心血管手术风险预测研究与现状

手术风险预测模型是术前风险评估的重要工具,在外科临床工作中起着十分重要的作用,它对手术适应证的确定、手术相关危险因素的识别、     

Prediction of Early Recurrence After Surgery for Liver Tumor (ERASL): An International Validation of the ERASL Risk Models

Annals of Surgical Oncology - This study aimed to assess the performance of the pre- and postoperative early recurrence after surgery for liver tumor (ERASL) models at external validation....     

Coronary Artery Bypass Risk Prediction Using Neural Networks

Background. Neural networks are nonparametric, robust, pattern recognition techniques that can be used to model complex relationships.

Methods. The applicability of multilayer perceptron neural networks (MLP) to coronary artery bypass grafting risk prediction was assessed using The Society of Thoracic Surgeons database of 80,606 patients who underwent coronary artery bypass grafting in 1993. The results of traditional logistic regression and Bayesian analysis were compared with single-layer (no hidden layer), two-layer (one hidden layer), and three-layer (two hidden layer) MLP neural networks. These networks were trained using stochastic gradient descent with early stopping. All prediction models used the same variables and were evaluated by training on 40,480 patients and cross-validation testing on a separate group of 40,126 patients. Techniques were also developed to calculate effective odds ratios for MLP networks and to generate confidence intervals for MLP risk predictions using an auxiliary “confidence MLP.”

Results. Receiver operating characteristic curve areas for predicting mortality were approximately 76% for all classifiers, including neural networks. Calibration (accuracy of posterior probability prediction) was slightly better with a two-member committee classifier that averaged the outputs of a MLP network and a logistic regression model. Unlike the individual methods, the committee classifier did not overestimate or underestimate risk for high-risk patients.

Conclusions. A committee classifier combining the best neural network and logistic regression provided the best model calibration, but the receiver operating characteristic curve area was only 76% irrespective of which predictive model was used.     

Muscle Strength and Physical Performance Improve Fracture Risk Prediction Beyond Garvan and FRAX: The Osteoporotic Fractures in Men (MrOS) Study

Muscle strength and physical performance are associated with fracture risk in men. However, it is not known whether these measurements enhance fracture prediction beyond Garvan and FRAX tools. A total of 5665 community-dwelling men, aged ≥65 years, from the Osteoporotic Fractures in Men (MrOS) Study, who had data on muscle strength (grip strength) and physical performance (gait speed and chair stand tests), were followed from 2000 to 2019 for any fracture, major osteoporotic fracture (MOF), initial hip, and any hip fracture. The contributions to different fracture outcomes were assessed using Cox's proportional hazard models. Tool-specific analysis approaches and outcome definitions were used. The added predictive values of muscle strength and physical performance beyond Garvan and FRAX were assessed using categorical net reclassification improvement (NRI) and relative importance analyses. During a median follow-up of 13 (interquartile range 7–17) years, there were 1014 fractures, 536 MOFs, 215 initial hip, and 274 any hip fractures. Grip strength and chair stand improved prediction of any fracture (NRI for grip strength 3.9% and for chair stand 3.2%) and MOF (5.2% and 6.1%). Gait speed improved prediction of initial hip (5.7%) and any hip (7.0%) fracture. Combining grip strength and the relevant performance test further improved the models (5.7%, 8.9%, 9.4%, and 7.0% for any, MOF, initial, and any hip fractures, respectively). The improvements were predominantly driven by reclassification of those with fracture to higher risk categories. Apart from age and femoral neck bone mineral density, muscle strength and performance were ranked equal to or better than the other risk factors included in fracture models, including prior fractures, falls, smoking, alcohol, and glucocorticoid use. Muscle strength and performance measurements improved fracture risk prediction in men beyond Garvan and FRAX. They were as or more important than other established risk factors. These measures should be considered for inclusion in fracture risk assessment tools. © 2021 American Society for Bone and Mineral Research (ASBMR).     

