scholarly journals Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study

2019 ◽  
Author(s):  
Johnny Wang ◽  
Maria J. Knol ◽  
Aleksei Tiulpin ◽  
Florian Dubost ◽  
Marleen de Bruijne ◽  
...  
Keyword(s):  
Grey Matter ◽  
Proportional Hazards ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Chronological Age ◽  
Population Based Study ◽  
Age Gap ◽  
Incident Dementia ◽  
Brain Age ◽  
Age Prediction

Key PointsQuestionIs the gap between brain age predicted from MRI and chronological age associated with incident dementia in a general population of Dutch adults?FindingsBrain age was predicted using a deep learning model, using MRI-derived grey matter density maps. In a population based study including 5496 participants, the observed gap was significantly associated with the risk of dementia.MeaningThe gap between MRI-brain predicted and chronological age is potentially a biomarker for dementia risk screening.AbstractImportanceThe gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as biomarker for early-stage neurodegeneration and potentially as a risk indicator for dementia. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link.ObjectiveWe aimed to investigate the utility of such a gap as a risk biomarker for incident dementia in a general Dutch population, using a deep learning approach for predicting brain age based on MRI-derived grey matter maps.DesignData was collected from participants of the cohort-based Rotterdam Study who underwent brain magnetic resonance imaging between 2006 and 2015. This study was performed in a longitudinal setting and all participant were followed up for incident dementia until 2016.SettingThe Rotterdam Study is a prospective population-based study, initiated in 1990 in the suburb Ommoord of in Rotterdam, the Netherlands.ParticipantsAt baseline, 5496 dementia- and stroke-free participants (mean age 64.67±9.82, 54.73% women) were scanned and screened for incident dementia. During 6.66±2.46 years of follow-up, 159 people developed dementia.Main outcomes and measuresWe built a convolutional neural network (CNN) model to predict brain age based on its MRI. Model prediction performance was measured in mean absolute error (MAE). Reproducibility of prediction was tested using the intraclass correlation coefficient (ICC) computed on a subset of 80 subjects. Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for years of education, ApoEε4 allele carriership, grey matter volume and intracranial volume. Additionally, we computed the attention maps of CNN, which shows which brain regions are important for age prediction.ResultsMAE of brain age prediction was 4.45±3.59 years and ICC was 0.97 (95% confidence interval CI=0.96-0.98). Logistic regression and Cox proportional hazards models showed that the age gap was significantly related to incident dementia (odds ratio OR=1.11 and 95% confidence intervals CI=1.05-1.16; hazard ratio HR=1.11 and 95% CI=1.06-1.15, respectively). Attention maps indicated that grey matter density around the amygdalae and hippocampi primarily drive the age estimation.Conclusion and relevanceWe show that the gap between predicted and chronological brain age is a biomarker associated with risk of dementia development. This suggests that it can be used as a biomarker, complimentary to those that are known, for dementia risk screening.

scholarly journals Gray Matter Age Prediction as a Biomarker for Risk of Dementia

2019 ◽  
Vol 116 (42) ◽  
pp. 21213-21218 ◽  
Author(s):  
Johnny Wang ◽  
Maria J. Knol ◽  
Aleksei Tiulpin ◽  
Florian Dubost ◽  
Marleen de Bruijne ◽  
...  
Keyword(s):  
Gray Matter ◽  
Proportional Hazards ◽  
Early Stage ◽  
Hippocampal Volume ◽  
Cox Proportional Hazards ◽  
Intracranial Volume ◽  
Age Gap ◽  
Incident Dementia ◽  
Brain Age ◽  
Age Prediction

The gap between predicted brain age using magnetic resonance imaging (MRI) and chronological age may serve as a biomarker for early-stage neurodegeneration. However, owing to the lack of large longitudinal studies, it has been challenging to validate this link. We aimed to investigate the utility of such a gap as a risk biomarker for incident dementia using a deep learning approach for predicting brain age based on MRI-derived gray matter (GM). We built a convolutional neural network (CNN) model to predict brain age trained on 3,688 dementia-free participants of the Rotterdam Study (mean age 66 ± 11 y, 55% women). Logistic regressions and Cox proportional hazards were used to assess the association of the age gap with incident dementia, adjusted for age, sex, intracranial volume, GM volume, hippocampal volume, white matter hyperintensities, years of education, and APOE ε4 allele carriership. Additionally, we computed the attention maps, which shows which regions are important for age prediction. Logistic regression and Cox proportional hazard models showed that the age gap was significantly related to incident dementia (odds ratio [OR] = 1.11 and 95% confidence intervals [CI] = 1.05–1.16; hazard ratio [HR] = 1.11, and 95% CI = 1.06–1.15, respectively). Attention maps indicated that GM density around the amygdala and hippocampi primarily drove the age estimation. We showed that the gap between predicted and chronological brain age is a biomarker, complimentary to those that are known, associated with risk of dementia, and could possibly be used for early-stage dementia risk screening.

