Random forest prediction of Alzheimer's disease using pairwise selection from time series data

Time-dependent data collected in studies of Alzheimer's disease usually has missing and irregularly sampled data points. For this reason time series methods which assume regular sampling cannot be applied directly to the data without a pre-processing step. In this paper we use a machine learning method to learn the relationship between pairs of data points at different time separations. The input vector comprises a summary of the time series history and includes both demographic and non-time varying variables such as genetic data. The dataset used is from the 2017 TADPOLE grand challenge which aims to predict the onset of Alzheimer's disease using including demographic, physical and cognitive data. The challenge is a three-fold diagnosis classification into AD, MCI and control groups, the prediction of ADAS-13 score and the normalised ventricle volume. While the competition proceeds, forecasting methods may be compared using a leaderboard dataset selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and with standard metrics for measuring accuracy. For diagnosis, we find an mAUC of 0.82, and a classification accuracy of 0.73. The results show that the method is effective and comparable with other methods.Comment: 6 pages, 1 figure, 6 table

Challenges for Optimizing Real-World Evidence in Alzheimer’s Disease: The ROADMAP Project

ROADMAP is a public-private advisory partnership to evaluate the usability of multiple data sources, including real-world evidence, in the decision-making process for new treatments in Alzheimer’s disease, and to advance key concepts in disease and pharmacoeconomic modeling. ROADMAP identified key disease and patient outcomes for stakeholders to make informed funding and treatment decisions, provided advice on data integration methods and standards, and developed conceptual cost-effectiveness and disease models designed in part to assess whether early treatment provides long-term benefit

Periodontitis and Outer Retinal Thickness: a Cross-Sectional Analysis of the United Kingdom Biobank Cohort

\ua9 2024 American Academy of OphthalmologyPurpose: Periodontitis, a ubiquitous severe gum disease affecting the teeth and surrounding alveolar bone, can heighten systemic inflammation. We investigated the association between very severe periodontitis and early biomarkers of age-related macular degeneration (AMD), in individuals with no eye disease. Design: Cross-sectional analysis of the prospective community-based cohort United Kingdom (UK) Biobank. Participants: Sixty-seven thousand three hundred eleven UK residents aged 40 to 70 years recruited between 2006 and 2010 underwent retinal imaging. Methods: Macular-centered OCT images acquired at the baseline visit were segmented for retinal sublayer thicknesses. Very severe periodontitis was ascertained through a touchscreen questionnaire. Linear mixed effects regression modeled the association between very severe periodontitis and retinal sublayer thicknesses, adjusting for age, sex, ethnicity, socioeconomic status, alcohol consumption, smoking status, diabetes mellitus, hypertension, refractive error, and previous cataract surgery. Main Outcome Measures: Photoreceptor layer (PRL) and retinal pigment epithelium–Bruch\u27s membrane (RPE–BM) thicknesses. Results: Among 36 897 participants included in the analysis, 1571 (4.3%) reported very severe periodontitis. Affected individuals were older, lived in areas of greater socioeconomic deprivation, and were more likely to be hypertensive, diabetic, and current smokers (all P < 0.001). On average, those with very severe periodontitis were hyperopic (0.05 \ub1 2.27 diopters) while those unaffected were myopic (−0.29 \ub1 2.40 diopters, P < 0.001). Following adjusted analysis, very severe periodontitis was associated with thinner PRL (−0.55 μm, 95% confidence interval [CI], −0.97 to −0.12; P = 0.022) but there was no difference in RPE–BM thickness (0.00 μm, 95% CI, −0.12 to 0.13; P = 0.97). The association between PRL thickness and very severe periodontitis was modified by age (P < 0.001). Stratifying individuals by age, thinner PRL was seen among those aged 60 to 69 years with disease (−1.19 μm, 95% CI, −1.85 to −0.53; P < 0.001) but not among those aged < 60 years. Conclusions: Among those with no known eye disease, very severe periodontitis is statistically associated with a thinner PRL, consistent with incipient AMD. Optimizing oral hygiene may hold additional relevance for people at risk of degenerative retinal disease. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article

Cohort profile: design and methods in the eye and vision consortium of UK Biobank

PURPOSE: To describe the rationale, methods and research potential of eye and vision measures available in UK Biobank. PARTICIPANTS: UK Biobank is a large, multisite, prospective cohort study. Extensive lifestyle and health questionnaires, a range of physical measures and collection of biological specimens are collected. The scope of UK Biobank was extended midway through data collection to include assessments of other measures of health, including eyes and vision. The eye assessment at baseline included questionnaires detailing past ophthalmic and family history, measurement of visual acuity, refractive error and keratometry, intraocular pressure (IOP), corneal biomechanics, spectral domain optical coherence tomography (OCT) of the macula and a disc-macula fundus photograph. Since recruitment, UK Biobank has collected accelerometer data and begun multimodal imaging data (including brain, heart and abdominal MRI) in 100 000 participants. Dense genotypic data and a panel of 20 biochemistry measures are available, and linkage to medical health records for the full cohort has begun. FINDINGS TO DATE: A total of 502 665 people aged between 40 and 69 were recruited to participate in UK Biobank. Of these, 117 175 took part in baseline assessment of vision, IOP, refraction and keratometry. A subgroup of 67 321 underwent OCT and retinal photography. The introduction of eye and vision measures in UK Biobank was accompanied by intensive training, support and a data monitoring quality control process. FUTURE PLANS: UK Biobank is one of the largest prospective cohorts worldwide with extensive data on ophthalmic diseases and conditions. Data collection is an ongoing process and a repeat of the baseline assessment including the questionnaires, measurements and sample collection will be performed in subsets of 25 000 participants every 2-3 years. The depth and breadth of this dataset, coupled with its open-access policy, will create a powerful resource for all researchers to investigate the eye diseases in later life

High-sensitivity cardiac troponin and the diagnosis of myocardial infarction in patients with renal impairment.

