Quantifying risk and assessing outcome in cardiac surgery (original) (raw)
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Defining Operative Mortality: Impact on Outcome Reporting
The Journal of Thoracic and Cardiovascular Surgery, 2015
Objective: Death is an important outcome of procedural interventions. The death rate, or mortality rate, is subject to variability by definition. The Society of Thoracic Surgeons Adult Cardiac Surgery Database definition of ''operative'' mortality originally included all in-hospital deaths and deaths occurring within 30 days of the procedure. In recent versions of the Society of Thoracic Surgeons Adult Cardiac Surgery Database, ''in-hospital'' has been modified to include ''patients transferred to other acute care facilities,'' and ''deaths within 30 days unless clearly unrelated to the procedure'' has been changed to ''deaths within 30 days regardless of cause.'' This study addresses the impact of these redefinitions on outcome reporting. Operative mortality using 5 methods. Central Message Mortality rates for the same procedure can be variable and depend on the definition chosen. Perspective Depending on the definition of mortality used, the mortality rate for any procedure can vary, and these definitions and rankings may not be accurate.
Archives of Surgery, 1998
To compare the performance of several riskscoring models to predict surgical mortality following open heart surgery. Design: A prospective observational study. Setting: Seven tertiary cardiac centers (3 private and 4 public and teaching hospitals) in Catalonia (Spain).
Indication for Surgery, the Revised Cardiac Risk Index, and 1Year Mortality
Annals of Vascular Surgery, 2011
Background: Patients who undergo vascular surgery are at increased risk of perioperative cardiovascular morbidity and mortality. The Revised Cardiac Risk Index (RCRI) is a validated and widely used bedside tool for estimating the risk of a perioperative major adverse myocardial event. We hypothesized that inclusion of the indication for surgery would add independent and prognostic information to the RCRI in predicting all-cause 30-day and 1-year mortality in open infrainguinal vascular surgical procedures. Methods: This was a retrospective study of 603 patients who underwent open infrainguinal bypass vascular surgery between January 2002 and January 2008 at a tertiary care medical center. RCRI and indication for surgery were determined. The primary outcomes of interest were all-cause 30-day mortality (which included all in-hospital mortality, regardless of time) and all-cause 1-year mortality. Results: Overall 30-day mortality was 32 (5.3%). Independent risk factors for early death were RCRI score, being of age 80 years, American Society of Anesthesiologists Physical Status classification ¼ 4, and emergency surgery. Overall 1-year mortality, including early deaths, was 114 (18.9%). Indication for surgery, RCRI score, age, American Society of Anesthesiologists Physical Status classification ¼ 4, female sex, and emergency surgery were all independent predictors of 1-year mortality. Conclusions: The RCRI score was associated with both 30-day and 1-year mortality in patients undergoing lower extremity bypass surgery. Indication for surgery was predictive of 1-year mortality but not of 30-day mortality.
BMJ, 1998
Objective: To detect changes in mortality after surgery, with allowance being made for variations in case mix. Design: Observational study of postoperative mortality from January 1992 to August 1995. Setting: Regional cardiothoracic unit. Subjects: 3983 patients aged 16 and over who had open heart operations. Main outcome measures: Preoperative risk factors and postoperative mortality in hospital within 30 days were recorded for all surgical heart operations. Mortality was adjusted for case mix using a preoperative estimate of risk based on additive Parsonnet factors. The number of operations required for statistical power to detect a doubling of mortality was examined, and control limits at a nominal significance level of P = 0.01 for detection of an adverse trend were determined. Results: Total mortality of 7.0% was 26% below the Parsonnet predictor (P < 0.0001). There was a highly significant variation in annual case mix (Parsonnet scores 8.7-10.6, P < 0.0001). There was no significant variation in mortality after adjustment for case mix (odds ratio 1-1.5, P = 0.18) with monitoring by calendar year. With continuous monitoring, however, nominal 99% control limits based on 16 expected deaths were crossed on two occasions. Conclusions: Hospital league tables for mortality from heart surgery will be of limited value because year to year differences in death rate can be large (odds ratio 1.5) even when the underlying risk or case mix does not change. Statistical quality control of a single series with adjustment for case mix is the only way to take into account recent performance when informing a patient of the risk of surgery at a particular hospital. If there is an increase in the number of deaths the chances of the next patient surviving surgery can be calculated from the last 16 deaths.
Challenges in comparing risk-adjusted bypass surgery mortality results
Journal of the American College of Cardiology, 2000
We sought to evaluate the predictive accuracy of four bypass surgery mortality clinical risk models and to examine the extent to which hospitals' risk-adjusted surgical outcomes vary depending on which risk-adjustment method is applied. BACKGROUND Cardiovascular "report cards" often compare risk-adjusted surgical outcomes; however, it is unclear to what extent the risk-adjustment process itself may affect these metrics.
