Recipients of public assistance with advanced chronic kidney disease: insights into receiving a presentation of kidney replacement therapy options and polypharmacy from Japanese investigators with innovative network about kidney disease study.

BACKGROUND: The characteristics of patients with advanced chronic kidney disease (CKD) who are recipients of public assistance in Japan, and the adequacy of their medical care have not been reported previously. METHODS: The records of patients with CKD stage G5 who visited nine facilities in Japan from April to June 2013 were retrospectively reviewed to compare the characteristics and care of recipients of public assistance with those of non-recipients. Receiving a presentation of kidney replacement therapy (KRT) options and polypharmacy were used as indicators of suboptimal medical care. RESULTS: Of the 592 patients included in this analysis (mean age, 69.6 years; male, 59.3%), 56 (9.5%) were recipients of public assistance and 536 (90.5%) were non-recipients of public assistance. The prevalence of diabetes mellitus, unmarried status, and living alone were higher in recipients of public assistance. In multivariable logistic regression analysis, compared with non-recipients of public assistance, recipients of public assistance were less likely to receive a presentation of KRT options (adjusted odds ratio [aOR], 0.31; 95% confidence interval [CI], 0.17-0.56), and were more likely to receive ≥ 10 (aOR, 1.92; 95% CI, 1.05-3.51), and ≥ 15 (aOR, 2.78; 95% CI, 1.23-6.26) types of medication. CONCLUSIONS: Patients with advanced CKD receiving public assistance were less likely to receive a presentation of KRT options and more likely to receive ≥ 10 and ≥ 15 types of medication, suggesting that recipients of public assistance are more likely to receive suboptimal medical care.

Metabolome subtyping of severe bronchiolitis in infancy and risk of childhood asthma.

BACKGROUND: Infants with bronchiolitis are at increased risk for developing asthma. Growing evidence suggests bronchiolitis is a heterogeneous condition. OBJECTIVES: We sought to identify biologically distinct subgroups based on the metabolome signatures (metabotypes) in infants with severe bronchiolitis and to examine the longitudinal relationships of metabotypes with asthma development. METHODS: In a multicenter prospective cohort study of infants (age, <12 months) hospitalized for bronchiolitis, the nasopharyngeal airway metabolome was profiled at hospitalization. Using a clustering approach, this study identified mutually exclusive metabotypes. This study also examined their longitudinal association with the risk of developing asthma by 5 years of age. RESULTS: Of 918 infants hospitalized for bronchiolitis (median age, 3 months), this study identified 5 distinct metabotypes-characterized by their nasopharyngeal metabolome profile: A, glycerophosphocholine-high; B, amino acid-high, polyunsaturated fatty acid-low; C, amino acid-high, glycerophospholipid-low; D, glycerophospholipid-high; and E, mixed. Compared with infants with metabotype A (who clinically resembled "classic" bronchiolitis), infants with metabotype B had a significantly higher risk for developing asthma (23% vs 41%; adjusted odds ratio, 2.22; 95% CI, 1.07-4.69). The pathway analysis showed that metabotype B had enriched amino acid (eg, methionine, histidine, glutathione) and α-linolenic/linoleic acid metabolism pathways (false discovery rate, <5 × 10-14 for all). Finally, the transcriptome analysis revealed that infants with metabotype B had upregulated IFN-α and IL-6/JAK/STAT3 pathways and downregulated fatty acid metabolism pathways (false discovery rate, <0.05 for both). CONCLUSIONS: In this multicenter prospective cohort study of infants with severe bronchiolitis, the clustering analysis of metabolome data identified biologically distinct metabotypes, including a metabotype characterized by high inflammatory amino acids and low polyunsaturated fatty acids that is at significantly increased risk for developing asthma.

Nasopharyngeal airway dual-transcriptome of infants with severe bronchiolitis and risk of childhood asthma: A multicenter prospective study.

