Improving Surgical Risk Prediction and Decision Making among Patients with Cirrhosis

改善肝硬化患者的手术风险预测和决策

• 批准号: 10598551
• 负责人: Nadim Mahmud
• 金额: $ 16.66万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10598551
• 关键词: Acute Cholecystitis; Address; Age; American; Award; Biometry; Calibration; Cardiac; Child; Cirrhosis; Clinical; Complex; Conceptions; Counseling; Data; Data Set; Databases; Decision Analysis; Decision Making; Development; Discrimination; Educational workshop; Etiology; Feedback; Fostering; Funding; Future; General Population; Goals; Grant; Health Policy; Health system; Hepatitis C; Heterogeneity; Hospitals; Impairment; Knowledge; Laboratories; Literature; Liver diseases; Medical; Mentorship; Methods; Modeling; Modernization; Natural History; Operative Surgical Procedures; Orthopedics; Pathway interactions; Patient Selection; Patients; Pennsylvania; Perception; Policy Research; Population; Positioning Attribute; Postoperative Period; Provider; Qualitative Methods; Qualitative Research; Quality of life; Relative Risks; Research; Research Methodology; Research Personnel; Retrospective Studies; Risk; Risk Estimate; Risk Factors; Sample Size; Schools; Severities; Severity of illness; Societies; Sodium; Structure; Surgeon; System; Techniques; United States National Institutes of Health; Universities; Validation; Veterans; Veterans Health Administration; chronic liver disease; clinical care; clinical center; clinical epidemiology; clinical implementation; clinical practice; cohort; design; disease classification; end stage liver disease; experience; improved; innovation; markov model; meetings; minimally invasive; mortality; mortality risk; nonalcoholic steatohepatitis; novel; operation; palliation; predictive modeling; predictive tools; prognostic; prognostic tool; risk prediction; risk prediction model; risk stratification; statistics; surgical risk; symposium; tool; web app; Acute Cholecystitis; Address; Age; American; Award; Biometry; Calibration; Cardiac; Child; Cirrhosis; Clinical; Complex; Conceptions; Counseling; Data; Data Set; Databases; Decision Analysis; Decision Making; Development; Discrimination; Educational workshop; Etiology; Feedback; Fostering; Funding; Future; General Population; Goals; Grant; Health Policy; Health system; Hepatitis C; Heterogeneity; Hospitals; Impairment; Knowledge; Laboratories; Literature; Liver diseases; Medical; Mentorship; Methods; Modeling; Modernization; Natural History; Operative Surgical Procedures; Orthopedics; Pathway interactions; Patient Selection; Patients; Pennsylvania; Perception; Policy Research; Population; Positioning Attribute; Postoperative Period; Provider; Qualitative Methods; Qualitative Research; Quality of life; Relative Risks; Research; Research Methodology; Research Personnel; Retrospective Studies; Risk; Risk Estimate; Risk Factors; Sample Size; Schools; Severities; Severity of illness; Societies; Sodium; Structure; Surgeon; System; Techniques; United States National Institutes of Health; Universities; Validation; Veterans; Veterans Health Administration; chronic liver disease; clinical care; clinical center; clinical epidemiology; clinical implementation; clinical practice; cohort; design; disease classification; end stage liver disease; experience; improved; innovation; markov model; meetings; minimally invasive; mortality; mortality risk; nonalcoholic steatohepatitis; novel; operation; palliation; predictive modeling; predictive tools; prognostic; prognostic tool; risk prediction; risk prediction model; risk stratification; statistics; surgical risk; symposium; tool; web app

