Objective To explore the causes of conversion to thoracotomy in patients with minimally invasive esophagectomy (MIE) in a surgical team, and to obtain a deeper understanding of the timing of conversion in MIE. Methods The clinical data of patients who underwent MIE between September 9, 2011 and February 12, 2022 by a single surgical team in the Department of Thoracic Surgery of the Fourth Hospital of Hebei Medical University were retrospectively analyzed. The main influencing factors and perioperative mortality of patients who converted to thoracotomy in this group were analyzed. Results In the cohort of 791 consecutive patients with MIE, there were 520 males and 271 females, including 29 patients of multiple esophageal cancer, 156 patients of upper thoracic cancer, 524 patients of middle thoracic cancer, and 82 patients of lower thoracic cancer. And 46 patients were converted to thoracotomy for different causes. The main causes for thoracotomy were advanced stage tumor (26 patients), anesthesia-related factors (5 patients), extensive thoracic adhesions (6 patients), and accidental injury of important structures (8 patients). There was a statistical difference in the distribution of tumor locations between patients who converted to thoracotomy and the MIE patients (P<0.05). The proportion of multiple and upper thoracic cancer in patients who converted to thoracotomy was higher than that in the MIE patients, while the proportion of lower thoracic cancer was lower than that in the MIE patients. The perioperative mortality of the thoracotomy patients was not significantly different from that of the MIE patients (P=1.000). Conclusion In MIE, advanced-stage tumor, anesthesia-related factors, extensive thoracic adhesions, and accidental injury of important structures are the main causes of conversion to thoracotomy. The rate varies at different tumor locations. Intraoperative conversion to thoracotomy does not affect the perioperative mortality of MIE.
ObjectiveTo investigate the value of preoperative clinical data and computed tomography angiography (CTA) data in predicting perioperative mortality risk in patients with acute aortic dissection (AAD), and to construct a Nomogram prediction model. MethodsA retrospective study was conducted on AAD patients treated at Affiliated Hospital of Zunyi Medical University from February 2013 to July 2023. Patients who died during the perioperative period were included in the death group, and those who improved during the same period were randomly selected as the non-death group using a random number table method. The first CTA data and preoperative clinical data within the perioperative period of the two groups were collected, and related risk factors were analyzed to screen out independent predictive factors for perioperative death. The Nomogram prediction model for perioperative mortality risk in AAD patients was constructed using the screened independent predictive factors, and the effect of the Nomogram was evaluated by calibration curves and area under the curve (AUC). ResultsA total of 270 AAD patients were included. There were 60 patients in the death group, including 42 males and 18 females with an average age of (56.89±13.42) years. There were 210 patients in the non-death group, including 163 males and 47 females with an average age of (56.15±13.77) years. Multivariate logistic regression analysis showed that type A AAD [OR=4.589, 95%CI (2.273, 9.267), P<0.001], irregular tear morphology [OR=2.054, 95%CI (1.025, 4.117), P=0.042], decreased hemoglobin [OR=0.983, 95%CI (0.971, 0.995), P=0.007], increased uric acid [OR=1.003, 95%CI (1.001, 1.005), P=0.004], and increased aspartate aminotransferase [OR=1.003, 95%CI (1.000, 1.006), P=0.035] were independent risk factors for perioperative death in AAD patients. The Nomogram prediction model constructed using the above risk factors had an AUC of 0.790 for predicting perioperative death, indicating good predictive performance. ConclusionType A AAD, irregular tear morphology, decreased hemoglobin, increased uric acid, and increased aspartate aminotransferase are independent predictive factors for perioperative death in AAD patients. The Nomogram prediction model constructed using these factors can help assess the perioperative mortality risk of AAD patients.
Objective To investigate the 30-day mortality risk factors in elderly patients with heart failure with reduced ejection fraction (HFrEF) after isolated coronary artery bypass grafting (CABG) and to construct a nomogram for predicting mortality risk. Methods A retrospective analysis of elderly (≥70 years) HFrEF patients undergoing isolated CABG at Tianjin Chest Hospital from 2010 to 2024 was performed. Simple random sampling in R software was used to divide the dataset into training and validation sets in a 7 : 3 ratio. The training set was further divided into survivors and non-survivors. Univariate logistic regression was performed to identify differences between groups, followed by multivariate logistic regression to select independent risk factors for death and to establish a death-risk nomogram, which underwent internal validation. The predictive value of the nomogram was assessed by plotting receiver operating characteristic (ROC) curves, calibration curves, and decision-curve analyses for both the training and validation sets. ResultsA total of 656 patients were included. The training set consisted of 458 patients (survivors 418, deaths 40); the validation set consisted of 198 patients (survivors 180, deaths 18). In the training set, univariate analysis showed significant differences between survivors and deaths for creatinine (Cr) level, brain natriuretic peptide (BNP), maximum Cr, intra-aortic balloon pump (IABP) use, assisted ventilation, reintubation, hyperlactatemia, low cardiac output syndrome, and renal failure (P<0.05). After multivariable logistic regression, five independent risk factors were identified: IABP use (OR=3.391, 95%CI 1.065-11.044, P=0.038), reintubation (OR=15.991, 95%CI 4.269-67.394, P<0.001), hyperlactatemia (OR=8.171, 95%CI 2.057-46.089, P=0.007), Cr (OR=4.330, 95%CI 0.997-6.022, P=0.024), and BNP (OR=1.603, 95%CI 1.000-2.000, P=0.010). Accordingly, a nomogram predicting mortality risk was constructed. The ROC and calibration analyses indicated good predictive value: area under the curve (AUC) in the training set was 0.898 (95%CI 0.831-0.966) and in the validation set was 0.912 (95%CI 0.805-1.000). Calibration and decision-curve analyses showed good agreement and clinical utility. Conclusion The nomogram incorporating IABP use, reintubation, hyperlactatemia, creatinine, and BNP provides good predictive value for 30-day mortality after CABG in elderly patients with HFrEF and demonstrates potential clinical utility.