Association networks in a matched case-control design - Co-occurrence patterns of preexisting chronic medical conditions in patients with major depression versus their matched controls.

OBJECTIVE: We present a method for comparing association networks in a matched case-control design, which provides a high-level comparison of co-occurrence patterns of features after adjusting for confounding factors. We demonstrate this approach by examining the differential distribution of chronic medical conditions in patients with major depressive disorder (MDD) compared to the distribution of these conditions in their matched controls. MATERIALS AND METHODS: Newly diagnosed MDD patients were matched to controls based on their demographic characteristics, socioeconomic status, place of residence, and healthcare service utilization in the Korean National Health Insurance Service's National Sample Cohort. Differences in the networks of chronic medical conditions in newly diagnosed MDD cases treated with antidepressants, and their matched controls, were prioritized with a permutation test accounting for the false discovery rate. Sensitivity analyses for the associations between prioritized pairs of chronic medical conditions and new MDD diagnosis were performed with regression modeling. RESULTS: By comparing the association networks of chronic medical conditions in newly diagnosed depression patients and their matched controls, five pairs of such conditions were prioritized among 105 possible pairs after controlling the false discovery rate at 5%. In sensitivity analyses using regression modeling, four out of the five prioritized pairs were statistically significant for the interaction terms. CONCLUSION: Association networks in a matched case-control design can provide a high-level comparison of comorbid features after adjusting for confounding factors, thereby supplementing traditional clinical study approaches. We demonstrate the differential co-occurrence pattern of chronic medical conditions in patients with MDD and prioritize the chronic conditions that have statistically significant interactions in regression models for depression.

Association of restless legs syndrome and mortality in end-stage renal disease: an analysis of the United States Renal Data System (USRDS).

BACKGROUND: Objective of the study is to assess prevalence and survival among end stage renal disease patients with restless legs syndrome (RLS) within a national database (USRDS). METHODS: A case-control, retrospective analysis was performed. Differences in characteristics between the groups, RLS and those with no sleep disorder (NSD), were determined using χ2 tests. Cox proportional hazard regression was used to assess survival between those with RLS and propensity score matched controls. RESULTS: Cases of restless legs syndrome were defined as patients that had received an ICD-9 code of 333.94 at any point during their treatment (n = 372). RLS group demonstrated a significantly higher proportion of patients with major depressive disorder, dysthymic disorder, anxiety, depression, minor depressive disorder, and psychological disorder. The difference between the survival was not statistically significant in those without sleep disorder as compared to those with RLS (HR =1.16±0.14, p = 0.3). CONCLUSIONS: True prevalence of RLS in dialysis patients can only be estimated if knowledge gap for care providers in diagnosis of RLS is addressed. RLS patients also have increased incidence of certain psychological disorders which needs to be addressed.

Cross-sectional examination of metabolites and metabolic phenotypes in uremia.

BACKGROUND: Although metabolomic approaches have begun to document numerous changes that arise in end stage renal disease (ESRD), how these alterations relate to established metabolic phenotypes in uremia is unknown. METHODS: In 200 incident hemodialysis patients we used partial least squares discriminant analysis to identify which among 166 metabolites could best discriminate individuals with or without diabetes, and across tertiles of body mass index, serum albumin, total cholesterol, and systolic blood pressure. RESULTS: Our data do not recapitulate metabolomic signatures of diabetes and obesity identified among individuals with normal renal function (e.g. elevations in branched chain and aromatic amino acids) and highlight several potential markers of diabetes status specific to ESRD, including xanthosine-5-phosphate and vanillylmandelic acid. Further, our data identify significant associations between elevated tryptophan and long-chain acylcarnitine levels and both decreased total cholesterol and systolic blood pressure in ESRD. Higher tryptophan levels were also associated with higher serum albumin levels, but this may reflect tryptophan's significant albumin binding. Finally, an examination of the uremic retention solutes captured by our platform in relation to 24 clinical phenotypes provides a framework for investigating mechanisms of uremic toxicity. CONCLUSIONS: In sum, these studies leveraging metabolomic and metabolic phenotype data acquired in a well-characterized ESRD cohort demonstrate striking differences from metabolomics studies in the general population, and may provide clues to novel functional pathways in the ESRD population.

