One-Year Mortality after Contemporary Laparoscopic Bariatric Surgery: An Analysis of the Bariatric Outcomes Longitudinal Database.

BACKGROUND:Contemporary mortality after bariatric surgery is low and has been decreasing over the past 2 decades. Most studies have reported inpatient or 30-day mortality, which may not represent the true risk of bariatric surgery. The objective of this study was to examine 1-year mortality and factors predictive of 1-year mortality after contemporary laparoscopic bariatric surgery. STUDY DESIGN:Using the 2008 to 2012 Bariatric Outcomes Longitudinal Database (BOLD), data from 158,606 operations were analyzed, including 128,349 (80.9%) laparoscopic Roux-en-Y gastric bypass (LRYGB) and 30,257 (19.1%) laparoscopic sleeve gastrectomy (LSG) operations. Multivariate logistic regression was used to determine independent risk factors associated with 1-year mortality for each type of procedure. RESULTS:The 30-day and 1-year mortality rates for LRYGB were 0.13% and 0.23%, respectively, and for LSG were 0.06% and 0.11%, respectively. Risk factors for 1-year mortality included older age (LRYGB: adjusted odds ratio [AOR] 1.05 per year, p < 0.001; LSG: AOR 1.08 per year, p < 0.001); male sex (LRYGB: AOR 1.88, p < 0.001); higher BMI (LRYGB: AOR 1.04 per unit, p < 0.001; LSG: AOR 1.05 per unit, p = 0.009); and the presence of 30-day leak (LRYGB: AOR 25.4, p < 0.001; LSG: AOR 35.8, p < 0.001), 30-day pulmonary embolism (LRYGB: AOR 34.5, p < 0.001; LSG: AOR 252, p < 0.001), and 30-day hemorrhage (LRYGB: AOR 2.34, p = 0.001). CONCLUSIONS:Contemporary 1-year mortality after laparoscopic bariatric surgery is much lower than previously reported, at <0.25%. It is important to continually refine techniques and perioperative management in order to minimize leaks, hemorrhage, and pulmonary embolus after bariatric surgery because these complications contribute to a higher risk of mortality

Rejoinder: Time-dynamic profiling with application to hospital readmission among patients on dialysis.

Standard profiling analysis aims to evaluate medical providers, such as hospitals, nursing homes, or dialysis facilities, with respect to a patient outcome. The outcome, for instance, may be mortality, medical complications, or 30-day (unplanned) hospital readmission. Profiling analysis involves regression modeling of a patient outcome, adjusting for patient health status at baseline, and comparing each provider's outcome rate (e.g., 30-day readmission rate) to a normative standard (e.g., national "average"). Profiling methods exist mostly for non time-varying patient outcomes. However, for patients on dialysis, a unique population which requires continuous medical care, methodologies to monitor patient outcomes continuously over time are particularly relevant. Thus, we introduce a novel time-dynamic profiling (TDP) approach to assess the time-varying 30-day readmission rate. TDP is used to estimate, for the first time, the risk-standardized time-dynamic 30-day hospital readmission rate, throughout the time period that patients are on dialysis. We develop the framework for TDP by introducing the standardized dynamic readmission ratio as a function of time and a multilevel varying coefficient model with facility-specific time-varying effects. We propose estimation and inference procedures tailored to the problem of TDP and to overcome the challenge of high-dimensional parameters when examining thousands of dialysis facilities

Dialysate Potassium and Mortality in a Prospective Hemodialysis Cohort.

