OBJECTIVE -To determine the mortality rate after diabetes-related lower-extremity amputation (LEA) in an African-descent Caribbean population.RESEARCH DESIGN AND METHODS -We conducted a prospective case-control study. We recruited case subjects (with diabetes and LEA) and age-matched control subjects (with diabetes and no LEA) between 1999 and 2001. We followed these groups for 5 years to assess mortality risk and causes.RESULTS -There were 205 amputations (123 minor and 82 major). The 1-year and 5-year survival rates were 69 and 44% among case subjects and 97 and 82% among control subjects (case-control difference, P Ͻ 0.001). The mortality rates (per 1,000 person-years) were 273.9 (95% CI 207.1-362.3) after a major amputation, 113.4 (85.2-150.9) after a minor amputation, and 36.4 (25.6 -51.8) among control subjects. Sepsis and cardiac disease were the most common causes of death.CONCLUSIONS -These mortality rates are the highest reported worldwide. Interventions to limit sepsis and complications from cardiac disease offer a huge potential for improving post-LEA survival in this vulnerable group.

The Revised Cardiac Risk Index in the new millennium: a single-centre prospective cohort re-evaluation of the original variables in 9,519 consecutive elective surgical patients L'indice de risque cardiaque modifié dans le nouveau millénaire: une réévaluation prospective et unicentrique de cohorte des variables originales chez 9519 patients consécutifs devant subir une chirurgie non urgente Abstract Purpose Cardiac complications following non-cardiac surgery are major causes of morbidity and mortality. The Revised Cardiac Risk Index (RCRI) has become a standard for predicting post-surgical cardiac complications. This study re-examined the original six risk factors to confirm their validity in a large modern prospective database.Methods Using the definitions in the original risk index, this study included 9,519 patients aged C 50 undergoing elective non-cardiac surgery with an expected length of stay C two days at two major tertiary-care teaching hospitals. The validity of the original predictors was tested in this population using binomial logistic regression modelling, area under the receiver operator curve (ROC) analysis, and the net reclassification index. Results Rates of major cardiac complications with 0, 1, 2, C 3 of the predictors were 0.5%, 2.6%, 7.2%, and 14.4%, respectively, in our patient cohort compared with 0.4%, 1.1%, 4.6%, and 9.7%, respectively, in the original cohort. Similar to the original report, binary logistic regression analysis showed that both preoperative treatment with insulin (odds ratio [OR] 1.4; 95% confidence interval [CI] 0.7 to 2.6) and preoperative creatinine [ 176.8 mmolÁL -1 (OR 1.7; 95% CI 0.8 to 3.6) did not improve the predictive ability of the index. Analysis of the remaining four factors resulted in an area under the curve (AUC) identical to that seen for the reconstructed six-factor RCRI (AUC = 0.79). We found that a Author contributions Christopher Davis organized and performed the analysis, wrote the first draft of the manuscript, and was responsible for major revisions to both the analysis and manuscript. Gordon Tait was responsible for creation of the database and the data integrity. He performed and or supervised quality checks on the data and helped perform the data analysis. Gordon Tait, Jo Carroll, and Duminda N. Wijeysundera made key revisions to the manuscript. Jo Carroll assisted in the creation of the database and quality control of the data. Duminda N. Wijeysundera and W. Scott Beattie were responsible in part for the concept of the study. Duminda N. Wijeysundera revised key aspects of the data analysis. W. Scott Beattie was responsible in part for supervision of the project. He obtained funding for the project, helped write all drafts of the manuscript, and made revisions to the data analysis. Dr. Beattie was Mr. Davis's summer elective supervisor. All authors have seen the data analysis and the revised manuscript and vouch for the authenticity of all aspects of this manuscript. glomerular filtration rate (GFR) \ 30 mLÁmin -1 was a better predictor of major...

PURPOSE Evidence suggests that patient-reported outcomes (PROs) from randomized trials in oncology may not influence clinical decision making and patient choice. Reasons for this are currently unclear and little is known about patients' interpretation of PROs. This study assessed patients' understanding of multidimensional PROs in a graphical format. PATIENTS AND METHODS Semistructured interviews in which patients interpreted a series of graphs depicting simple, then multiple different hypothetical PROs associated with two treatments with identical chances of survival were audio recorded. The interviewer and a blinded observer (listening to audio recordings) scored patients' understanding of the graphs. Logistic regression examined the associations between patient understanding of the graphs and clinical and sociodemographic details. Results One hundred thirty-two patients with esophageal and gastric cancer were interviewed and 115 understood the first two graphs depicting different PROs of two treatments (87%; 95% CI,81 to 93). Simultaneous interpretation of adverse and beneficial treatment effects was achieved by 74 (66%; 95% CI, 57 to 75). Graphs showing complex, longitudinal data were correctly interpreted by 97 (73%; 95% CI, 66 to 81) and 108 (81%; 95% CI, 75 to 88), respectively. Univariable analyses demonstrated associations between patient understanding and patient age, educational level, and cancer site (P < or = .02 for all); however, in a multivariable model each of these associations was attenuated. CONCLUSION Most patients understand graphical multidimensional PROs, although a smaller majority were able to interpret more complex, or simultaneous, presentations. Additional work is needed to define methods for communicating clinical and PRO data from trials to allow patients to make informed treatment choices.