The benefit and utility of high-sensitivity cardiac troponin (hs-cTn) in the diagnosis of myocardial infarction in patients with kidney impairment is unclear. Here, we describe implementation of hs-cTnI testing on the diagnosis, management, and outcomes of myocardial infarction in patients with and without kidney impairment. Consecutive patients with suspected acute coronary syndrome enrolled in a stepped-wedge, cluster-randomized controlled trial were included in this pre-specified secondary analysis. Kidney impairment was defined as an eGFR under 60mL/min/1.73m2. The index diagnosis and primary outcome of type 1 and type 4b myocardial infarction or cardiovascular death at one year were compared in patients with and without kidney impairment following implementation of hs-cTnI assay with 99th centile sex-specific diagnostic thresholds. Serum creatinine concentrations were available in 46,927 patients (mean age 61 years; 47% women), of whom 9,080 (19%) had kidney impairment. hs-cTnIs were over 99th centile in 46% and 16% of patients with and without kidney impairment. Implementation increased the diagnosis of type 1 infarction from 12.4% to 17.8%, and from 7.5% to 9.4% in patients with and without kidney impairment (both significant). Patients with kidney impairment and type 1 myocardial infarction were less likely to undergo coronary revascularization (26% versus 53%) or receive dual anti-platelets (40% versus 68%) than those without kidney impairment, and this did not change post-implementation. In patients with hs-cTnI above the 99th centile, the primary outcome occurred twice as often in those with kidney impairment compared to those without (24% versus 12%, hazard ratio 1.53, 95% confidence interval 1.31 to 1.78). Thus, hs-cTnI testing increased the identification of myocardial injury and infarction but failed to address disparities in management and outcomes between those with and without kidney impairment

Mind the (treatment) gap: a global perspective on current and future strategies for prevention of fragility fractures

This narrative review considers the key challenges facing healthcare professionals and policymakers responsible for providing care to populations in relation to bone health. These challenges broadly fall into four distinct themes: (1) case finding and management of individuals at high risk of fracture, (2) public awareness of osteoporosis and fragility fractures, (3) reimbursement and health system policy and (4) epidemiology of fracture in the developing world. Findings from cohort studies, randomised controlled trials, systematic reviews and meta-analyses, in addition to current clinical guidelines, position papers and national and international audits, are summarised, with the intention of providing a prioritised approach to delivery of optimal bone health for all. Systematic approaches to case-finding individuals who are at high risk of sustaining fragility fractures are described. These include strategies and models of care intended to improve case finding for individuals who have sustained fragility fractures, those undergoing treatment with medicines which have an adverse effect on bone health and people who have diseases, whereby bone loss and, consequently, fragility fractures are a common comorbidity. Approaches to deliver primary fracture prevention in a clinically effective and cost-effective manner are also explored. Public awareness of osteoporosis is low worldwide. If older people are to be more pro-active in the management of their bone health, that needs to change. Effective disease awareness campaigns have been implemented in some countries but need to be undertaken in many more. A major need exists to improve awareness of the risk that osteoporosis poses to individuals who have initiated treatment, with the intention of improving adherence in the long term. A multisector effort is also required to support patients and their clinicians to have meaningful discussions concerning the risk-benefit ratio of osteoporosis treatment. With regard to prioritisation of fragility fracture prevention in national policy, there is much to be done. In the developing world, robust epidemiological estimates of fracture incidence are required to inform policy development. As the aging of the baby boomer generation is upon us, this review provides a comprehensive analysis of how bone health can be improved worldwide for all

Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation

Background: The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy. Methods: For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961–2007, median latest follow-up years 1980–2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU. Findings: For participants with diabetes, we observed a linear dose–response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43–2·97) when diagnosed at 30–39 years, 2·26 (2·08–2·45) at 40–49 years, 1·84 (1·72–1·97) at 50–59 years, 1·57 (1·47–1·67) at 60–69 years, and 1·39 (1·29–1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier. Interpretation: Every decade of earlier diagnosis of diabetes was associated with about 3–4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes. Funding: British Heart Foundation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK

Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis

The added value of incorporating information from repeated measurements of blood pressure and cholesterol for cardiovascular disease (CVD) risk prediction has not been rigorously assessed. We used data from the Emerging Risk Factors Collaboration on 191,445 adults (38 cohorts from across 17 countries with data from 1962-2014) with > 1 million measurements of systolic blood pressure, total cholesterol and high-density lipoprotein cholesterol; over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative means of repeated measurements and summary measures from longitudinal modelling of the repeated measurements were compared to models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analysed across studies. Compared to the single time point model, the cumulative means and the longitudinal models increased the C-index by 0.0040 (95% CI: 0.0023, 0.0057) and 0.0023 (0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared to the single time point model, overall net reclassification improvements were 0.0369 (0.0303, 0.0436) for the cumulative means model and 0.0177 (0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction