Baseline characteristics and age-related macular degeneration in participants of the 'ASPirin in Reducing Events in the Elderly' (ASPREE)-AMD trial

Purpose: To describe the baseline participant characteristics in the ASPREE-AMD study, investigating the effect of aspirin on AMD incidence and progression.Methods: Australian participants from the ASPirin in Reducing Events in the Elderly (ASPREE) trial, randomized to 100 mg aspirin daily or placebo, had non-mydriatic, digital color fundus images graded according to the Beckman AMD classification. Associations with AMD were determined for baseline characteristics and genetic risk variants.Results: ASPREE-AMD sub-study enrolled 4993 participants with gradable macular images. Median age was 73.4 years (IQR, 71.5, 76.6), 52% were female, 10% had diabetes mellitus, 73% had hypertension, and 44% were former/current smokers. Early, intermediate and late AMD (detected in 20.6%, 16.1%, 1.1%, respectively), significantly associated with age, were also associated with increasing HDL levels: OR = 1.52 (95%CI, 1.26, 1.84), OR = 1.43 (1.17, 1.77) and OR = 1.96 (1.02, 3.76), respectively. Female sex was associated with early [OR = 1.37 (1.16, 1.62)], and intermediate [OR = 1.35 (1.12, 1.63)] AMD, as was previous regular use of aspirin, with OR = 1.46 (1.11, 1.92) and OR = 1.37 (1.01, 1.85), respectively. Current smoking had increased odds for late AMD, OR = 4.02 (1.42, 11.36). Genetic risk variant rs3750846 (ARMS2/HTRA1) was associated with each AMD stage (p CFH) with intermediate and late AMD (p C3) with late AMD (p Conclusions: Observed associations are typical of AMD. The ASPREE-AMD clinical trial provides a unique opportunity to determine the risks and benefits of low-dose aspirin for AMD incidence and progression in elderly population

A comparison of model selection methods for prediction in the presence of multiply imputed data

Many approaches for variable selection with multiply imputed data in the development of a prognostic model have been proposed. However, no method prevails as uniformly best. We conducted a simulation study with a binary outcome and a logistic regression model to compare two classes of variable selection methods in the presence of MI data: (I) Model selection on bootstrap data, using backward elimination based on AIC or lasso, and fit the final model based on the most frequently (e.g. urn:x-wiley:03233847:media:bimj1946:bimj1946-math-0001) selected variables over all MI and bootstrap data sets; (II) Model selection on original MI data, using lasso. The final model is obtained by (i) averaging estimates of variables that were selected in any MI data set or (ii) in 50% of the MI data; (iii) performing lasso on the stacked MI data, and (iv) as in (iii) but using individual weights as determined by the fraction of missingness. In all lasso models, we used both the optimal penalty and the 1‐se rule. We considered recalibrating models to correct for overshrinkage due to the suboptimal penalty by refitting the linear predictor or all individual variables. We applied the methods on a real dataset of 951 adult patients with tuberculous meningitis to predict mortality within nine months. Overall, applying lasso selection with the 1‐se penalty shows the best performance, both in approach I and II. Stacking MI data is an attractive approach because it does not require choosing a selection threshold when combining results from separate MI data sets

Cardiovascular risk prediction in healthy older people.

Identification of individuals with increased risk of major adverse cardiovascular events (MACE) is important. However, algorithms specific to the elderly are lacking. Data were analysed from a randomised trial involving 18,548 participants ≥ 70 years old (mean age 75.4 years), without prior cardiovascular disease events, dementia or physical disability. MACE included coronary heart disease death, fatal or nonfatal ischaemic stroke or myocardial infarction. Potential predictors tested were based on prior evidence and using a machine-learning approach. Cox regression analyses were used to calculate 5-year predicted risk, and discrimination evaluated from receiver operating characteristic curves. Calibration was also assessed, and the findings internally validated using bootstrapping. External validation was performed in 25,138 healthy, elderly individuals in the primary care environment. During median follow-up of 4.7 years, 594 MACE occurred. Predictors in the final model included age, sex, smoking, systolic blood pressure, high-density lipoprotein cholesterol (HDL-c), non-HDL-c, serum creatinine, diabetes and intake of antihypertensive agents. With variable selection based on machine-learning, age, sex and creatinine were the most important predictors. The final model resulted in an area under the curve (AUC) of 68.1 (95% confidence intervals 65.9; 70.4). The model had an AUC of 67.5 in internal and 64.2 in external validation. The model rank-ordered risk well but underestimated absolute risk in the external validation cohort. A model predicting incident MACE in healthy, elderly individuals includes well-recognised, potentially reversible risk factors and notably, renal function. Calibration would be necessary when used in other populations