BACKGROUND: Severe bronchiolitis (ie, bronchiolitis requiring hospitalization) during infancy is a major risk factor for childhood asthma. However, the exact mechanism linking these common conditions remains unclear. OBJECTIVES: This study sought to examine the integrated role of airway microbiome (both taxonomy and function) and host response in asthma development in this high-risk population. METHODS: This multicenter prospective cohort study of 244 infants with severe bronchiolitis (median age, 3 months) examined the infants' nasopharyngeal metatranscriptomes (microbiomes) and transcriptomes (hosts), as well as metabolomes at hospitalization. The longitudinal relationships investigated include (1) major bacterial species (Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis), (2) microbial function, and (3) host response with risks of developing asthma by age 6 years. RESULTS: First, the abundance of S pneumoniae was associated with greater risks of asthma (P = .01), particularly in infants with nonrhinovirus infection (Pinteraction = .04). Second, of 328 microbial functional pathways that are differentially enriched by asthma development, the top pathways (eg, fatty acid and glycolysis pathways; false discovery rate [FDR] < 1 × 10-12) were driven by these 3 major species (eg, positive association of S pneumoniae with glycolysis; FDR < 0.001). These microbial functional pathways were validated with the parallel metabolome data. Third, 104 transcriptome pathways were differentially enriched (FDR < .05)-for example, downregulated interferon-α and -γ and upregulated T-cell activation pathways. S pneumoniae was associated with most differentially expressed transcripts (eg, DAGLB; FDR < 0.05). CONCLUSIONS: By applying metatranscriptomic, transcriptomic, and metabolomic approaches to a multicenter cohort of infants with bronchiolitis, this study found an interplay between major bacterial species, their function, and host response in the airway, and their longitudinal relationship with asthma development.

Nasopharyngeal lipidomic endotypes of infants with bronchiolitis and risk of childhood asthma: a multicentre prospective study.

BACKGROUND: Bronchiolitis is the leading cause of hospitalisation of US infants and an important risk factor for childhood asthma. Recent evidence suggests that bronchiolitis is clinically heterogeneous. We sought to derive bronchiolitis endotypes by integrating clinical, virus and lipidomics data and to examine their relationship with subsequent asthma risk. METHODS: This is a multicentre prospective cohort study of infants (age <12 months) hospitalised for bronchiolitis. We identified endotypes by applying clustering approaches to clinical, virus and nasopharyngeal airway lipidomic data measured at hospitalisation. We then determined their longitudinal association with the risk for developing asthma by age 6 years by fitting a mixed-effects logistic regression model. To account for multiple comparisons of the lipidomics data, we computed the false discovery rate (FDR). To understand the underlying biological mechanism of the endotypes, we also applied pathway analyses to the lipidomics data. RESULTS: Of 917 infants with bronchiolitis (median age, 3 months), we identified clinically and biologically meaningful lipidomic endotypes: (A) cinicalclassiclipidmixed (n=263), (B) clinicalseverelipidsphingolipids-high (n=281), (C) clinicalmoderatelipidphospholipids-high (n=212) and (D) clinicalatopiclipidsphingolipids-low (n=161). Endotype A infants were characterised by 'classic' clinical presentation of bronchiolitis. Profile D infants were characterised by a higher proportion of parental asthma, IgE sensitisation and rhinovirus infection and low sphingolipids (eg, sphingomyelins, ceramides). Compared with endotype A, profile D infants had a significantly higher risk of asthma (22% vs 50%; unadjusted OR, 3.60; 95% CI 2.31 to 5.62; p<0.001). Additionally, endotype D had a significantly lower abundance of polyunsaturated fatty acids (eg, docosahexaenoic acid; FDR=0.01). The pathway analysis revealed that sphingolipid metabolism pathway was differentially expressed in endotype D (FDR=0.048). CONCLUSIONS: In this multicentre prospective cohort study of infants with bronchiolitis, integrated clustering of clinical, virus and lipidomic data identified clinically and biologically distinct endotypes that have a significantly differential risk for developing asthma.Delete.

Nasopharyngeal metatranscriptome profiles of infants with bronchiolitis and risk of childhood asthma: a multicentre prospective study.