BackgroundStudies examining the association of dialysate potassium concentration and mortality in hemodialysis patients show conflicting findings. We hypothesized that low dialysate potassium concentrations are associated with higher mortality, particularly in patients with high pre-dialysis serum potassium concentrations.MethodsWe evaluated 624 hemodialysis patients from the prospective Malnutrition, Diet, and Racial Disparities in Kidney Disease study recruited from 16 outpatient dialysis facilities over 2011-2015 who underwent protocolized collection of dialysis treatment characteristics every 6 months. We examined the association of dialysate potassium concentration, categorized as 1, 2, and 3 mEq/L, with all-cause mortality risk in the -overall cohort, and stratified by pre-dialysis serum potassium (< 5 vs. ≥5 mEq/L) using case-mix adjusted Cox models.ResultsIn baseline analyses, dialysate potassium concentrations of 1 mEq/L were associated with higher mortality, whereas concentrations of 3 mEq/L were associated with similar mortality in the overall cohort (reference: 2 mEq/L): adjusted hazard ratios (aHRs; 95% CI) 1.70 (1.01-2.88) and 0.95 (0.64-1.39), respectively. In analyses stratified by serum potassium, baseline dialysate potassium concentrations of 1 mEq/L were associated with higher mortality in patients with serum potassium ≥5 mEq/L but not in those with serum potassium < 5 mEq/L: aHRs (95% CI) 2.87 (1.51-5.46) and 0.74 (0.27-2.07), respectively (p interaction = 0.04). These findings were robust with incremental adjustment for serum potassium, potassium-binding resins, and potassium-modifying medications.ConclusionLow (1 mEq/L) dialysate potassium -concentrations were associated with higher mortality, particularly in hemodialysis patients with high pre-dialysis serum potassium. Further studies are needed to identify therapeutic strategies that mitigate inter-dialytic serum potassium accumulation and subsequent high dialysate serum potassium gradients in this population

Association of thyroid status prior to transition to end-stage renal disease with early dialysis mortality.

BackgroundAdvanced chronic kidney disease (CKD) patients, including those receiving dialysis, have a high prevalence of thyroid dysfunction. Although hypothyroidism is associated with higher death risk in end-stage renal disease (ESRD) patients, no studies have examined whether thyroid status in the pre-ESRD period impacts mortality after dialysis initiation.MethodsAmong US veterans with CKD identified from the national Veterans Affairs database that transitioned to dialysis over the period from October 2007 to September 2011, we examined the association of pre-ESRD serum thyrotropin (TSH) levels averaged over the 1-year pre-dialysis ('prelude') period with all-cause mortality in the first year following dialysis initiation.ResultsAmong 15 335 patients in the 1-year prelude cohort, TSH levels >5.0 mIU/L were associated with higher mortality in expanded case-mix Cox models (reference: TSH 0.5-5.0 mIU/L): adjusted hazard ratio (aHR) [95% confidence interval (CI) 1.20 (1.07-1.33). Similar findings were observed for TSH >5.0 mIU/L and mortality in the 2- and 5-year cohorts: aHRs (95% CI) 1.11 (1.02-1.21) and 1.15 (1.07-1.24), respectively. Analyses of finer gradations of TSH in the 1-year prelude cohort demonstrated that incrementally higher levels >5.0 mIU/L were associated with increasingly higher mortality in expanded case-mix models (reference: TSH 0.5-3.0 mIU/L): aHRs (95% CI) 1.18 (1.04-1.33) and 1.28 (1.03-1.59) for TSH levels >5.0-10.0 mIU/L and >10.0 mIU/L, respectively. In the 2- and 5-year cohorts, mortality associations persisted most strongly for those with TSH >10.0 mIU/L, particularly after laboratory covariate adjustment.ConclusionsAmong new ESRD patients, there is a dose-dependent relationship between higher pre-ESRD TSH levels >5.0 mIU/L and post-ESRD mortality. Further studies are needed to determine the impact of TSH reduction with thyroid hormone supplementation in this population

Predialysis Kidney Function and Its Rate of Decline Predict Mortality and Hospitalizations After Starting Dialysis.

