24-h energy expenditure in people with type 1 diabetes: impact on equations for clinical estimation of energy expenditure.

BACKGROUND/OBJECTIVES: Type 1 diabetes (T1D) is associated with an increase in resting metabolic rate (RMR), but the impact of T1D on other components of 24-h energy expenditure (24-h EE) is not known. Also, there is a lack of equations to estimate 24-h EE in patients with T1D. The aims of this analysis were to compare 24-h EE and its components in young adults with T1D and healthy controls across the spectrum of body mass index (BMI) and derive T1D-specific equations from clinical variables. SUBJECTS/METHODS: Thirty-three young adults with T1D diagnosed ≥1 year prior and 33 healthy controls matched for sex, age and BMI were included in this analysis. We measured 24-h EE inside a whole room indirect calorimeter (WRIC) and body composition with dual x-ray absorptiometry. RESULTS: Participants with T1D had significantly higher 24-h EE than healthy controls (T1D = 2047 ± 23 kcal/day vs control= 1908 ± 23 kcal/day; P < 0.01). We derived equations to estimate 24-h EE with both body composition (fat free mass + fat mass) and anthropometric (weight + height) models, which provided high coefficients of determination (R2 = 0.912 for both). A clinical model that did not incorporate spontaneous physical activity yielded high coefficients of determination as well (R2 = 0.897 and R2 = 0.880 for body composition and anthropometric models, respectively). CONCLUSION: These results confirm that young adults with established T1D have increased 24-h EE relative to controls without T1D. The derived equations from clinically available variables can assist clinicians with energy prescriptions for weight management in patients with T1D.

Comparative Effect of Loop Diuretic Prescription on Mortality and Heart Failure Readmission.

Loop diuretics are a standard pharmacologic therapy in heart failure (HF) management. Although furosemide is most frequently used, torsemide and bumetanide are increasingly prescribed in clinical practice, possibly because of superior bioavailability. Few real-world comparative effectiveness studies have examined outcomes across all 3 loop diuretics. The study goal was to compare the effects of loop diuretic prescribing at HF hospitalization discharge on mortality and HF readmission. We identified patients in Medicare claims data initiating furosemide, torsemide, or bumetanide after an index HF hospitalization from 2007 to 2017. We estimated 6-month risks of all-cause mortality and a composite outcome (HF readmission or all-cause mortality) using inverse probability of treatment weighting to adjust for relevant confounders. We identified 62,632 furosemide, 1,720 torsemide, and 2,389 bumetanide initiators. The 6-month adjusted all-cause mortality risk was lowest for torsemide (13.2%), followed by furosemide (14.5%) and bumetanide (15.6%). The 6-month composite outcome risk was 21.4% for torsemide, 24.7% for furosemide, and 24.9% for bumetanide. Compared with furosemide, the 6-month all-cause mortality risk was 1.3% (95% confidence interval [CI]: -3.7, 1.0) lower for torsemide and 1.0% (95% CI: -1.2, 3.2) higher for bumetanide, and the 6-month composite outcome risk was 3.3% (95% CI: -6.3, -0.3) lower for torsemide and 0.2% (95% CI: -2.5, 2.9) higher for bumetanide. In conclusion, the findings suggested that the first prescribed loop diuretic following HF hospitalization is associated with clinically important differences in morbidity in older patients receiving torsemide, bumetanide, or furosemide. These differences were consistent for the effect of all-cause mortality alone, but were not statistically significant.

Assessment of a Precision Medicine Analysis of a Behavioral Counseling Strategy to Improve Adherence to Diabetes Self-management Among Youth: A Post Hoc Analysis of the FLEX Trial.