BACKGROUND: Bronchiolitis is not only the leading cause of hospitalisation in US infants but also a major risk factor for asthma development. Growing evidence supports clinical heterogeneity within bronchiolitis. Our objectives were to identify metatranscriptome profiles of infant bronchiolitis, and to examine their relationship with the host transcriptome and subsequent asthma development. METHODS: As part of a multicentre prospective cohort study of infants (age <1 year) hospitalised for bronchiolitis, we integrated virus and nasopharyngeal metatranscriptome (species-level taxonomy and function) data measured at hospitalisation. We applied network-based clustering approaches to identify metatranscriptome profiles. We then examined their association with the host transcriptome at hospitalisation and risk for developing asthma. RESULTS: We identified five metatranscriptome profiles of bronchiolitis (n=244): profile A: virusRSVmicrobiomecommensals; profile B: virusRSV/RV-Amicrobiome H.influenzae ; profile C: virusRSVmicrobiome S.pneumoniae ; profile D: virusRSVmicrobiome M.nonliquefaciens ; and profile E: virusRSV/RV-Cmicrobiome M.catarrhalis . Compared with profile A, profile B infants were characterised by a high proportion of eczema, Haemophilus influenzae abundance and enriched virulence related to antibiotic resistance. These profile B infants also had upregulated T-helper 17 and downregulated type I interferon pathways (false discovery rate (FDR) <0.005), and significantly higher risk for developing asthma (17.9% versus 38.9%; adjusted OR 2.81, 95% CI 1.11-7.26). Likewise, profile C infants were characterised by a high proportion of parental asthma, Streptococcus pneumoniae dominance, and enriched glycerolipid and glycerophospholipid metabolism of the microbiome. These profile C infants had an upregulated RAGE signalling pathway (FDR <0.005) and higher risk of asthma (17.9% versus 35.6%; adjusted OR 2.49, 95% CI 1.10-5.87). CONCLUSIONS: Metatranscriptome and clustering analysis identified biologically distinct metatranscriptome profiles that have differential risks of asthma.

Proteomics endotyping of infants with severe bronchiolitis and risk of childhood asthma.

BACKGROUND: Bronchiolitis is the leading cause of hospitalization in U.S. infants and a major risk factor for childhood asthma. Growing evidence supports clinical heterogeneity within bronchiolitis. We aimed to identify endotypes of infant bronchiolitis by integrating clinical, virus, and serum proteome data, and examine their relationships with asthma development. METHODS: This is a multicenter prospective cohort study of infants hospitalized for physician-diagnosis of bronchiolitis. We identified bronchiolitis endotypes by applying unsupervised machine learning (clustering) approaches to integrated clinical, virus (respiratory syncytial virus [RSV], rhinovirus [RV]), and serum proteome data measured at hospitalization. We then examined their longitudinal association with the risk for developing asthma by age 6 years. RESULTS: In 140 infants hospitalized with bronchiolitis, we identified three endotypes: (1) clinicalatopic virusRV proteomeNFκB-dysregulated , (2) clinicalnon-atopic virusRSV/RV proteomeTNF-dysregulated , and (3) clinicalclassic virusRSV proteomeNFκB/TNF-regulated endotypes. Endotype 1 infants were characterized by high proportion of IgE sensitization and RV infection. These endotype 1 infants also had dysregulated NFκB pathways (FDR < 0.001) and significantly higher risks for developing asthma (53% vs. 22%; adjOR 4.04; 95% CI, 1.49-11.0; p = 0.006), compared with endotype 3 (clinically resembling "classic" bronchiolitis). Likewise, endotype 2 infants were characterized by low proportion of IgE sensitization and high proportion of RSV or RV infection. These endotype 2 infants had dysregulated tumor necrosis factor (TNF)-mediated signaling pathway (FDR <0.001) and significantly higher risks for developing asthma (44% vs. 22%; adjOR 2.71; 95% CI, 1.03-7.11, p = 0.04). CONCLUSION: In this multicenter cohort, integrated clustering of clinical, virus, and proteome data identified biologically distinct endotypes of bronchiolitis that have differential risks of asthma development.

Integrated-omics endotyping of infants with rhinovirus bronchiolitis and risk of childhood asthma.

