Predicting acute renal failure after coronary bypass surgery: cross-validation of two risk-stratification algorithms

BACKGROUND: Acute renal failure (ARF) requiring dialysis after coronary artery bypass grafting (CABG) occurs in 1 to 5% of patients and is independently associated with postoperative mortality, even after case-mix adjustment. A risk-stratification algorithm that could reliably identify patients at increased risk of ARF could help improve outcomes. METHODS: To assess the validity and generalizability of a previously published preoperative renal risk-stratification algorithm, we analyzed data from the Quality Measurement and Management Initiative (QMMI)1 patient cohort. The QMMI includes all adult patients (N = 9498) who underwent CABG at 1 of 12 academic tertiary care hospitals from August 1993 to October 1995. ARF requiring dialysis was the outcome of interest. Cross-validation of a recursive partitioning algorithm developed from the VA Continuous Improvement in Cardiac Surgery Program (CICSP) was performed on the QMMI. An additive severity score derived from logistic regression was also cross-validated on the QMMI. RESULTS: The CICSP recursive partitioning algorithm discriminated well (ARF vs. no ARF) in QMMI patients, even though the QMMI cohort was more diverse. Rates of ARF were similar among risk subgroups in the CICSP tree, as was the overall ranking of subgroups by risk. Using logistic regression, independent predictors of ARF in the QMMI cohort were similar to those found in the CICSP. The CICSP additive severity score performed well in the QMMI cohort, successfully stratifying patients into low-, medium-, high-, and very high-risk groups. CONCLUSIONS: The CICSP preoperative renal-risk algorithms are valid and generalizable across diverse populations.     

Prediction rules for complications in coronary bypass surgery: a comparison and methodological critique

BACKGROUND: Clinical prediction rules have been developed that use preoperative information to stratify patients according to risk of complications after cardiac surgery. OBJECTIVES: To assess the methodological standards and performance of 7 models. PARTICIPANTS: The validation portion of the Quality Measurement and Management Initiative (QMMI) cohort included a random sample of all adult patients (n = 3,261) who underwent coronary artery bypass grafting (CABG) surgery not involving valvular or other concomitant procedures at 12 medical centers from August 1993 to October 1995. OUTCOME MEASURES: Methodological standards used for model comparison were adapted from published criteria. Model performance was assessed by receiver-operating characteristic (ROC) analysis, and calibration was evaluated with the Hosmer-Lemeshow (HL) statistic and observed-expected plots. METHODS: We performed cross-validation by applying the published criteria for the development of each model to the validation subset of the QMMI cohort and by assessing the performance of each model in discriminating outcomes. RESULTS: Wide variations existed in the methodologies used to develop and validate the 5 additive scores evaluated. Cross-validation of all 5 additive scores revealed degradation in their abilities to discriminate outcomes. The 2 logistic models examined performed similarly to the additive scores examined in predicting mortality. CONCLUSIONS: Substantial variation existed both in the methodologies used to develop models and in the ability of the models to predict outcomes. Models developed at single institutions or using fewer patients may be less generalizable when applied to diverse clinical settings. Additive and logistic regression models performed similarly, as assessed by ROC and HL analyses.     

Is preparation for emergency obstetric anaesthesia adequate? A maternal questionnaire survey

BACKGROUND: Women are often unprepared for emergency obstetric procedures and need to receive information about anaesthesia quickly and succinctly. In the absence of previous studies, we sought feedback from women to find out how information was given, and particular areas of concern in order to define practice and improve women's experiences. METHODS: After Ethics Committee approval this prospective structured questionnaire study was conducted in a teaching and a district general hospital. Women were recruited up to 48 h after anaesthesia. RESULTS: Of 102 women studied, 55 had no prior knowledge of obstetric anaesthetic interventions and risks until told, usually by the obstetrician (n=47), just before the procedure. The most frightening aspect was anticipating the efficacy of regional anaesthesia (n=18), but 28 women were reassured by the explanation provided by the anaesthetist. All but two women expressed satisfaction with the content of information and the described attendant risks. Nevertheless, in contrast to our observed practice, 51 (50%) would have preferred having verbal information before labour preferably from an anaesthetist or midwife. CONCLUSIONS: Most women were unprepared for emergency obstetric anaesthesia. Many received information just before the event. After delivery they expressed a clear preference for earlier information.     