ObjectiveTo determine whether kidney function level and its rate of decline in the immediate predialysis period among veterans transitioning to end-stage renal disease (ESRD) predict postdialysis mortality and hospitalization.Patients and methodsIn 19,985 veterans transitioning to ESRD during the period October 1, 2007, to March 30, 2014, we examined kidney function and its slope over the final year of the pre-ESRD(prelude) period. Two categories of low vs high estimated glomerular filtration rate (eGFR, dichotomized at 10 mL/min/1.73 m2) and slow vs fast slope (dichotomized at -10 mL/min/1.73 m2/y) were combined into 4 groups. Their associations with 12-month post-ESRD all-cause and cardiovascular (CV) mortality and hospitalization rates were examined in adjusted models accounting for clinical characteristics and laboratory measurements at transition.ResultsPatients, 66±11 years old, and 34% blacks, had a median (interquartile range) eGFR at transition and slope of 9.7 (7.1-13.3) mL/min/1.73 m2 and -10.5 (-18.8 to -5.9) mL/min/1.73 m2/y, respectively. Patients with a low eGFR and slow slope had the lowest 12-month all-cause and CV mortality risks and hospitalization rate. Conversely, patients with high eGFR and fast slope had the highest risk of all-cause and CV mortality and hospitalization rate compared with patients with a low eGFR and slow slope. This relationship persisted in sensitivity analyses, including propensity scoring.ConclusionA kidney profile of a low eGFR and slow slope in the prelude period is associated with favorable early dialysis outcomes in veteran patients. Trials to examine a more conservative approach to dialysis are warranted

Thyroid Status and Death Risk in US Veterans With Chronic Kidney Disease.

OBJECTIVE:Given that patients with non-dialysis-dependent chronic kidney disease (NDD-CKD) have a disproportionately higher prevalence of hypothyroidism compared with their non-CKD counterparts, we sought to determine the association between thyroid status, defined by serum thyrotropin (TSH) levels, and mortality among a national cohort of patients with NDD-CKD. PATIENTS AND METHODS:Among 227,422 US veterans with stage 3 NDD-CKD with 1 or more TSH measurements during the period October 1, 2004, to September 30, 2012, we first examined the association of thyroid status, defined by TSH categories of less than 0.5, 0.5 to 5.0 (euthyroidism), and more than 5.0 mIU/L, with all-cause mortality. We then evaluated 6 granular TSH categories: less than 0.1, 0.1 to less than 0.5, 0.5 to less than 3.0, 3.0 to 5.0, more than 5.0 to 10.0, and more than 10.0 mIU/L. We concurrently examined thyroid status, thyroid-modulating therapy, and mortality in sensitivity analyses. RESULTS:In expanded case-mix adjusted Cox analyses, compared with euthyroidism, baseline and time-dependent TSH levels of more than 5.0 mIU/L were associated with higher mortality (adjusted hazard ratios [aHRs] [95% CI], 1.19 [1.15-1.24] and 1.23 [1.19-1.28], respectively), as were baseline and time-dependent TSH levels of less than 0.5 mIU/L (aHRs [95% CI], 1.18 [1.15-1.22] and 1.41 [1.37-1.45], respectively). Granular examination of thyroid status showed that incrementally higher TSH levels of 3.0 mIU/L or more were associated with increasingly higher mortality in baseline and time-dependent analyses, and TSH categories of less than 0.5 mIU/L were associated with higher mortality (reference, 0.5-<3.0 mIU/L) in baseline analyses. In time-dependent analyses, untreated and undertreated hypothyroidism and untreated hyperthyroidism were associated with higher mortality (reference, spontaneous euthyroidism), whereas hypothyroidism treated-to-target showed lower mortality. CONCLUSION:Among US veterans with NDD-CKD, high-normal TSH (≥3.0 mIU/L) and lower TSH (<0.5 mIU/L) levels were associated with higher death risk. Interventional studies identifying the target TSH range associated with the greatest survival in patients with NDD-CKD are warranted

Development and Validation of a Novel Laboratory-Specific Correction Equation for Total Serum Calcium and Its Association With Mortality Among Hemodialysis Patients.