BACKGROUND: Young children with rhinovirus (RV) infection-particularly bronchiolitis-are at high risk for developing childhood asthma. Emerging evidence suggests clinical heterogeneity within RV bronchiolitis. However, little is known about these biologically distinct subgroups (endotypes) and their relations with asthma risk. OBJECTIVE: We aimed to identify RV bronchiolitis endotypes and examine their longitudinal relations with asthma risk. METHODS: As part of a multicenter prospective cohort study of infants (age <12 months) hospitalized for bronchiolitis, we integrated clinical, RV species (RV-A, RV-B, and RV-C), nasopharyngeal microbiome (16S rRNA gene sequencing), cytokine, and metabolome (liquid chromatography tandem mass spectrometry) data collected at hospitalization. We then applied network and clustering approaches to identify bronchiolitis endotypes. We also examined their longitudinal association with risks of developing recurrent wheeze by age 3 years and asthma by age 5 years. RESULTS: Of 122 infants hospitalized for RV bronchiolitis (median age, 4 months), we identified 4 distinct endotypes-mainly characterized by RV species, microbiome, and type 2 cytokine (T2) response: endotype A, virusRV-CmicrobiomemixedT2low; endotype B, virusRV-AmicrobiomeHaemophilusT2low; endotype C, virusRSV/RVmicrobiomeStreptococcusT2low; and endotype D, virusRV-CmicrobiomeMoraxellaT2high. Compared with endotype A infants, endotype D infants had a significantly higher rate of recurrent wheeze (33% vs 64%; hazard ratio, 2.23; 95% CI, 1.00-4.96; P = .049) and a higher risk for developing asthma (28% vs 59%; odds ratio, 3.74: 95% CI, 1.21-12.6; P = .03). CONCLUSIONS: Integrated-omics analysis identified biologically meaningful RV bronchiolitis endotypes in infants, such as one characterized by RV-C infection, Moraxella-dominant microbiota, and high T2 cytokine response, at higher risk for developing recurrent wheeze and asthma. This study should facilitate further research toward validating our inferences.

Integrated associations of nasopharyngeal and serum metabolome with bronchiolitis severity and asthma: A multicenter prospective cohort study.

BACKGROUND: While infant bronchiolitis contributes to substantial acute (eg, severity) and chronic (eg, asthma development) morbidities, its pathobiology remains uncertain. We examined the integrated relationships of local (nasopharyngeal) and systemic (serum) responses with bronchiolitis morbidities. METHODS: In a multicenter prospective cohort study of infants hospitalized for bronchiolitis, we applied a network analysis approach to identify distinct networks (modules)-clusters of densely interconnected metabolites-of the nasopharyngeal and serum metabolome. We examined their individual and integrated relationships with acute severity (defined by positive pressure ventilation [PPV] use) and asthma development by age 5 years. RESULTS: In 140 infants, we identified 285 nasopharyngeal and 639 serum metabolites. Network analysis revealed 7 nasopharyngeal and 8 serum modules. At the individual module level, nasopharyngeal-amino acid, tricarboxylic acid (TCA) cycle, and carnitine modules were associated with higher risk of PPV use (r > .20; P < .001), while serum-carnitine, amino acid, and glycerophosphorylcholine (GPC)/glycerophosphorylethanolamine (GPE) modules were associated with lower risk (all r < -.20; P < .05). The integrated analysis for PPV use revealed consistent findings-for example, nasopharyngeal-TCA (adjOR: 2.87, 95% CI: 1.68-12.2) and serum-GPC/GPE (adjOR: 0.54, 95% CI: 0.38-0.80) modules-and an additional module-serum-glucose-alanine cycle module (adjOR: 0.69, 95% CI: 0.56-0.86). With asthma risk, there were no individual associations, but there were integrated associations (eg, nasopharyngeal-carnitine module; adjOR: 1.48, 95% CI: 1.11-1.99). CONCLUSION: In infants with bronchiolitis, we found integrated relationships of local and systemic metabolome networks with acute and chronic morbidity. Our findings advance research into the complex interplay among respiratory viruses, local and systemic response, and disease pathobiology in infants with bronchiolitis.

Respiratory viruses are associated with serum metabolome among infants hospitalized for bronchiolitis: A multicenter study.

