flow-mediated vasodilatation demonstrated good predictive power for detecting coronary heart disease with an AUC of 0.783.

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Why the study?

A feasible method was needed for early screening and diagnosis of coronary heart disease in middle-aged and elderly people.

Does a clinical prediction model incorporating age, HbA1c, ABI, and FMD accurately detect coronary heart disease in middle-aged and elderly patients?

Population

839 eligible patients with suspected CHD

Comparison

588 patients in derivation set vs 251 in validation set

Design

Single-center retrospective case-control study

Key result

A clinical prediction model incorporating age, HbA1c, ankle-brachial index, and flow-mediated vasodilatation demonstrated good predictive power for detecting coronary heart disease with an AUC of 0.783.

Authors

STShiyi TaoLYLintong YuDYDeshuang Yang

Discussion

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Member takes

Overview

Does not support routine CHD screening; leaves open external validation before clinical use.

Study Design

Type

Case-Control (n=839)

Multicenter

No

Structured PICO

Does a clinical prediction model incorporating age, HbA1c, ABI, and FMD accurately detect coronary heart disease in middle-aged and elderly patients?

P
Population
839 middle-aged and elderly patients (≥45 years) with suspected coronary heart disease were retrospectively evaluated to develop and validate a diagnostic prediction model.
E
Exposure
Clinical prediction model (nomogram) incorporating age, hemoglobin A1c (HbA1c), ankle-brachial index (ABI), and brachial artery flow-mediated vasodilatation (FMD).
O
Outcome
Diagnosis of coronary heart disease (defined as ≥50% stenosis in at least one coronary artery on coronary angiography).surrogate

Limitations

  • Retrospective single-center study with a single population source leading to selection bias
  • Single time-node data modeling cannot avoid the impact of dynamic changes
  • Clinical performance was only evaluated by internal validation
  • Did not assess the impact of the prediction model on patient outcomes

Cite This Study

Tao et al. (2023) conducted a case-control in Coronary heart disease (n=839). Clinical prediction model (age, HbA1c, ABI, FMD) vs. Non-CHD patients was evaluated on Area under the receiver operating characteristic curve (AUC) in the validation set. A clinical prediction model incorporating age, HbA1c, ankle-brachial index, and flow-mediated vasodilatation demonstrated good predictive power for detecting coronary heart disease with an AUC of 0.783.

synapsesocial.com/papers/6a99a835d8169d122295b260https://doi.org/10.1186/s40001-023-01233-0
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