Importance: The Flexible Lifestyles Empowering Change (FLEX) trial, an 18-month randomized clinical trial testing an adaptive behavioral intervention in adolescents with type 1 diabetes, showed no overall treatment effect for its primary outcome, change in hemoglobin A1c (HbA1c) percentage of total hemoglobin, but demonstrated benefit for quality of life (QoL) as a prespecified secondary outcome. Objective: To apply a novel statistical method for post hoc analysis that derives an individualized treatment rule (ITR) to identify FLEX participants who may benefit from intervention based on changes in HbA1c percentage (primary outcome), QoL, and body mass index z score (BMIz) (secondary outcomes) during 18 months. Design, Setting, and Participants: This multisite clinical trial enrolled 258 adolescents aged 13 to 16 years with type 1 diabetes for 1 or more years, who had literacy in English, HbA1c percentage of total hemoglobin from 8.0% to 13.0%, a participating caregiver, and no other serious medical conditions. From January 5, 2014, to April 4, 2016, 258 adolescents were recruited. The post hoc analysis excluded adolescents missing outcome measures at 18 months (2 participants [0.8%]) or continuous glucose monitoring data at baseline (40 participants [15.5%]). Data were analyzed from April to December 2018. Interventions: The FLEX intervention included a behavioral counseling strategy that integrated motivational interviewing and problem-solving skills training to increase adherence to diabetes self-management. The control condition entailed usual diabetes care. Main Outcomes and Measures: Subgroups of FLEX participants were derived from an ITR estimating which participants would benefit from intervention, which would benefit from control conditions, and which would be indifferent. Multiple imputation by chained equations and reinforcement learning trees were used to estimate the ITR. Subgroups based on ITR pertaining to changes during 18 months in 3 univariate outcomes (ie, HbA1c percentage, QoL, and BMIz) and a composite outcome were compared by baseline demographic, clinical, and psychosocial characteristics. Results: Data from 216 adolescents in the FLEX trial were reanalyzed (166 [76.9%] non-Hispanic white; 108 teenaged girls [50.0%]; mean [SD] age, 14.9 [1.1] years; mean [SD] diabetes duration, 6.3 [3.7] years). For the univariate outcomes, a large proportion of FLEX participants had equivalent predicted outcomes under intervention vs usual care settings, regardless of randomization, and were assigned to the muted group (HbA1c: 105 participants [48.6%]; QoL: 63 participants [29.2%]; BMIz: 136 participants [63.0%]). Regarding the BMIz univariate outcome, mean baseline BMIz of participants assigned to the muted group was lower than that of those assigned to the intervention and control groups (muted vs intervention: mean difference, 0.48; 95% CI, 0.21 to 0.75; P = .002; muted vs control: mean difference, 0.86; 95% CI, 0.61 to 1.11; P < .001); this group also had a higher proportion of individuals with underweight or normal weight using weight status cutoffs (95 [69.9%] in muted group vs 24 [54.6%] in intervention group and 11 [30.6%] in control group; χ24 = 24.67; P < .001). The approach identified subgroups estimated to benefit based on HbA1c percentage (54 participants [25.0%]), QoL (89 participants [41.2%]), and BMIz (44 participants [20.4%]). Regarding the HbA1c percentage outcome, participants expected to benefit from the intervention did not have significantly higher baseline HbA1c percentages than those expected to benefit from usual care (9.4% vs 9.2%; difference, 0.2%; 95% CI, -0.16% to 0.56%; P = .44). However, participants in the muted group had higher mean HbA1c percentages at baseline than those assigned to the intervention or control groups (muted vs intervention: 9.9% vs 9.4%; difference, 0.5%; 95% CI, 0.13% to 0.89%; P = .02; muted vs control; 9.9% vs 9.2%; difference, 0.7%; 95% CI, 0.34% to 1.08%; P = .001). No significant differences were found between subgroups estimated to benefit in terms of the composite outcome from the FLEX intervention (91 participants [42.1%]) vs usual care (125 participants [57.9%]). Conclusions and Relevance: The precision medicine approach represents a conceptually and analytically novel approach to post hoc subgroup identification. More work is needed to understand markers of positive response to the FLEX intervention. Trial Registration: ClinicalTrial.gov identifier: NCT01286350.

Genome analysis and pleiotropy assessment using causal networks with loss of function mutation and metabolomics.

BACKGROUND: Many genome-wide association studies have detected genomic regions associated with traits, yet understanding the functional causes of association often remains elusive. Utilizing systems approaches and focusing on intermediate molecular phenotypes might facilitate biologic understanding. RESULTS: The availability of exome sequencing of two populations of African-Americans and European-Americans from the Atherosclerosis Risk in Communities study allowed us to investigate the effects of annotated loss-of-function (LoF) mutations on 122 serum metabolites. To assess the findings, we built metabolomic causal networks for each population separately and utilized structural equation modeling. We then validated our findings with a set of independent samples. By use of methods based on concepts of Mendelian randomization of genetic variants, we showed that some of the affected metabolites are risk predictors in the causal pathway of disease. For example, LoF mutations in the gene KIAA1755 were identified to elevate the levels of eicosapentaenoate (p-value = 5E-14), an essential fatty acid clinically identified to increase essential hypertension. We showed that this gene is in the pathway to triglycerides, where both triglycerides and essential hypertension are risk factors of metabolomic disorder and heart attack. We also identified that the gene CLDN17, harboring loss-of-function mutations, had pleiotropic actions on metabolites from amino acid and lipid pathways. CONCLUSION: Using systems biology approaches for the analysis of metabolomics and genetic data, we integrated several biological processes, which lead to findings that may functionally connect genetic variants with complex diseases.