BACKGROUND: Bronchiolitis is the leading cause of infant hospitalizations in the United States. Growing evidence supports the heterogeneity of bronchiolitis. However, little is known about the interrelationships between major respiratory viruses (and their species), host systemic metabolism, and disease pathobiology. METHODS: In an ongoing multicenter prospective cohort study, we profiled the serum metabolome in 113 infants (63 RSV-only, 21 RV-A, and 29 RV-C) hospitalized with bronchiolitis. We identified serum metabolites that are most discriminatory in the RSV-RV-A and RSV-RV-C comparisons using sparse partial least squares discriminant analysis. We then investigated the association between discriminatory metabolites with acute and chronic outcomes. RESULTS: In 113 infants with bronchiolitis, we measured 639 metabolites. Serum metabolomic profiles differed in both comparisons (Ppermutation  < 0.05). In the RSV-RV-A comparison, we identified 30 discriminatory metabolites, predominantly in lipid metabolism pathways (eg, sphingolipids and carnitines). In multivariable models, these metabolites were significantly associated with the risk of clinical outcomes (eg, tricosanoyl sphingomyelin, OR for recurrent wheezing at age of 3 years = 1.50; 95% CI: 1.05-2.15). In the RSV-RV-C comparison, the discriminatory metabolites were also primarily involved in lipid metabolism (eg, glycerophosphocholines [GPCs], 12,13-diHome). These metabolites were also significantly associated with the risk of outcomes (eg, 1-stearoyl-2-linoleoyl-GPC, OR for positive pressure ventilation use during hospitalization = 0.47; 95% CI: 0.28-0.78). CONCLUSION: Respiratory viruses and their species had distinct serum metabolomic signatures that are associated with differential risks of acute and chronic morbidities of bronchiolitis. Our findings advance research into the complex interrelations between viruses, host systemic response, and bronchiolitis pathobiology.

Emergency department triage prediction of clinical outcomes using machine learning models.

BACKGROUND: Development of emergency department (ED) triage systems that accurately differentiate and prioritize critically ill from stable patients remains challenging. We used machine learning models to predict clinical outcomes, and then compared their performance with that of a conventional approach-the Emergency Severity Index (ESI). METHODS: Using National Hospital and Ambulatory Medical Care Survey (NHAMCS) ED data, from 2007 through 2015, we identified all adult patients (aged ≥ 18 years). In the randomly sampled training set (70%), using routinely available triage data as predictors (e.g., demographics, triage vital signs, chief complaints, comorbidities), we developed four machine learning models: Lasso regression, random forest, gradient boosted decision tree, and deep neural network. As the reference model, we constructed a logistic regression model using the five-level ESI data. The clinical outcomes were critical care (admission to intensive care unit or in-hospital death) and hospitalization (direct hospital admission or transfer). In the test set (the remaining 30%), we measured the predictive performance, including area under the receiver-operating-characteristics curve (AUC) and net benefit (decision curves) for each model. RESULTS: Of 135,470 eligible ED visits, 2.1% had critical care outcome and 16.2% had hospitalization outcome. In the critical care outcome prediction, all four machine learning models outperformed the reference model (e.g., AUC, 0.86 [95%CI 0.85-0.87] in the deep neural network vs 0.74 [95%CI 0.72-0.75] in the reference model), with less under-triaged patients in ESI triage levels 3 to 5 (urgent to non-urgent). Likewise, in the hospitalization outcome prediction, all machine learning models outperformed the reference model (e.g., AUC, 0.82 [95%CI 0.82-0.83] in the deep neural network vs 0.69 [95%CI 0.68-0.69] in the reference model) with less over-triages in ESI triage levels 1 to 3 (immediate to urgent). In the decision curve analysis, all machine learning models consistently achieved a greater net benefit-a larger number of appropriate triages considering a trade-off with over-triages-across the range of clinical thresholds. CONCLUSIONS: Compared to the conventional approach, the machine learning models demonstrated a superior performance to predict critical care and hospitalization outcomes. The application of modern machine learning models may enhance clinicians' triage decision making, thereby achieving better clinical care and optimal resource utilization.

A case of a pulmonary-renal syndrome caused by streptococcal infection.