Mortality After Noncardiac Surgery
Medical Care, 2005
Background: Hospital profiles are increasingly constructed using risk-adjusted clinical data abstracted from patient records. Objective: We sought to compare hospital profiles based on risk adjusted death within 30 days of surgery from administrative versus clinical data in a national cohort of surgical patients. Design: This was a cohort study that included 78,546 major noncardiac operations performed between October 1, 1991 and December 31, 1993 in 44 Veterans Affairs hospitals. Administrative data were used to develop and validate multivariable logistic regression models of 30-day postoperative death for all surgery and 4 surgical specialties (general, orthopedic, thoracic, and vascular). Previously developed and validated clinical models were obtained and reproduced for matching operations using data from the VA National Surgical Quality Improvement Program. Observed-to-expected 30-day mortality ratios for administrative and clinical data were calculated and compared for each hospital. Results: In multivariable logistic regression models using administrative data, characteristics such as patient age, race, marital status, admission from a nursing home, interhospital transfer, admission on the weekend, weekend surgery, and risk strata consisting of groups of principal and comorbidity diagnoses were predictive of postoperative mortality (P Ͻ 0.05). Correlations of the clinical and administrative observed-to-expected ratios were 0.75, 0.83, 0.64, 0.78, and 0.86 for all surgery, general, orthopedic, thoracic, and vascular surgery, respectively. When compared with clinical models, administrative models identified outlier hospitals with sensitivity of 73%, specificity of 89%, positive predictive value of 51%, and negative predictive value of 96%. Conclusions: Our data suggest that risk adjustment of mortality using administrative data may be useful for screening hospitals for potential quality problems.
European Journal of Cardio-thoracic Surgery, 1997
Objecti6e: To develop a risk stratification model to assess open heart surgery mortality in Catalonia (Spain) in order to use risk-adjusted hospital mortality rates as an approach to analyze quality of care. Methods: Data were prospectively collected through a specific data-sheet during 6 1 2 months in consecutive adult patients subjected to open heart surgery. The dependent variable was surgical mortality, and independent variables included were presurgical (sociodemographic data, clinical antecedents, morphological and functional studies) and surgical. The model was built on a subsample (70% of study population) through univariate and logistic regression analysis and validated in the rest of the sample. Results: The total sample was of 1309 procedures in seven hospitals; 47% of them were valve procedures. The overall crude mortality rate was 10.9% and varied among centers (range, 2.8-14.8%). Risk factors included in the model received a weight based on the logistic regression coefficient and a score was generated for each patient. The factors with the highest weight were patient older than 80 and second reoperation. Score was stratified in five categories of increasing risk. There was a good agreement between observed and predicted mortality rates in the validation group. Overall patient distribution was as follows: 52% low risk level, 16% fair, 13% high, 12% very high, and 6% extremely high risk level. Mortality rate increased from 4.2% in the low risk to 54.4% in the highest risk group. Case mix adjustment was performed through the risk score level. There were statistically significant differences in the risk profiles of patients admitted among centers. After adjustment by risk profiles, there were no differences in mortality by hospital. Conclusion: A risk stratification model through a multicentric, prospective and exhaustive collection of data in all types of open heart procedures was developed. In spite of wide differences on crude rates and in the risk profiles of patients admitted, we did not find statistically significant differences in adjusted mortality rates among centers. Timely and accurate information about surgical outcomes can lead to improvements in clinical practice and quality of care. © 1997 Elsevier Science B.V.
Risk factors for early and late mortality in surgical treatment of coronary artery disease
Cardiovascular Surgery, 1995
A total of IOZS patients who had coronary bypass surgery at the Surgical Department A, Rikshospitalet, Oslo. between 1982 and 1966, were analysed for factors associated with early mortality and long-term survival. The cumulative follow-up time accounted for 6553 patient-years: the median follow-up was 6.45 years and ranged from the day of admission to IO years. In total, 31 patients (3%) died within 30 days of surgery. Some 30 possible risk factors were analysed. Univariate analysis followed by a multiiariate analysis defined six independent risk factors for early mortality. These were lack of sinus rhythm, previous heart surgery, mitral regurgitation, left main stem stenosis, unstable angina, and an elevated left ventricular end-diastolic pressure. Estimation of attributable risk showed that these factors could identify all patients who died early. Independent risk factors for late death were: lack of sinus rhythm, resection of a left ventricular aneurysm, left main stem stenosis, New York Heart Association (NYHA) class N on admission, an elevated end-diastolic pressure, and prolonged cross-ciamping time. The attributable risk analysis showed that independent risk factors for total mortaiii explained only about half of the patients who died. This appeared to be because of the competing effect of non-cardiac mortality. Results of the study show that risk factors for early mortality are good indicators for the outcome of coronary artery bypass surgery, identif+jng all deaths, whereas long-term mortality cannot be predii. Stratlfkation of independent risk factors allows a better comparison of mortality in different centres, and also better qualii control of bypass surgery.
Subjective Versus Statistical Model Assessment of Mortality Risk in Open Heart Surgical Procedures
surgical procedures Subjective versus statistical model assessment of mortality risk in open heart http://ats.ctsnetjournals.org/cgi/content/full/67/3/635 on the World Wide Web at: The online version of this article, along with updated information and services, is located Print ISSN: 0003-4975; eISSN: 1552-6259. Southern Thoracic Surgical Association. Background. The aim of this study was to compare the predictive accuracy for open heart surgical mortality between a statistical model based on collection of clinical data and surgeons' subjective risk assessment.
The Annals of Thoracic Surgery, 2004
Risk models play a vital role in monitoring health care performances. Despite extensive research and widespread use of risk models in cardiac surgery, there are methodologic problems. We reviewed the methodology used for risk models for short-term mortality. The findings suggest that many risk models are developed in an ad hoc manner. Important aspects such as selection of risk factors, handling of missing values, and size of the data used for model development are not dealt with adequately. Methodologic details presented in publications are often sparse and unclear. Model development and validation processes are not always linked to the clinical aim of the model, which may affect their clinical validity. We make some suggestions in this review for improvement in methodology and reporting.