Conventional albumin-corrected calcium is inaccurate in predicting ionized calcium, and hidden hypercalcemia, characterized as high ionized calcium with normal total calcium, is associated with higher mortality in hemodialysis patients. By using a national cohort of hemodialysis patients in the Unites States, a novel laboratory-specific prediction equation composed of total calcium, albumin, and phosphorus was derived from 242 patients in the South Atlantic division (adjusted R2  = 0.80 versus 0.71 for the conventional equation) and then validated among 566 patients in the other divisions (adjusted R2  = 0.79 versus 0.68 for the conventional equation). Compared with the conventional equation, the novel equation showed a greater correlation with intact parathyroid hormone. Its relative performance against the conventional equation was consistent across subgroups based on medications related to calcium metabolism. The novel equation also had a higher sensitivity (57% versus 34%) and an equivalent specificity (99% versus 100%) against ionized hypercalcemia at a cut-off value of 10.2 mg/dL. Sensitivity and specificity at 9.4 mg/dL was 94% and 76% (versus 87% and 82% for the conventional equation), respectively. A survival analysis in 87,779 incident hemodialysis patients showed that among patients who were categorized as having a high-normal calcium status (ie, >9.4 to 10.2 mg/dL) by the conventional equation, there appeared a trend toward higher adjusted mortality risk across higher calcium status defined according to the novel equation. Meanwhile, the mortality risk was consistent across calcium strata defined according to the conventional equation within the categories defined by the novel equation. In conclusion, in comparison to the conventional equation, a novel laboratory-specific correction equation derived for correction of total calcium performs significantly better in ascertaining hidden hypercalcemia in hemodialysis patients, and aids in identifying patients at higher risk for mortality. © 2016 American Society for Bone and Mineral Research

Machine Learning to Identify Dialysis Patients at High Death Risk.

IntroductionGiven the high mortality rate within the first year of dialysis initiation, an accurate estimation of postdialysis mortality could help patients and clinicians in decision making about initiation of dialysis. We aimed to use machine learning (ML) by incorporating complex information from electronic health records to predict patients at risk for postdialysis short-term mortality.MethodsThis study was carried out on a contemporary cohort of 27,615 US veterans with incident end-stage renal disease (ESRD). We implemented a random forest method on 49 variables obtained before dialysis transition to predict outcomes of 30-, 90-, 180-, and 365-day all-cause mortality after dialysis initiation.ResultsThe mean (±SD) age of our cohort was 68.7 ± 11.2 years, 98.1% of patients were men, 29.4% were African American, and 71.4% were diabetic. The final random forest model provided C-statistics (95% confidence intervals) of 0.7185 (0.6994-0.7377), 0.7446 (0.7346-0.7546), 0.7504 (0.7425-0.7583), and 0.7488 (0.7421-0.7554) for predicting risk of death within the 4 different time windows. The models showed good internal validity and replicated well in patients with various demographic and clinical characteristics and provided similar or better performance compared with other ML algorithms. Results may not be generalizable to non-veterans. Use of predictors available in electronic medical records has limited the assessment of number of predictors.ConclusionWe implemented and ML-based method to accurately predict short-term postdialysis mortality in patients with incident ESRD. Our models could aid patients and clinicians in better decision making about the best course of action in patients approaching ESRD

Hypoglycemia-Related Hospitalizations and Mortality Among Patients With Diabetes Transitioning to Dialysis.