The Effects of Parenteral Amino Acid Therapy on Protein Carbamylation in Maintenance Hemodialysis Patients.

OBJECTIVE: Protein carbamylation is a urea-driven post-translational protein modification associated with mortality in dialysis patients. Free amino acids (AAs) are competitive inhibitors of protein carbamylation and animal studies suggest increasing AA concentrations reduces carbamylation burden. We hypothesized that AA therapy in maintenance hemodialysis patients would reduce carbamylation, carrying the potential to improve clinical outcomes. DESIGN: Prospective pilot clinical trial (NCT1612429). SETTING: The study was conducted from March 2013 to March 2014 in outpatient dialysis facilities in the Boston metropolitan area. SUBJECTS AND INTERVENTION: We enrolled 23 consecutively consenting hemodialysis subjects, infusing the first 12 individuals with 250 cc of AAs 3 times per week postdialysis over 8 weeks. The remaining 11 subjects served as controls. MAIN OUTCOME MEASURE: Change in carbamylated albumin (C-Alb), a measure of total body carbamylation burden, between baseline and 8 weeks was the primary outcome. RESULTS: The treated and control groups had similar clinical characteristics and similar baseline C-Alb levels (mean ± SE 9.5 ± 2.4 and 9.3 ± 1.3 mmol/mol, respectively; P = .61). The treated arm showed a significant reduction in C-Alb compared with controls at 4 weeks (8.4% reduction in the treated arm vs. 4.3% increase in controls; P = .03) and the effect was greater by 8 weeks (15% reduction in the treated vs. 1% decrease in controls; P = .01). CONCLUSION: In this pilot study, AA therapy appeared safe and effective at reducing C-Alb levels in hemodialysis patients compared with no treatment. The impact of reduced protein carbamylation on clinical outcomes should be further investigated.

Social determinants of health in mental health care and research: a case for greater inclusion.

Social determinants of health (SDOH) are known to influence mental health outcomes, which are independent risk factors for poor health status and physical illness. Currently, however, existing SDOH data collection methods are ad hoc and inadequate, and SDOH data are not systematically included in clinical research or used to inform patient care. Social contextual data are rarely captured prospectively in a structured and comprehensive manner, leaving large knowledge gaps. Extraction methods are now being developed to facilitate the collection, standardization, and integration of SDOH data into electronic health records. If successful, these efforts may have implications for health equity, such as reducing disparities in access and outcomes. Broader use of surveys, natural language processing, and machine learning methods to harness SDOH may help researchers and clinical teams reduce barriers to mental health care.

Risk Factors for Depression Among Civilians After the 9/11 World Trade Center Terrorist Attacks: A Systematic Review and Meta-Analysis.

INTRODUCTION: The development of depressive symptoms among the population of civilians who were not directly involved in recovery or rescue efforts following the 9/11 World Trade Center (WTC) terrorist attacks is not comprehensively understood. We performed a meta-analysis that examined the associations between multiple risk factors and depressive symptoms after the 9/11 WTC terrorist attacks in New York City among civilians including survivors, residents, and passersby. METHODS: PubMed, Google Scholar, and the Cochrane Library were searched from September, 2001 through July, 2016. Reviewers identified eligible studies and synthesized odds ratios (ORs) using a random-effects model. RESULTS: The meta-analysis included findings from 7 studies (29,930 total subjects). After adjusting for multiple comparisons, depressive symptoms were significantly associated with minority race/ethnicity (OR, 1.40; 99.5% Confidence Interval [CI], 1.04 to 1.88), lower income level (OR, 1.25; 99.5% CI, 1.09 to 1.43), post-9/11 social isolation (OR, 1.68; 99.5% CI, 1.13 to 2.49), post-9/11 change in employment (OR, 2.06; 99.5% CI, 1.30 to 3.26), not being married post-9/11 (OR, 1.59; 99.5% CI, 1.18 to 2.15), and knowing someone injured or killed (OR, 2.02; 99.5% CI, 1.42 to 2.89). Depressive symptoms were not significantly associated with greater age (OR, 0.86; 99.5% CI, 0.70 to 1.05), no college degree (OR, 1.32; 99.5% CI, 0.96 to 1.83), female sex (OR, 1.24; 99.5% CI, 0.98 to 1.59), or direct exposure to WTC related traumatic events (OR, 1.26; 99.5% CI, 0.69 to 2.30). DISCUSSION: Findings from this study suggest that lack of post-disaster social capital was most strongly associated with depressive symptoms among the civilian population after the 9/11 WTC terrorist attacks, followed by bereavement and lower socioeconomic status. These risk factors should be identified among civilians in future disaster response efforts.