PROJECT SUMMARY Patients with cirrhosis have increased surgical risk relative to the general population Several risk factors have been established to predict cirrhosis surgical risk. These are reflected in the primary clinical tools used for risk prediction—the Model for End-stage Liver Disease-sodium (MELD-Na), Child-Turcotte-Pugh (CTP) score, and the Mayo surgical risk score—which rely on age, cirrhosis severity, ASA physical status score, and etiology of liver disease. However, significant heterogeneity in post-operative mortality by surgery type (e.g., cardiac versus orthopedic) suggests that these tools are inadequate. The literature on cirrhosis surgical risk prediction is further limited by: 1) single-center designs with small sample sizes, 2) lack of granular data for risk prediction, 3) evidence of poor prediction score calibration, 4) lack of key stakeholder involvement to inform real-world implementation of prediction tools, and 5) no incorporation of decision analysis methods to compare surgery to non-operative management. The impact of these shortcomings is that many patients with cirrhosis are denied necessary surgery due to overestimates of risk, and others receive surgery with inaccurate prognostic counseling or inadequate consideration of non-operative options. Granular, population-level data are needed to address the above gaps. By using national Veterans Health Administration (VHA) and University of Pennsylvania Hospital System (UPHS) data, we hypothesize that we will be able to create and implement an accurate, well-calibrated cirrhosis surgical risk calculator with broad clinical utility. The primary aims of this proposal are as follows: Aim 1 – derive, internally validate, and externally validate cirrhosis surgical risk models for short- and intermediate-term post-operative mortality among diverse patients with cirrhosis.; Aim 2 – create a web application for surgical risk prediction informed by key stakeholder input.; Aim 3 – use Markov modeling to compare operative to non-operative management pathways and determine optimal clinical decisions for a common clinical scenario: acute cholecystitis. This proposal will foster Dr. Nadim Mahmud's development as an independent, NIH-funded clinical researcher with a focus on improving risk prediction for patients with chronic liver diseases, as well as specific expertise in advanced prediction modeling, qualitative methods, and decision analysis. This will be facilitated through a comprehensive mentorship plan consisting of: 1) biweekly to monthly meetings with his mentorship team, 2) formal coursework in advanced prediction modeling, qualitative research methods, and decision analysis through the Center for Clinical Epidemiology and Biostatistics (CCEB), Wharton School, Department of Health Policy Research (HPR), Operations, Information, and Decisions Department (OIDD), and Department of Statistics (STAT) at the University of Pennsylvania, 3) structured research workshops and national conferences, and 4) conception, development, and submission of future grants during the latter portion of the award period to further explore issues related to surgical risk prediction among patients with cirrhosis.

项目摘要 肝硬化患者相对于一般人群的手术风险增加了多种风险因素 建立他们以预测肝硬化手术风险。这些反映在用于风险的主要临床工具中 预测 - 终阶段肝病 - 钠（MELD-NA），Child-Turcotte-Pugh（CTP）评分和 蛋黄酱的手术风险评分（依赖年龄，肝硬化严重程度，ASA身体状况评分和病因 肝病。但是，手术类型的术后死亡率的显着异质性（例如心脏 与骨科）表明，这些工具不足。关于肝硬化手术风险预测的文献 进一步受到以下限制：1）单中心设计的样本量较小，2）缺乏风险的颗粒状数据 预测，3）预测得分校准差的证据，4）缺乏关键利益相关者参与来告知 实际实施预测工具，以及5）没有决策分析方法的保险来比较 非手术管理的手术。这些缺点的影响是许多肝硬化患者 由于风险高估而被拒绝进行必要的手术，而其他人则接受手术不准确 预后咨询或考虑非手术选择的考虑不足。颗粒状，人口级数据 需要解决上述差距。使用国家退伍军人卫生管理局（VHA）和大学 宾夕法尼亚州医院系统（UPHS）数据，我们假设我们能够创建和实施 具有广泛临床实用性的精确，精心校准的肝硬化手术风险计算器。主要目的 建议如下：AIM 1 - 衍生，内部验证和外部验证肝硬化风险 肝硬化患者的短期和中期术后死亡率的模型。目标2 - 创建一个Web应用程序，以通过关键利益相关者输入告知的手术风险预测。瞄准3 - 使用马尔可夫 建模以比较运行与非手术管理途径并确定最佳临床 常见临床情况的决定：急性胆囊炎。该建议将培养纳迪姆·马哈茂德博士 作为一名独立的，由NIH资助的临床研究人员发展，重点是改善风险预测 患有慢性肝病的患者以及高级预测建模的特定专业知识，定性 方法和决策分析。这将通过一项全面的心态计划来准备： 1）每两周与他的Mentalship团队每月举行会议，2）高级预测的正式课程 通过临床流行病学中心建模，定性研究方法和决策分析 和生物统计学（CCEB），沃顿大学院，卫生政策研究系（HPR），运营， 信息和决策系（OIDD）和统计系（STAT） 宾夕法尼亚州，3）结构化的研究研讨会和国家会议，以及4）概念，发展， 并在颁奖期的后期提交未来赠款，以进一步探讨与 肝硬化患者的手术风险预测。