Pulmonary-renal syndrome (PRS) is defined as a combination of diffuse alveolar haemorrhage and glomerulonephritis. An 18-year-old woman visited our hospital with a 2-day history of fever, dyspnoea, and leg edema. Laboratory investigations revealed an elevated inflammatory reaction, increased serum creatinine levels, and normocytic anaemia. Additionally, the anti-streptolysin-O titre was positive, and complement component-3 levels were decreased. Urinalysis revealed proteinuria and hematuria. Bronchoalveolar lavage aliquots were progressively more hemorrhagic. These findings supported a diagnosis of PRS secondary to streptococcal infection. The patient was treated with high-dose methylprednisolone and antibiotics. After 4 days of treatment, her respiratory symptoms and serum creatinine levels improved. Steroid tapering was performed over 15 days. The findings in this case indicate that streptococcal infection is a potential cause of PRS, and that short-term steroid therapy is an effective treatment.

Intravenous Tranexamic Acid in Percutaneous Kidney Biopsy: A Randomized Controlled Trial.

BACKGROUND: Tranexamic acid is frequently reported to reduce bleeding-related complications in major surgery and trauma. We aimed to investigate whether tranexamic acid reduced hematoma size after percutaneous kidney biopsy. METHODS: We conducted a double-blind, parallel three-group, randomized placebo-controlled trial at a teaching hospital in Japan between January 2016 and July 2018. Adult patients with clinical indication for ultrasound-guided percutaneous biopsy of a native kidney were included. Participants were randomly assigned into three groups: high-dose tranexamic acid (1,000 mg in total), low-dose tranexamic acid (500 mg in total), or placebo (counterpart saline). Intervention drugs were intravenously administered twice, as a bolus just before the biopsy and as a continuous infusion initiated just after the biopsy. Primary outcome was post-biopsy perirenal hematoma size as measured by ultrasound on the morning after the biopsy. RESULTS: We assessed 90 adult patients for study eligibility, of whom 56 were randomly allocated into the three groups: 20 for high-dose tranexamic acid, 19 for low-dose tranexamic acid, and 17 for placebo. The median size of perirenal hematoma was 200 mm2 (interquartile range, 21-650) in the high-dose tranexamic acid group, 52 mm2 (0-139) in the low-dose tranexamic acid group, and 0 mm2 (0-339) in the placebo group (p = 0.048 for high-dose tranexamic acid vs. placebo). CONCLUSION: In this trial, the median size of post-kidney biopsy hematoma was unexpectedly larger in the high-dose tranexamic acid group than in the placebo group. Although our results do not support the routine use of tranexamic acid in percutaneous kidney biopsy at present, further studies are needed to confirm the results.

Prediction of Vitamin D Deficiency in Older Adults: The Role of Machine Learning Models.

CONTEXT: Conventional prediction models for vitamin D deficiency have limited accuracy. BACKGROUND: Using cross-sectional data, we developed models based on machine learning (ML) and compared their performance with those based on a conventional approach. METHODS: Participants were 5106 community-resident adults (50-84 years; 58% male). In the randomly sampled training set (65%), we constructed 5 ML models: lasso regression, elastic net regression, random forest, gradient boosted decision tree, and dense neural network. The reference model was a logistic regression model. Outcomes were deseasonalized serum 25-hydroxyvitamin D (25(OH)D) <50 nmol/L (yes/no) and <25 nmol/L (yes/no). In the test set (the remaining 35%), we evaluated predictive performance of each model, including area under the receiver operating characteristic curve (AUC) and net benefit (decision curves). RESULTS: Overall, 1270 (25%) and 91 (2%) had 25(OH)D <50 and <25 nmol/L, respectively. Compared with the reference model, the ML models predicted 25(OH)D <50 nmol/L with similar accuracy. However, for prediction of 25(OH)D <25 nmol/L, all ML models had higher AUC point estimates than the reference model by up to 0.14. AUC was highest for elastic net regression (0.93; 95% CI 0.90-0.96), compared with 0.81 (95% CI 0.71-0.91) for the reference model. In the decision curve analysis, ML models mostly achieved a greater net benefit across a range of thresholds. CONCLUSION: Compared with conventional models, ML models predicted 25(OH)D <50 nmol/L with similar accuracy but they predicted 25(OH)D <25 nmol/L with greater accuracy. The latter finding suggests a role for ML models in participant selection for vitamin D supplement trials.

