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Background: Patients undergoing amputation of the lower extremity for the complications of peripheral artery disease and/or diabetes are at risk of treatment failure and the need for reamputation at a higher level. The aim of this study was to develop a patient‐specific reamputation risk prediction model. Methods: Patients with incident unilateral transmetatarsal, transtibial or transfemoral amputation between 2004 and 2014 secondary to diabetes and/or peripheral artery disease, and who survived 12 months after amputation, were identified using Veterans Health Administration databases. Procedure codes and natural language processing were used to define subsequent ipsilateral reamputation at the same or higher level. Stepdown logistic regression was used to develop the prediction model. It was then evaluated for calibration and discrimination by evaluating the goodness of fit, area under the receiver operating characteristic curve (AUC) and discrimination slope. Results: Some 5260 patients were identified, of whom 1283 (24·4 per cent) underwent ipsilateral reamputation in the 12 months after initial amputation. Crude reamputation risks were 40·3, 25·9 and 9·7 per cent in the transmetatarsal, transtibial and transfemoral groups respectively. The final prediction model included 11 predictors (amputation level, sex, smoking, alcohol, rest pain, use of outpatient anticoagulants, diabetes, chronic obstructive pulmonary disease, white blood cell count, kidney failure and previous revascularization), along with four interaction terms. Evaluation of the prediction characteristics indicated good model calibration with goodness‐of‐fit testing, good discrimination (AUC 0·72) and a discrimination slope of 11·2 per cent. Conclusion: A prediction model was developed to calculate individual risk of primary healing failure and the need for reamputation surgery at each amputation level. This model may assist clinical decision‐making regarding amputation‐level selection. [ABSTRACT FROM AUTHOR]

Background: Patients who undergo lower extremity amputation secondary to the complications of diabetes or peripheral artery disease have poor long‐term survival. Providing patients and surgeons with individual‐patient, rather than population, survival estimates provides them with important information to make individualized treatment decisions. Methods: Patients with peripheral artery disease and/or diabetes undergoing their first unilateral transmetatarsal, transtibial or transfemoral amputation were identified in the Veterans Affairs Surgical Quality Improvement Program (VASQIP) database. Stepdown logistic regression was used to develop a 1‐year mortality risk prediction model from a list of 33 candidate predictors using data from three of five Department of Veterans Affairs national geographical regions. External geographical validation was performed using data from the remaining two regions. Calibration and discrimination were assessed in the development and validation samples. Results: The development sample included 5028 patients and the validation sample 2140. The final mortality prediction model (AMPREDICT‐Mortality) included amputation level, age, BMI, race, functional status, congestive heart failure, dialysis, blood urea nitrogen level, and white blood cell and platelet counts. The model fit in the validation sample was good. The area under the receiver operating characteristic (ROC) curve for the validation sample was 0·76 and Cox calibration regression indicated excellent calibration (slope 0·96, 95 per cent c.i. 0·85 to 1·06; intercept 0·02, 95 per cent c.i. –0·12 to 0·17). Given the external validation characteristics, the development and validation samples were combined, giving a total sample of 7168. Conclusion: The AMPREDICT‐Mortality prediction model is a validated parsimonious model that can be used to inform the 1‐year mortality risk following non‐traumatic lower extremity amputation of patients with peripheral artery disease or diabetes. [ABSTRACT FROM AUTHOR]

Obesity is a major health problem in the United States and a growing concern among members of the military. Posttraumatic stress disorder (PTSD) has been associated with overweight and obesity and may increase the risk of those conditions among military service members. Disordered eating behaviors have also been associated with PTSD and weight gain. However, eating disorders remain understudied in military samples. We investigated longitudinal associations among PTSD, disordered eating, and weight gain in the Millennium Cohort Study, which includes a nationally representative sample of male (n = 27,741) and female (n = 6,196) service members. PTSD at baseline (time 1; 2001-2003) was associated with disordered eating behaviors at time 2 (2004-2006), as well as weight change from time 2 to time 3 (2007-2008). Structural equation modeling results revealed that the association between PTSD and weight change from time 2 to time 3 was mediated by disordered eating symptoms. The association between PTSD and weight gain resulting from compensatory behaviors (vomiting, laxative use, fasting, overexercise) was significant for white participants only and for men but not women. PTSD was both directly and indirectly (through disordered eating) associated with weight change. These results highlight potentially important demographic differences in these associations and emphasize the need for further investigation of eating disorders in military service members. [ABSTRACT FROM AUTHOR]

Whether or not age by itself increases susceptibility to pneumococcal infections separate from the effects of chronic disease is controversial. To address this issue, data collected for a retrospective cohort study of pneumococcal infections among 63 middle-aged and older veterans and 126 uninfected controls were reanalysed. Univariate analysis suggested a linear increase in risk with increasing age for patients 50 years old and older (p = 0.03). Subjects over age 80 years seemed to be at particularly high risk when compared with patients under 50 (odds ratio = 4.3, p less than 0.03). The odds of pneumococcal infection increased by an estimated factor of 1.33 (95% confidence interval = 1.03, 1.71) for each 10-year increase in age. Controlling for other risk factors did not appreciably change the point estimate of the age effect, but statistical significance was lost. This result however suggests that age has an independent association with the risk of pneumococcal infections. The potential impact of this finding on public policy urges that the association of age with the risk of pneumococcal disease be re-examined in a study of sufficient sample size to resolve the issue. [ABSTRACT FROM AUTHOR]