Leukotriene A4 Hydrolase Genotype and HIV Infection Influence Intracerebral Inflammation and Survival From Tuberculous Meningitis.

Background.: Tuberculous meningitis (TBM) is the most devastating form of tuberculosis, yet very little is known about the pathophysiology. We hypothesized that the genotype of leukotriene A4 hydrolase (encoded by LTA4H), which determines inflammatory eicosanoid expression, influences intracerebral inflammation, and predicts survival from TBM. Methods.: We characterized the pretreatment clinical and intracerebral inflammatory phenotype and 9-month survival of 764 adults with TBM. All were genotyped for single-nucleotide polymorphism rs17525495, and inflammatory phenotype was defined by cerebrospinal fluid (CSF) leukocyte and cytokine concentrations. Results.: LTA4H genotype predicted survival of human immunodeficiency virus (HIV)-uninfected patients, with TT-genotype patients significantly more likely to survive TBM than CC-genotype patients, according to Cox regression analysis (univariate P = .040 and multivariable P = .037). HIV-uninfected, TT-genotype patients had high CSF proinflammatory cytokine concentrations, with intermediate and lower concentrations in those with CT and CC genotypes. Increased CSF cytokine concentrations correlated with more-severe disease, but patients with low CSF leukocytes and cytokine concentrations were more likely to die from TBM. HIV infection independently predicted death due to TBM (hazard ratio, 3.94; 95% confidence interval, 2.79-5.56) and was associated with globally increased CSF cytokine concentrations, independent of LTA4H genotype. Conclusions.: LTA4H genotype and HIV infection influence pretreatment inflammatory phenotype and survival from TBM. LTA4H genotype may predict adjunctive corticosteroid responsiveness in HIV-uninfected individuals

Prediction of disability-free survival in healthy older people.

Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6-77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people.Trial registration Clinicaltrials.gov (NCT01038583)

Effects of infection control measures on acquisition of five antimicrobial drug-resistant microorganisms in a tetanus intensive care unit in Vietnam

Purpose: To quantify the effects of barrier precautions and antibiotic mixing on prevalence and acquisition of five drug-resistant microorganisms within a single tetanus intensive care unit at a tertiary referral hospital in Ho Chi Minh City, Vietnam. Methods: All patients admitted within the study period were included. After a 1-year baseline period, barrier precautions were implemented and the single empirical treatment ceftazidime was changed to mixing (per consecutive patient) of three different regimens (ceftazidime, ciprofloxacin, piperacillin-tazobactam). Markov chain modeling and genotyping were used to determine the effects of interventions on prevalence levels and the relative importance of cross-transmission and antibiotic-associated selection. Results: A total of 190 patients were included in year 1 (2,708 patient days, 17,260 cultures) and 167 patients in year 2 (3,384 patient days, 20,580 cultures). In year 1, average daily prevalence rates for methicillin-resistant Staphylococcus aureus (MRSA), extended spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae (excluding Klebsiella pneumoniae), Pseudomonas aeruginosa, gentamicin-resistant K. pneumoniae, and amikacin-resistant Acinetobacter species were 34.0, 61.3, 53.4, 65.7 and 57.1 %. After intervention, ceftazidime usage decreased by 53 %; the use of piperacillin-tazobactam and ciprofloxacin increased 7.2-fold and 4.5-fold, respectively. Adherence to hand hygiene after patient contact was 54 %. These measures were associated with a reduction of MRSA prevalence by 69.8 % (to 10.3 %), mainly because of less cross-transmission (88 % reduction), and of ESBL-producing Enterobacteriaceae prevalence by 10.3 % (non-significantly). In contrast, prevalence levels of the other three pathogens remained unaffected. Conclusion: The combination of simple infection control measures and antibiotic mixing was highly effective in reducing the prevalence of MRSA, but not of Gram-negative microorganisms. © 2013 The Author(s)