Association between serum alkaline phosphatase and bacteraemia in haemodialysis outpatients: a multicentre retrospective cross-sectional study.

OBJECTIVES: Elevated baseline serum alkaline phosphatase (ALP) may correlate with higher medium-term to long-term mortality in the general population and in patients with chronic kidney disease. However, few data are available on the association between serum ALP and the short-term prognosis of patients on haemodialysis (HD). We verified the association of ALP levels and bacteraemia or death in maintenance HD patients suspected of bacteraemia in an outpatient setting. DESIGN: We analysed 315 consecutive HD patients suspected of having bacteraemia with two sets of blood culture drawn on admission. SETTING: Admission to two tertiary-care university medical centres from January 2013 to December 2015. PARTICIPANTS: Consecutive cases on maintenance HD aged≥18 years. Cases of hospitalised patients who had been transferred from another hospital, had a dialysis vintage<2 months, were also undergoing peritoneal dialysis, and/or were receiving HD less than once a week were excluded. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome measure was bacteraemia and secondary outcome was in-hospital death. RESULTS: Among 315 cases included in the study, 187 had baseline-measured ALP levels, with a cut-off value on ROC analysis of 360 U/L (Area Under the Curve (AUC) 0.60, sensitivity 0.49, specificity 0.76). In multivariate analysis, there was a statistically significant association between a higher ALP in hospital visit and bacteraemia (OR: 2.37, 95% CI: 1.17 to 4.83). However, there were no statistically significant associations between higher ALP and in-hospital death (OR: 1.20, 95% CI: 0.57 to 2.54). A sensitivity analysis of 187 patients with no missing ALP values also demonstrated a significant association between elevated ALP and bacteraemia, but no significant association between ALP and in-hospital death. CONCLUSIONS: Elevated ALP is a predictor of bacteraemia. In HD patients suspected of bacteraemia in outpatient settings, increased ALP levels were associated with increased likelihood of confirmed disease.

Prediction of Major Adverse Cardiovascular Events in Patients With Hypertrophic Cardiomyopathy Using Proteomics Profiling.

BACKGROUND: Hypertrophic cardiomyopathy often causes major adverse cardiovascular events (MACE), for example, arrhythmias, stroke, heart failure, and sudden cardiac death. Currently, there are no models available to predict MACE. Furthermore, it remains unclear which signaling pathways mediate MACE. Therefore, we aimed to prospectively determine protein biomarkers that predict MACE in hypertrophic cardiomyopathy and to identify signaling pathways differentially regulated in patients who subsequently develop MACE. METHODS: In this multi-centre prospective cohort study of patients with hypertrophic cardiomyopathy, we conducted plasma proteomics profiling of 4979 proteins upon enrollment. We developed a proteomics-based model to predict MACE using data from one institution (training set). We tested the predictive ability in independent samples from the other institution (test set) and performed time-to-event analysis. Additionally, we executed pathway analysis of predictive proteins using a false discovery rate threshold of <0.001. RESULTS: The study included 245 patients (n=174 in the training set and n=71 in the test set). Using the proteomics-based model to predict MACE derived from the training set, the area under the receiver-operating-characteristic curve was 0.81 (95% CI, 0.68-0.93) in the test set. In the test set, the high-risk group determined by the proteomics-based predictive model had a significantly higher rate of developing MACE (hazard ratio, 13.6 [95% CI, 1.7-107]; P=0.01). The Ras-MAPK (mitogen-activated protein kinase) pathway was upregulated in patients who subsequently developed MACE (false discovery rate<1.0×10-7). Pathways involved in inflammation and fibrosis-for example, the TGF (transforming growth factor)-ß pathway-were also upregulated. CONCLUSIONS: This study serves as the first to demonstrate the ability of proteomics profiling to predict MACE in hypertrophic cardiomyopathy, exhibiting both novel (eg, Ras-MAPK) and known (eg, TGF-ß) pathways differentially regulated in patients who subsequently experience MACE.