Patient, procedural, and hardware factors associated with pacemaker lead failures in pediatrics and congenital heart disease

OBJECTIVES: To examine outcomes of children with pacemakers over a 22-year period and identify risk factors for lead failure. BACKGROUND: Small patient size, structural cardiac abnormalities, and growth may complicate pediatric pacemaker management. Better knowledge of risk factors for lead failure in these patients may help improve future outcomes. METHODS: All pacemaker patients followed at one pediatric center 1980-2002 were included. Lead failures were identified retrospectively as leads repaired, replaced, or abandoned due to fracture, insulation break, dislodgement, or abnormalities in pacing or sensing. Risk factors were identified using logistic regression and Cox analyses. RESULTS: A total of 1007 leads were implanted in 497 patients during the study period (5175 lead-years). Median age at implant was 9 years (0-55); 64% of patients had structural congenital heart disease. Median follow-up time was 6.2 years (0-22). Lead failure occurred in 155 leads (15%), and 115 patients (23%), with 28% of patients experiencing multiple failures. Significant independent correlates of lead failure included age <12 years at implant, history of structural congenital heart defects, and epicardial lead placement. Younger patients (<12 years) experienced significantly more lead fractures than older children (P = .005), while patients with congenital heart defects experienced more exit block. Epicardial leads were more likely to fail due to fracture or exit block, while transvenous leads failed more due to insulation breaks or dislodgements. CONCLUSIONS: Pediatric pacing patients have a high incidence lead failures. These occur most commonly in younger patients, structural congenital heart disease, and those with epicardial lead systems. Approaches to pacing system implantation and follow-up in these patients need to be individualized, with special attention to minimizing risk of lead failures. Our findings suggest that expanded utilization of transvenous systems in smaller patients seems justified when anatomy permits.     

Development and validation of a clinical prediction rule for major adverse outcomes in coronary bypass grafting.

In this study, we develop and internally validate a clinical prediction rule for in-hospital major adverse outcomes, defined as death, renal failure, reinfarction, cardiac arrest, cerebrovascular accident, or coma, in patients who underwent coronary artery bypass grafting (CABG). All adult patients (n = 9,498) who underwent a CABG and no other concomitant surgery at 12 academic medical centers from August 1993 to October 1995 were included in the study. We assessed in-hospital major adverse outcomes and their predictors using information on admission, coronary angiography, and postoperative hospital course. Predictor variables were limited to information available before the procedure, and outcome variables were represented only by events that occurred postoperatively. We developed and internally validated a clinical prediction rule for any major adverse outcome after CABG. The rule's ability to discriminate outcomes and its calibration were assessed using receiver-operating characteristic analysis and the Hosmer-Lemeshow goodness-of-fit statistic, respectively. A major adverse outcome occurred in 6.5% of patients in the derivation set and 7.2% in the validation set. Death occurred in 2.5% of patients in the derivation set and 2.2% in the validation set. Sixteen variables were independently correlated with major adverse outcomes, with the risk score value attributed to each risk factor ranging from 2 to 12 points. The rule stratified patients into 6 levels of risk based on the total risk score. The spread in probability between the lowest and highest risk groups of having a major adverse outcome was 1.7% to 32.3% in the derivation set and 2.2% to 22.3% in the validation set. The prediction model performed well in both outcome discrimination and calibration. Thus, this clinical prediction rule allows accurate stratification of potential CABG candidates before surgery according to the risk of experiencing a major adverse outcome postoperatively.