Leukotriene A4 Hydrolase Genotype and HIV Infection Influence Intracerebral Inflammation and Survival From Tuberculous Meningitis.

Background.: Tuberculous meningitis (TBM) is the most devastating form of tuberculosis, yet very little is known about the pathophysiology. We hypothesized that the genotype of leukotriene A4 hydrolase (encoded by LTA4H), which determines inflammatory eicosanoid expression, influences intracerebral inflammation, and predicts survival from TBM. Methods.: We characterized the pretreatment clinical and intracerebral inflammatory phenotype and 9-month survival of 764 adults with TBM. All were genotyped for single-nucleotide polymorphism rs17525495, and inflammatory phenotype was defined by cerebrospinal fluid (CSF) leukocyte and cytokine concentrations. Results.: LTA4H genotype predicted survival of human immunodeficiency virus (HIV)-uninfected patients, with TT-genotype patients significantly more likely to survive TBM than CC-genotype patients, according to Cox regression analysis (univariate P = .040 and multivariable P = .037). HIV-uninfected, TT-genotype patients had high CSF proinflammatory cytokine concentrations, with intermediate and lower concentrations in those with CT and CC genotypes. Increased CSF cytokine concentrations correlated with more-severe disease, but patients with low CSF leukocytes and cytokine concentrations were more likely to die from TBM. HIV infection independently predicted death due to TBM (hazard ratio, 3.94; 95% confidence interval, 2.79-5.56) and was associated with globally increased CSF cytokine concentrations, independent of LTA4H genotype. Conclusions.: LTA4H genotype and HIV infection influence pretreatment inflammatory phenotype and survival from TBM. LTA4H genotype may predict adjunctive corticosteroid responsiveness in HIV-uninfected individuals

Prognostic models for 9 month mortality in tuberculous meningitis.

Background Tuberculous meningitis (TBM) is the most severe form of extrapulmonary tuberculosis. We developed and validated prognostic models for 9-month mortality in adults with TBM, with or without human immunodeficiency virus (HIV) infection. Methods We included 1699 subjects from 4 randomized clinical trials and 1 prospective observational study conducted at 2 major referral hospitals in Southern Vietnam from 2001–2015. Modeling was based on multivariable Cox proportional hazards regression. The final prognostic models were validated internally and temporally and were displayed using nomograms and a Webbased app (https://thaole.shinyapps.io/tbmapp/) Results 951 HIV-uninfected and 748 HIV-infected subjects with TBM were included; 219 of 951 (23.0%) and 384 of 748 (51.3%) died during 9-month follow-up. Common predictors for increased mortality in both populations were higher Medical Research Council (MRC) disease severity grade and lower cerebrospinal fluid lymphocyte cell count. In HIV-uninfected subjects, older age, previous tuberculosis, not receiving adjunctive dexamethasone, and focal neurological signs were additional risk factors; in HIVinfected subjects, lower weight, lower peripheral blood CD4 cell count, and abnormal plasma sodium were additional risk factors. The areas under the receiver operating characteristic curves (AUCs) for the final prognostic models were 0.77 (HIV-uninfected population) and 0.78 (HIV-infected population), demonstrating better discrimination than the MRC grade (AUC, 0.66 and 0.70) or Glasgow Coma Scale score (AUC, 0.68 and 0.71) alone. Conclusions The developed models showed good performance and could be used in clinical practice to assist physicians in identifying patients with TBM at high risk of death and with increased need of supportive care.</p