Construction and evaluation of nomogram for risk prediction of cognitive impairment in chronic obstructive pulmonary disease comorbidity
Bibliographic record
Abstract
OBJECTIVES: Chronic Obstructive Pulmonary Disease (COPD) remains a serious public health problem globally, and the mortality rate for older COPD patients with cognitive impairment is almost three times that of older patients with cognitive impairment or COPD. The aim of this study was to construct a nomogram prediction model for the risk of comorbid cognitive impairment in COPD patients and to evaluate its clinical application. It helps to detect cognitive impairment in COPD patients at an early stage and give them effective interventions in time, so as to delay the progression of COPD patients and improve their prognosis. METHODS: In this study, patients with COPD hospitalized at the Affiliated Hospital of North China University of Science and Technology were evaluated for cognitive function using the Montreal Cognitive Assessment(MoCA) scale after stabilization of acute exacerbations. Participants were stratified into two groups: a case group (with cognitive impairment) and a control group (without cognitive impairment), based on predefined MoCA cutoff scores(< 26scores). Based on the basic characteristics of the patients and the laboratory indexes after stabilization of acute exacerbations, we conducted statistical analyses, screened out the risk factors and established the Nomogram Prediction Model by using the R software, and finally, we evaluated the clinical value of the model through the calculation of ROC curves for sensitivity, specificity and kappa value. Finally, the sensitivity, specificity and Kappa value were calculated by ROC curve to evaluate the clinical value of the model. RESULTS: After statistical analysis, C-reactive protein (CRP) and homocysteine (Hcy) were found to be the risk factors for combined cognitive impairment in COPD patients, and the Nomogram prediction model was constructed by combining CRP and Hcy and plotted the ROC curve, and it was found that its model finally screened the critical value of the total score of 62.55, and the area under the ROC curve of the model was 0.870, and the sensitivity was 84.7%, and the specificity was 80.4%, indicating that it has a high degree of consistency with the actual results, which indicated that the consistency between the prediction results and the actual results was better, and it had a higher clinical application value. CONCLUSIONS: CRP and Hcy are closely associated with comorbid cognitive impairment in COPD patients after stabilization of acute exacerbations, and increased levels of CRP and Hcy are associated with an increased risk of comorbid cognitive impairment in COPD patients. Combining both CRP and Hcy to create a nomogram model for predicting comorbid cognitive impairment in patients with COPD has good predictive ability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".