Patients scoring above 37 on the Tampa Scale for Kinesiophobia-Heart were classified as having kinesiophobia; those at or below that threshold were classified as not having it. The split was striking. Ninety-five of the 138 patients, or 68.84 percent, met the criteria for kinesiophobia, while 43 did not.

To determine what distinguished the two groups, the researchers applied multivariable logistic regression, a statistical technique that estimates the independent contribution of each candidate factor while adjusting for the others. Six factors emerged as significant. Advanced age carried an odds ratio of 1.127 (P=0.003), meaning each incremental increase in age raised the odds of kinesiophobia.

Lower educational level was protective in the reverse direction, with an odds ratio of 0.246 (P=0.001), indicating that patients with less education faced substantially higher risk. The remaining four factors painted a picture of physical and psychological vulnerability. A higher degree of disability in activities of daily living more than tripled the odds, with an odds ratio of 3.880 (P=0.007).

Lower self-efficacy for cardiac rehabilitation exercise, measured as the patient’s confidence in their ability to carry out the prescribed activity, was associated with an odds ratio of 0.898 (P=0.024), again indicating that weaker confidence meant higher risk. Pain catastrophizing, the tendency to magnify and ruminate over pain, showed an odds ratio of 4.513 (P=0.023), the largest effect in the model. Fear of falling contributed an odds ratio of 1.212 (P=0.004).

With these coefficients in hand, the team constructed a nomogram, a graphical scoring tool that lets clinicians plot a patient’s values for each risk factor on scaled axes, sum the points, and read off an estimated probability of kinesiophobia. The model’s performance was evaluated with standard metrics. Discrimination, the ability to separate patients who develop kinesiophobia from those who do not, was quantified by the area under the receiver operating characteristic curve.

The nomogram achieved an AUC of 0.939, with a 95 percent confidence interval of 0.898 to 0.981, a figure conventionally regarded as excellent. Sensitivity was 93.7 percent and specificity 83.7 percent, meaning the tool rarely missed true cases while keeping false alarms at a moderate level. Calibration, the agreement between predicted probabilities and observed outcomes, was assessed two ways.

The Hosmer-Lemeshow test returned a chi-square statistic of 5.97 with P=0.65, indicating no statistically significant departure from perfect calibration. A bootstrap-corrected calibration plot, which corrects for the optimism that arises when a model is evaluated on the same data used to build it, showed close alignment between predicted and observed probabilities across the risk range. The authors conclude that advanced age, low educational attainment, dependency in activities of daily living, poor self-efficacy for rehabilitation exercise, pain catastrophizing and fear of falling are significant risk factors for kinesiophobia after CABG, and that the nomogram is a reliable and accurate instrument for identifying high-risk patients early.

Several caveats frame these findings. The study was retrospective and conducted at a single center with a modest sample of 138 patients, and the reported performance metrics reflect internal validation rather than testing in an independent external cohort. The case-control design identifies associations, not causal effects, so the risk factors should be read as markers of vulnerability rather than proven causes.

The final, formatted version of the article was still pending publication at the time of this report, with the manuscript received in November 2025 and accepted in October 2026. Even so, the high observed prevalence and the strong discriminatory performance of the model suggest that routine screening for movement fear after bypass surgery, guided by the six identified factors, warrants evaluation in larger and more diverse populations before broader clinical adoption.

Subject of Research: Risk factors for kinesiophobia after coronary artery bypass grafting and a nomogram prediction model

Article Title: Analysis of risk factors for kinesiophobia after coronary artery bypass grafting and construction of a nomogram prediction model

Article References: Guo, L., Li, J., Ye, W., Wei, X., Wu, X., & Wang, X. (2026). Analysis of risk factors for kinesiophobia after coronary artery bypass grafting and construction of a nomogram prediction model. Frontiers in Cardiovascular Medicine, 13, Article 1742685. https://doi.org/10.3389/fcvm.2026.1742685

Image Credits: AI Generated

DOI: 10.3389/fcvm.2026.1742685

Keywords: kinesiophobia, coronary artery bypass grafting, cardiac rehabilitation, nomogram, risk factors, Tampa Scale, pain catastrophizing, fear of falling, self-efficacy, logistic regression, prediction model, cardiovascular medicine