Using electronic health records to characterize prescription patterns: focus on antidepressants in nonpsychiatric outpatient settings.

OBJECTIVE: To characterize nonpsychiatric prescription patterns of antidepressants according to drug labels and evidence assessments (on-label, evidence-based, and off-label) using structured outpatient electronic health record (EHR) data. METHODS: A retrospective analysis was conducted using deidentified EHR data from an outpatient practice at a New York City-based academic medical center. Structured "medication-diagnosis" pairs for antidepressants from 35 325 patients between January 2010 and December 2015 were compared to the latest drug product labels and evidence assessments. RESULTS: Of 140 929 antidepressant prescriptions prescribed by primary care providers (PCPs) and nonpsychiatry specialists, 69% were characterized as "on-label/evidence-based uses." Depression diagnoses were associated with 67 233 (48%) prescriptions in this study, while pain diagnoses were slightly less common (35%). Manual chart review of "off-label use" prescriptions revealed that on-label/evidence-based diagnoses of depression (39%), anxiety (25%), insomnia (13%), mood disorders (7%), and neuropathic pain (5%) were frequently cited as prescription indication despite lacking ICD-9/10 documentation. CONCLUSIONS: The results indicate that antidepressants may be prescribed for off-label uses, by PCPs and nonpsychiatry specialists, less frequently than believed. This study also points to the fact that there are a number of off-label uses that are efficacious and widely accepted by expert clinical opinion but have not been included in drug compendia. Despite the fact that diagnosis codes in the outpatient setting are notoriously inaccurate, our approach demonstrates that the correct codes are often documented in a patient's recent diagnosis history. Examining both structured and unstructured data will help to further validate findings. Routinely collected clinical data in EHRs can serve as an important resource for future studies in investigating prescribing behaviors in outpatient clinics.

Understanding the research landscape of major depressive disorder via literature mining: an entity-level analysis of PubMed data from 1948 to 2017.

OBJECTIVE: To analyze literature-based data from PubMed to identify diseases and medications that have frequently been studied with major depressive disorder (MDD). MATERIALS AND METHODS: Abstracts of 23 799 research articles about MDD that have been published since 1948 till 2017 were analyzed using data and text mining approaches. Methods such as information extraction, frequent pattern mining, regression, and burst detection were used to explore diseases and medications that have been associated with MDD. RESULTS: In addition to many mental disorders and antidepressants, we identified several nonmental health diseases and nonpsychotropic medications that have frequently been studied with MDD. Our results suggest that: (1) MDD has been studied with disorders such as Pain, Diabetes Mellitus, Wounds and Injuries, Hypertension, and Cardiovascular Diseases; (2) medications such as Hydrocortisone, Dexamethasone, Ketamine, and Lithium have been studied in terms of their side effects and off-label uses; (3) the relationships between nonmental disorders and MDD have gained increased attention from the scientific community; and (4) the bursts of Diabetes Mellitus and Cardiovascular Diseases explain the psychiatric and/or depression screening recommended by authoritative associations during the periods of the bursts. DISCUSSION AND CONCLUSION: This study summarized and presented an overview of the previous MDD research in terms of diseases and medications that are highly relevant to MDD. The reported results can potentially facilitate hypothesis generation for future studies. The approaches proposed in the study can be used to better understand the progress and advance of the field.

Ascertaining Depression Severity by Extracting Patient Health Questionnaire-9 (PHQ-9) Scores from Clinical Notes.