心脏瓣膜手术在院死亡风险预测模型及评分标准的建立

目的为提高心脏瓣膜手术围术期的安全性,建立我国心脏瓣膜手术在院死亡的风险预测模型及评分标准。方法纳入1998年1月1日至2008年12月31日于长海医院接受主动脉瓣置换术、二尖瓣置换术、二尖瓣成形术和二尖瓣＋主动脉瓣联合手术患者共4 032例的临床资料,其中男1876例（46.53%）,女2156例（53.47%）;年龄45.90±13.60岁。根据左侧房室瓣的手术部位,将患者分为二尖瓣手术组（n=1910）、主动脉瓣手术组（n=724）和二尖瓣＋主动脉瓣联合手术组（n=1398）3组;并将纳入患者的60%作为建模亚库（n=2418）,40%作为验证亚库（n=1 614）。采用单因素分析和多因素logistic回归分析建立模型,通过Hosmer-Lemeshow（H-L）卡方检验及受试者工作特征（receiver operating characteristic,ROC）曲线下面积评价模型预测校准度和鉴别效度,据模型中各危险因素的权重系数及其变量类型构建风险预测的评分标准。结果总在院病死率为4.74%（191/4032）。多因素logistic回归分析发现,三尖瓣关闭不全[OR=1.33,95%CI（1.071,1.648）]、主动脉瓣狭窄[OR=1.34,95%CI（1.082,1.659）]、慢性肺部疾病[OR=2.11,95%CI（1.292,3.455）]、左心室射血分数[OR=1.55,95%CI（1.081,2.234）]、术前危重状态[OR=2.69,95%CI（1.499,4.821）]、心功能分级（NYHA）[OR=2.75,95%CI（1.343,5.641）]、同期冠状动脉旁路移植术（CABG）[OR=3.02,95%CI（1.405,6.483）]以及术前最后一次血清肌酐水平[OR=4.16,95%CI（1.979,8.766）]为心瓣膜手术在院死亡的独立危险因子。各组预测校准度较好,H-L卡方检验P均〉0.05（建模亚库组：χ^2=1.615,P=0.830;验证亚库组：χ^2=2.218,P=0.200;二尖瓣手术组：χ^2=5.175,P=0.470;主动脉瓣手术组：χ^2=12.708,P=0.090;二尖瓣＋主动脉瓣手术组：χ^2=3.875,P=0.380）,而ROC曲线下面积均〉0.70[建模亚库组：0.757,95%CI（0.712,0.802）;验证亚库组：0.754,95% CI（0.701,0.806）;二尖瓣手术组：0.760,95%CI（0.706,0.813）;主动脉瓣手术组：0.803,95%CI（0.738,0.868）;二尖瓣＋主动脉瓣联合手术组：0.727,95%CI（0.668,0.785）]。成功建立风险预测的评分标准为：三尖瓣关闭不全（轻度1分、中度2分、重度3分）,主动脉瓣狭窄（轻度1分、中度2分、重度3分）,慢性肺部疾病3分,左心室射血分数（40%-50%2分3、0%-40%4分、〈30%6分）,术前危重状态3分,NYHA分级Ⅲ-Ⅳ级4分,同期CABG 4分以及术前最后一次血清肌酐水平〉110μmol/L5分。结论三尖瓣关闭不全等8个因素为影响我国心瓣膜手术在院死亡的独立危险因子,该模型具有良好的预测校准度和鉴别效度,通过该模型建立的评分标准对我国心瓣膜手术在院死亡的发生具有较好的预测性。     

Comparison of Preoperative Surgical Risk Estimated by Thoracic Surgeons vs a Standardized Surgical Risk Prediction Tool

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Method of Glomerular Filtration Rate Estimation Affects Prediction of Mortality Risk

Decreased kidney function, determined using a serum creatinine–based estimation of GFR, is associated with a higher risk for mortality from cardiovascular disease. Equations incorporating cystatin C improve the estimation of GFR, but whether this improves the prediction of risk for mortality is unknown. We measured cystatin C on 6942 adult participants in the Third National Health and Nutrition Examination Survey Linked Mortality File, including all participants who had high serum creatinine (>1.2 mg/dl for men; >1.0 mg/dl for women) or were older than 60 yr and 25% random sample of participants who were younger than 60 yr. We estimated GFR using equations that included standardized serum creatinine, cystatin C, or both. Participant data were linked to the National Death Index. A total of 1573 (22.7%) deaths (713 deaths from cardiovascular disease) occurred during a median of 8 yr. Lower estimated GFR based on cystatin C was strongly associated with higher risk for overall and cardiovascular mortality across the range of normal to moderately decreased estimated GFR. Creatinine-based estimates of GFR resulted in weaker associations, with the association between estimated GFR and all-cause mortality reversed at higher levels of estimated GFR. An equation using both creatinine and cystatin C (in addition to age, race, and gender) resulted in weaker associations than equations using only cystatin C (with or without age, race, and gender). In conclusion, despite better performance in terms of estimating GFR, equations based on both cystatin C and creatinine do not predict mortality as well as equations based on cystatin C alone.Moderately decreased kidney function, as estimated from equations based on serum creatinine, is associated with an elevated risk for mortality, both in individuals with existing cardiovascular disease (CVD) and in the general population.^1–3 Serum levels of creatinine, however, are affected by other factors in addition to GFR, most importantly, variations in creatinine generation as a result of differences in muscle mass and turnover.⁴ Muscle wasting as a result of chronic illness is associated with lower creatinine generation, leading to an overestimation of GFR in such individuals. Because these same individuals are at an elevated risk for mortality, this systematic bias would result in an underestimation of the association between decreased GFR and mortality risk. This may be a particular problem in the elderly because of their higher prevalence of chronic illness and higher risk for mortality. In addition, currently available GFR estimates based on serum creatinine are less accurate at higher levels of kidney function, probably reflecting a greater proportional contribution of creatinine generation to variation in the serum creatinine level than at lower levels of kidney function.⁵Cystatin C is a marker of kidney function that is less sensitive to differences in muscle mass than is serum creatinine.⁴ Cystatin C predicted total and cardiovascular mortality risk more strongly than creatinine-based estimates of GFR in prospective studies of older adults.^6,7 Data on younger individuals are lacking. Recent data allow GFR estimation from serum cystatin C and showed that equations using both serum creatinine and cystatin C, in addition to age, race, and gender, are more closely correlated with directly measured GFR among individuals with chronic kidney disease (CKD) than equations based on either marker alone.⁸ The associations with mortality risk of eGFR based on serum creatinine, cystatin C, or the combination of the two, however, has not been studied. As the use of cystatin C as a marker of cardiovascular risk increases, it is critical to understand how one should combine information on serum creatinine with cystatin C for risk prediction. We analyzed up to 13 yr of mortality follow-up on 6942 participants in the Third National Health and Nutrition Examination Survey (NHANES III) to assess the association of eGFR based on equations using creatinine, cystatin C, or both markers with the risk for all-cause and cardiovascular mortality in a representative sample of US adults.