Objective:To develop and validate a risk prediction model for in-stent restenosis (ISR) after percutaneous coronary intervention (PCI).Methods:This prospective study included 126 patients with acute myocardial infarction (AMI) who underwent PCI at Lishui Central Hospital from May 2021 to April 2023. The patients were divided into two groups based on whether they experienced ISR after PCI: ISR group ( n = 33) and non-ISR group ( n = 93). Clinical data were compared between the two groups. Binary logistic regression was used to identify independent risk factors for ISR in patients with AMI after PCI. A risk prediction model was then developed, and the predictive value of the model was assessed using receiver operating characteristic curve analysis. Results:After surgery, significant differences were observed between the ISR and non-ISR groups regarding postoperative smoking [21(63.64%) vs. 27(29.03%)], elevated uric acid level [19 (57.58%) vs. 28(30.11%)], serum amyloid A (SAA) ≥ 10 mg/L [20(60.61%) vs. 26(27.96%)], and lipoprotein(a) [Lp(a)] ≥ 300 mg/L [21(63.64%) vs. 32(34.41%)] [ χ2 = 12.36, 7.85, 11.20, 8.53, all P < 0.05]. Postoperative smoking, elevated uric acid levels, SAA ≥ 10 mg/L, and Lp(a) ≥ 300 mg/L were identified as independent risk factors for ISR in patients with AMI after PCI ( OR = 0.234, 0.317, 0.252, 0.300, all P < 0.05). A risk prediction model for ISR after PCI was developed based on postoperative smoking, elevated uric acid levels, SAA levels, and Lp(a) levels ≥ 300 mg/L. Receiver operating characteristic curve analysis revealed the areas under the curve were 0.673 [95% CI(0.564, 0.782)], 0.637 [95% CI(0.525, 0.750)], 0.663 [95% CI(0.552, 0.774)], 0.646 [95% CI(0.536, 0.757)], and 0.889 [95% CI(0.821, 0.958)] for ostoperative smoking, elevated uric acid levels, SAA levels, Lp(a) levels ≥ 300 mg/L, and the risk prediction model, respectively. At the critical threshold values, the sensitivities for these variables were 0.636, 0.576, 0.606, 0.636, and 0.909, respectively, while the specificities were 0.710, 0.699, 0.720, 0.656, and 0.763, respectively. The bootstrap method (B = 1000) was used for the internal validation of the risk prediction model. After bias correction, the predicted curve approached the ideal curve, yielding a consistency index of 0.778, which indicates a high predictive value for the model. Moreover, the risk prediction model demonstrated a net benefit greater than 0 within a threshold probability range of 0.02 to 0.93, exceeding two ineffective thresholds. Conclusions:Postoperative smoking, elevated uric acid levels, SAA, and Lp(a) are independent risk factors for ISR in patients with AMI after PCI. The risk prediction model developed based on these four factors demonstrates a high predictive value, which can aid in assessing the risk of ISR in AMI patients with AMI after PCI and in formulating appropriate intervention measures.

Objective:To develop and validate a risk prediction model for in-stent restenosis (ISR) after percutaneous coronary intervention (PCI).Methods:This prospective study included 126 patients with acute myocardial infarction (AMI) who underwent PCI at Lishui Central Hospital from May 2021 to April 2023. The patients were divided into two groups based on whether they experienced ISR after PCI: ISR group ( n = 33) and non-ISR group ( n = 93). Clinical data were compared between the two groups. Binary logistic regression was used to identify independent risk factors for ISR in patients with AMI after PCI. A risk prediction model was then developed, and the predictive value of the model was assessed using receiver operating characteristic curve analysis. Results:After surgery, significant differences were observed between the ISR and non-ISR groups regarding postoperative smoking [21(63.64%) vs. 27(29.03%)], elevated uric acid level [19 (57.58%) vs. 28(30.11%)], serum amyloid A (SAA) ≥ 10 mg/L [20(60.61%) vs. 26(27.96%)], and lipoprotein(a) [Lp(a)] ≥ 300 mg/L [21(63.64%) vs. 32(34.41%)] [ χ2 = 12.36, 7.85, 11.20, 8.53, all P < 0.05]. Postoperative smoking, elevated uric acid levels, SAA ≥ 10 mg/L, and Lp(a) ≥ 300 mg/L were identified as independent risk factors for ISR in patients with AMI after PCI ( OR = 0.234, 0.317, 0.252, 0.300, all P < 0.05). A risk prediction model for ISR after PCI was developed based on postoperative smoking, elevated uric acid levels, SAA levels, and Lp(a) levels ≥ 300 mg/L. Receiver operating characteristic curve analysis revealed the areas under the curve were 0.673 [95% CI(0.564, 0.782)], 0.637 [95% CI(0.525, 0.750)], 0.663 [95% CI(0.552, 0.774)], 0.646 [95% CI(0.536, 0.757)], and 0.889 [95% CI(0.821, 0.958)] for ostoperative smoking, elevated uric acid levels, SAA levels, Lp(a) levels ≥ 300 mg/L, and the risk prediction model, respectively. At the critical threshold values, the sensitivities for these variables were 0.636, 0.576, 0.606, 0.636, and 0.909, respectively, while the specificities were 0.710, 0.699, 0.720, 0.656, and 0.763, respectively. The bootstrap method (B = 1000) was used for the internal validation of the risk prediction model. After bias correction, the predicted curve approached the ideal curve, yielding a consistency index of 0.778, which indicates a high predictive value for the model. Moreover, the risk prediction model demonstrated a net benefit greater than 0 within a threshold probability range of 0.02 to 0.93, exceeding two ineffective thresholds. Conclusions:Postoperative smoking, elevated uric acid levels, SAA, and Lp(a) are independent risk factors for ISR in patients with AMI after PCI. The risk prediction model developed based on these four factors demonstrates a high predictive value, which can aid in assessing the risk of ISR in AMI patients with AMI after PCI and in formulating appropriate intervention measures.