Multistate recursively imputed survival trees for time-to-event data analysis: an application to AIDS and mortality post-HIV infection data.

BACKGROUND: This study aimed to introduce recursively imputed survival trees into multistate survival models (MSRIST) to analyze these types of data and to identify the prognostic factors influencing the disease progression in patients with intermediate events. The proposed method is fully nonparametric and can be used for estimating transition probabilities. METHODS: A general algorithm was provided for analyzing multi-state data with a focus on the illness-death and progressive multi-state models. The model considered both beyond Markov and Non-Markov settings. We also proposed a multi-state random survival method (MSRSF) and compared their performance with the classical multi-state Cox model. We applied the proposed method to a dataset related to HIV/AIDS patients based on a retrospective cohort study extracted in Tehran from April 2004 to March 2014 consist of 2473 HIV-infected patients. RESULTS: The results showed that MSRIST outperformed the classical multistate method using Cox Model and MSRSF in terms of integrated Brier score and concordance index over 500 repetitions. We also identified a set of important risk factors as well as their interactions on different states of HIV and AIDS progression. CONCLUSIONS: There are different strategies for modelling the intermediate event. We adapted two newly developed data mining technique (RSF and RIST) for multistate models (MSRSF and MSRIST) to identify important risk factors in different stages of the diseases. The methods can capture any complex relationship between variables and can be used as a useful tool for identifying important risk factors in different states of this disease.

Respiratory infections with Pseudomonas aeruginosa in children with cystic fibrosis: early detection by serology and assessment of risk factors.

CONTEXT: Patients with cystic fibrosis (CF) are susceptible to lower respiratory tract infections with Pseudomonas aeruginosa and typically acquire this organism in early childhood. Once P aeruginosa infection is established, eradication may be impossible, and progressive lung disease often aggravates morbidity and mortality risks. The ability to diagnose CF by genetic testing at birth makes it possible to determine the temporal sequence of events that result in P aeruginosa-associated pulmonary infections. OBJECTIVE: To evaluate the longitudinal relationship between the production of an antibody response against P aeruginosa and clinical factors associated with P aeruginosa pulmonary infections in patients with CF diagnosed in early life. DESIGN, SETTING, AND PATIENTS: Serum samples and oropharyngeal cultures (protocol cultures) were obtained at 6-month intervals from April 15, 1985, to April 15, 2000 (or for up to 180 months depending on their enrollment date) from 68 patients at 2 centers in Madison and Milwaukee, Wis, diagnosed through the Wisconsin CF Neonatal Screening Project, a longitudinal cohort study. Additional cultures were obtained at examining physicians' discretion (all cultures). MAIN OUTCOME MEASURES: Time to serum IgG, IgA, and IgM antibody titer of at least 1:256 against P aeruginosa, assessed by enzyme-linked immunosorbent assay using cell lysate, exotoxin A, and elastase as antigens; time to organism isolation from respiratory samples; time to Wisconsin Cystic Fibrosis Radiograph (WCXR) score of 5 or more. RESULTS: The median time to an antibody titer of at least 1:256 was 17.8, 24.2, and 70.9 months for cell lysate, exotoxin A, and elastase, respectively. The rise of anti-cell lysate and anti-exotoxin A titers to 1:256 or more occurred a mean of 11.9 (P<.001) and 5.6 (P =.04) months, respectively, before the isolation of P aeruginosa for all cultures and 18.2 (P<.001) and 11.9 (P =.006) months, respectively, before protocol cultures. There was no significant difference between the rise of anti-cell lysate and anti-exotoxin A titer and a WCXR score of 5 or more (P =.24 and.32, respectively). Treatment with long-term, non-Pseudomonas oral antibiotics and integration of CF infants with older, chronically infected patients were associated with a significantly increased risk of P aeruginosa pulmonary infection. CONCLUSIONS: In CF patients diagnosed through neonatal screening, P aeruginosa pulmonary infections occurred 6 to 12 months before the organism was isolated from respiratory secretions. The longitudinal monitoring of P aeruginosa antibody titers, in concert with WCXR score, should facilitate diagnosis and treatment of P aeruginosa pulmonary infections in young children with CF.