Rationale & objectiveDiabetic patients with declining kidney function are at heightened risk for hypoglycemia. We sought to determine whether hypoglycemia-related hospitalizations in the interval before dialysis therapy initiation are associated with post-end-stage renal disease (ESRD) mortality among incident patients with ESRD with diabetes.Study designObservational cohort study.Setting & participantsUS veterans from the national Veterans Affairs database with diabetes and chronic kidney disease transitioning to dialysis therapy from October 2007 to September 2011.ExposureHypoglycemia-related hospitalizations during the pre-ESRD period and antidiabetic medication regimens.OutcomeThe outcome of post-ESRD all-cause mortality was evaluated relative to pre-ESRD hypoglycemia. The outcome of pre-ESRD hypoglycemia-related hospitalization was evaluated relative to antidiabetic medication regimens.Analytic approachWe examined whether the occurrence and frequency of pre-ESRD hypoglycemia-related hospitalizations are associated with post-ESRD mortality using Cox regression models adjusted for case-mix covariates. In a subcohort of patients prescribed 0 to 2 oral antidiabetic drugs and/or insulin, we examined the 12 most commonly prescribed antidiabetic medication regimens and risk for pre-ESRD hypoglycemia-related hospitalization using logistic regression models adjusted for case-mix covariates.ResultsAmong 30,156 patients who met eligibility criteria, the occurrence of pre-ESRD hypoglycemia-related hospitalization(s) was associated with higher post-ESRD mortality risk: adjusted HR (aHR), 1.25; 95% CI, 1.17-1.34 (reference group: no hypoglycemia hospitalization). Increasing frequency of hypoglycemia-related hospitalizations was independently associated with incrementally higher mortality risk: aHRs of 1.21 (95% CI, 1.12-1.30), 1.47 (95% CI, 1.19-1.82), and 2.07 (95% CI, 1.46-2.95) for 1, 2, and 3 or more hypoglycemia-related hospitalizations, respectively (reference group: no hypoglycemia hospitalization). Compared with patients who were prescribed neither oral antidiabetic drugs nor insulin, medication regimens that included sulfonylureas and/or insulin were associated with higher risk for hypoglycemia.LimitationsResidual confounding cannot be excluded.ConclusionsAmong incident patients with ESRD with diabetes, a dose-dependent relationship between frequency of pre-ESRD hypoglycemia-related hospitalizations and post-ESRD mortality was observed. Further study of diabetic management strategies that prevent hypoglycemia as patients with chronic kidney disease transition to ESRD are warranted

Development and Validation of Prediction Scores for Early Mortality at Transition to Dialysis.

ObjectiveTo develop and validate a risk prediction model that would help individualize treatment and improve the shared decision-making process between clinicians and patients.Patients and methodsWe developed a risk prediction tool for mortality during the first year of dialysis based on pre-end-stage renal disease characteristics in a cohort of 35,878 US veterans with incident end-stage renal disease who transitioned to dialysis treatment between October 1, 2007, and March 31, 2014 and then externally validated this tool among 4284 patients in the Kaiser Permanente Southern California (KPSC) health care system who transitioned to dialysis treatment between January 1, 2007, and September 30, 2015.ResultsTo ensure model goodness of fit, 2 separate models were selected for patients whose last estimated glomerular filtration rate (eGFR) before dialysis initiation was less than 15 mL/min per 1.73 m2 or 15 mL/min per 1.73 m2 or higher. Model discrimination in the internal validation cohort of veterans resulted in C statistics of 0.71 (95% CI, 0.70-0.72) and 0.66 (95% CI, 0.65-0.67) among patients with eGFR lower than 15 mL/min per 1.73 m2 and 15 mL/min per 1.73 m2 or higher, respectively. In the KPSC external validation cohort, the developed risk score exhibited C statistics of 0.77 (95% CI, 0.74-0.79) in men and 0.74 (95% CI, 0.71-0.76) in women with eGFR lower than 15 mL/min per 1.73 m2 and 0.71 (95% CI, 0.67-0.74) in men and 0.67 (95% CI, 0.62-0.72) in women with eGFR of 15 mL/min per 1.73 m2 or higher.ConclusionA new risk prediction tool for mortality during the first year after transition to dialysis (available at www.DialysisScore.com) was developed in the large national Veterans Affairs cohort and validated with good performance in the racially, ethnically, and gender diverse KPSC cohort. This risk prediction tool will help identify high-risk populations and guide management strategies at the transition to dialysis