The Patient Health Questionnaire-9 (PHQ-9) is a validated instrument for assessing depression severity. While some electronic health record (EHR) systems capture PHQ-9 scores in a structured format, unstructured clinical notes remain the only source in many settings, which presents data retrieval challenges for research and clinical decision support. To address this gap, we extended the open-source Leo natural language processing (NLP) platform to extract PHQ-9 scores from clinical notes and evaluated performance using EHR data for n=123,703 patients who were prescribed antidepressants. Compared to a reference standard, the NLP method exhibited high accuracy (97%), sensitivity (98%), precision (97%), and F-score (97%). Furthermore, of patients with PHQ-9 scores identified by the NLP method, 31% (n=498) had at least one PHQ-9 score clinically indicative of major depressive disorder (MDD), but lacked a structured ICD-9/10 diagnosis code for MDD. This NLP technique may facilitate accurate identification and stratification of patients with depression.

Prognosis of Acute Kidney Injury and Hepatorenal Syndrome in Patients with Cirrhosis: A Prospective Cohort Study.

Background/Aims. Acute kidney injury is a common problem for patients with cirrhosis and is associated with poor survival. We aimed to examine the association between type of acute kidney injury and 90-day mortality. Methods. Prospective cohort study at a major US liver transplant center. A nephrologist's review of the urinary sediment was used in conjunction with the 2007 Ascites Club Criteria to stratify acute kidney injury into four groups: prerenal azotemia, hepatorenal syndrome, acute tubular necrosis, or other. Results. 120 participants with cirrhosis and acute kidney injury were analyzed. Ninety-day mortality was 14/40 (35%) with prerenal azotemia, 20/35 (57%) with hepatorenal syndrome, 21/36 (58%) with acute tubular necrosis, and 1/9 (11%) with other (p = 0.04 overall). Mortality was the same in hepatorenal syndrome compared to acute tubular necrosis (p = 0.99). Mortality was lower in prerenal azotemia compared to hepatorenal syndrome (p = 0.05) and acute tubular necrosis (p = 0.04). Ten participants (22%) were reclassified from hepatorenal syndrome to acute tubular necrosis because of granular casts on urinary sediment. Conclusions. Hepatorenal syndrome and acute tubular necrosis result in similar 90-day mortality. Review of urinary sediment may add important diagnostic information to this population. Multicenter studies are needed to validate these findings and better guide management.

Nutritional vitamin D supplementation in dialysis: a randomized trial.

BACKGROUND AND OBJECTIVES: Vitamin D (25-hydroxyvitamin D; 25[OH]D) deficiency is common in patients initiating long-term hemodialysis, but the safety and efficacy of nutritional vitamin D supplementation in this population remain uncertain. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This randomized, placebo-controlled, parallel-group multicenter trial compared two doses of ergocalciferol with placebo between October 2009 and March 2013. Hemodialysis patients (n=105) with 25(OH)D levels ≤32 ng/ml from 32 centers in the Northeast United States were randomly assigned to oral ergocalciferol, 50,000 IU weekly (n=36) or monthly (n=33), or placebo (n=36) for a 12-week treatment period. The primary endpoint was the achievement of vitamin D sufficiency (25[OH]D >32 ng/ml) at the end of the 12-week treatment period. Survival was assessed through 1 year. RESULTS: Baseline characteristics were similar across all arms, with overall mean±SD 25(OH)D levels of 21.9±6.9 ng/ml. At 12 weeks, vitamin D sufficiency (25[OH]D >32 ng/ml) was achieved in 91% (weekly), 66% (monthly), and 35% (placebo) (P<0.001). Mean 25(OH)D was significantly higher in both the weekly (49.8±2.3 ng/ml; P<0.001) and monthly (38.3±2.4 ng/ml; P=0.001) arms compared with placebo (27.4±2.3 ng/ml). Calcium, phosphate, parathyroid hormone levels, and active vitamin D treatment did not differ between groups. All-cause and cause-specific hospitalizations and adverse events were similar between groups during the intervention period. Lower all-cause mortality among ergocalciferol-treated participants was not statistically significant (hazard ratio, 0.28; 95% confidence interval, 0.07 to 1.19). CONCLUSIONS: Oral ergocalciferol can increase 25(OH)D levels in incident hemodialysis patients without significant alterations in blood calcium, phosphate, or parathyroid hormone during a 12-week period.

