Discussion
AHF, heart disease, fracture, respiratory diseases, fractures, heart failure, COPD
RESPIRATORY DISEASE, CHRONIC HEART FAILURE, HEART DISEASE, RENAL FAILURE, ELECTROLYTE DISTURBANCE, COMPLICATION, CHRONIC OBSTRUCTIVE PULMONARY DISEASE, COPD, REGRESSION, CARDIAC EVENTS, HEART FAILURE
AHF is a common and serious complication in older patients with hip fractures. In this study, we found that the prevalence of AHF was 18.37%. The results demonstrate that respiratory disease, history of heart disease (chronic heart failure excluded), ASA ≥ 3, and preoperative waiting time ≤ 2 days were independent risk factors for perioperative AHF in older hip fracture patients.The AUC of the risk prediction model constructed was 0.877 in the modeling group and 0.910 in the validation group. It can be seen that the prediction model is highly accurate in identifying the occurrence of perioperative AHF. Regarding the Hosmer–Lemeshow test, the The worse the patient's health condition before injury, the more likely they will have perioperative AHF, especially the patients with respiratory diseases and cardiac history. Paul found that the chance of heart failure in patients with chronic obstructive pulmonary disease (COPD) is 2.17 times high than in those without COPD, which is close to 1.9 times that of Truls et al. [In this study, we found that ASA ≥ 3 was the strongest predictor of perioperative AHF in older hip fracture patients, with an OR of 14.46 as compared with those with lower ASA class. ASA grading standard is a scoring system that can be used to assess patients’ operative risk of patients and guide resource allocations [The optimal timing of surgery for older patients with hip fracture has still been controversial. Relevant guidelines from abroad recommend that patients with hip fractures should receive early aggressive surgical treatment within 48 or even 24 h after injury [Nomograms integrate multiple independent risk factors identified via the multivariate regression analysis, and assign a value according to the contribution of each risk factor to the outcome variable, proving an excellent results visualization tool. In this study, the prediction model includes four easily available risk factors. Clinicians only need to draw vertical lines according to a specific proportion to obtain the prediction probability of each variable and calculate the sum to obtain the final probability of risk. This model helps doctors monitor the risk of AHF regularly and guide medical personnel in correcting potential changeable risk factors, thereby facilitating the reduction of perioperative AHF.The merits of this study were the establishment of a nomogram for visualized assessment of risk factors for perioperative AHF in older hip fracture patients. However, several limitations should be mentioned. First, there was a bias in the selection of subjects, because this study was a single-center retrospective study. Therefore, the results may have been affected by the inaccuracy of the collected data and the absence of external validation, requiring prospective multicenter studies to verify. Second, although a multivariate regression model was used to minimize confounders, there are still unknown or unmeasured confounders, such as the perioperative fluid balance condition, the perioperative defecation condition, etc. Third, the study sample was limited, thus having less power to detect the significance of some infrequent variables, such as renal failure, which was more likely associated with electrolyte disturbance and caused adverse cardiac events [