Carbamylation of serum albumin and erythropoietin resistance in end stage kidney disease.

BACKGROUND AND OBJECTIVES: The mechanisms underlying erythropoietin resistance are not fully understood. Carbamylation is a post-translational protein modification that can alter the function of proteins, such as erythropoietin. The hypothesis of this study is that carbamylation burden is independently associated with erythropoietin resistance. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In a nonconcurrent prospective cohort study of incident hemodialysis patients in the United States, carbamylated albumin, a surrogate of overall carbamylation burden, in 158 individuals at day 90 of dialysis initiation and erythropoietin resistance index (defined as average weekly erythropoietin dose [U] per kg body weight per hemoglobin [g/dl]) over the subsequent 90 days were measured. Linear regression was used to describe the relationship between carbamylated albumin and erythropoietin resistance index. Logistic regression characterized the relationship between erythropoietin resistance index, 1-year mortality, and carbamylation. RESULTS: The median percent carbamylated albumin was 0.77% (interquartile range=0.58%-0.93%). Median erythropoietin resistance index was 18.7 units/kg per gram per deciliter (interquartile range=8.1-35.6 units/kg per gram per deciliter). Multivariable adjusted analysis showed that the highest quartile of carbamylated albumin was associated with a 72% higher erythropoietin resistance index compared with the lowest carbamylation quartile (P=0.01). Increasing erythropoietin resistance index was associated with a higher risk of death (odds ratio per unit increase in log-erythropoietin resistance index, 1.69; 95% confidence interval, 1.06 to 2.70). However, the association between erythropoietin resistance index and mortality was no longer statistically significant when carbamylation was included in the analysis (odds ratio, 1.44; 95% confidence interval, 0.87 to 2.37), with carbamylation showing the dominant association with death (odds ratio for high versus low carbamylation quartile, 4.53; 95% confidence interval, 1.20 to 17.10). CONCLUSION: Carbamylation was associated with higher erythropoietin resistance index in incident dialysis patients and a better predictor of mortality than erythropoietin resistance index.

A plasma long-chain acylcarnitine predicts cardiovascular mortality in incident dialysis patients.

BACKGROUND: The marked excess in cardiovascular mortality that results from uremia remains poorly understood. METHODS AND RESULTS: In 2 independent, nested case-control studies, we applied liquid chromatography-mass spectrometry-based metabolite profiling to plasma obtained from participants of a large cohort of incident hemodialysis patients. First, 100 individuals who died of a cardiovascular cause within 1 year of initiating hemodialysis (cases) were randomly selected along with 100 individuals who survived for at least 1 year (controls), matched for age, sex, and race. Four highly intercorrelated long-chain acylcarnitines achieved the significance threshold adjusted for multiple testing (P<0.0003). Oleoylcarnitine, the long-chain acylcarnitine with the strongest association with cardiovascular mortality in unadjusted analysis, remained associated with 1-year cardiovascular death after multivariable adjustment (odds ratio per SD 2.3 [95% confidence interval, 1.4 to 3.8]; P=0.001). The association between oleoylcarnitine and 1-year cardiovascular death was then replicated in an independent sample (n=300, odds ratio per SD 1.4 [95% confidence interval, 1.1 to 1.9]; P=0.008). Addition of oleoylcarnitine to clinical variables improved cardiovascular risk prediction using net reclassification (NRI, 0.38 [95% confidence interval, 0.20 to 0.56]; P<0.0001). In physiologic profiling studies, we demonstrate that the fold change in plasma acylcarnitine levels from the aorta to renal vein and from pre- to posthemodialysis samples exclude renal or dialytic clearance of long-chain acylcarnitines as confounders in our analysis. CONCLUSIONS: Our data highlight clinically meaningful alterations in acylcarnitine homeostasis at the time of dialysis initiation, which may represent an early marker, effector, or both of uremic cardiovascular risk.