Diet Inflammatory Index and Dementia Incidence: A Population-Based Study

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012973
Author(s):  
Sokratis Charisis ◽  
Eva Ntanasi ◽  
Mary Yannakoulia ◽  
Costas A Anastasiou ◽  
Mary H Kosmidis ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Community Dwelling ◽  
Dietary Interventions ◽  
Clinical Criteria ◽  
Inflammatory Index ◽  
Incident Dementia ◽  
Dementia Incidence ◽  
Increased Risk

Background and objectives:Aging is characterized by a functional shift of the immune system towards a proinflammatory phenotype. This derangement has been associated with cognitive decline and has been implicated in the pathogenesis of dementia. Diet can modulate systemic inflammation; thus, it may be a valuable tool to counteract the associated risks for cognitive impairment and dementia. The present study aimed to explore the associations between the inflammatory potential of diet, assessed using an easily applicable, population-based, biomarker-validated diet inflammatory index (DII), and the risk for dementia in community-dwelling older adults.Methods:Individuals from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) were included in the present cohort study. Participants were recruited through random population sampling, and were followed for a mean of 3.05 (SD=0.85) years. Dementia diagnosis was based on standard clinical criteria. Those with baseline dementia and/or missing cognitive follow-up data were excluded from the analyses. The inflammatory potential of diet was assessed through a DII score which considers literature-derived associations of 45 food parameters with levels of pro- and anti-inflammatory cytokines in the blood; higher values indicated a more pro-inflammatory diet. Consumption frequencies were derived from a detailed food frequency questionnaire, and were standardized to representative dietary intake normative data from 11 different countries. Analysis of dementia incidence as a function of baseline DII scores was performed by Cox proportional hazards models.Results:Analyses included 1059 individuals (mean age=73.1 years; 40.3% males; mean education=8.2 years), 62 of whom developed incident dementia. Each additional unit of DII was associated with a 21% increase in the risk for dementia incidence [HR=1.21 (1.03 – 1.42); p=0.023]. Compared to participants in the lowest DII tertile, participants in the highest one (maximal pro-inflammatory diet potential) were 3 [(1.2 – 7.3); p=0.014] times more likely to develop incident dementia. The test for trend was also significant, indicating a potential dose-response relationship (p=0.014).Conclusions:In the present study, higher DII scores (indicating greater pro-inflammatory diet potential) were associated with an increased risk for incident dementia. These findings might avail the development of primary dementia preventive strategies through tailored and precise dietary interventions.

scholarly journals Reliable longitudinal brain age prediction in stroke patients: Associations with cognitive function and response to cognitive training

2019 ◽  
Author(s):  
Geneviève Richard ◽  
Knut Kolskår ◽  
Kristine M. Ulrichsen ◽  
Tobias Kaufmann ◽  
Dag Alnæs ◽  
...  
Keyword(s):  
Cognitive Training ◽  
Outcome Prediction ◽  
Cognitive Intervention ◽  
Chronological Age ◽  
Double Blind Study ◽  
Stroke Patients ◽  
Brain Morphometry ◽  
Age Gap ◽  
Brain Age ◽  
Age Prediction

AbstractCognitive deficits are important predictors for outcome, independence and quality of life after stroke, but often remain unnoticed and unattended because other impairments are more evident. Computerized cognitive training (CCT) is among the candidate interventions that may alleviate cognitive difficulties, but the evidence supporting its feasibility and effectiveness is scarce, partly due to the lack of tools for outcome prediction and monitoring. Magnetic resonance imaging (MRI) provides candidate markers for disease monitoring and outcome prediction. By integrating information not only about lesion extent and localization, but also regarding the integrity of the unaffected parts of the brain, advanced MRI provides relevant information for developing better prediction models in order to tailor cognitive intervention for patients, especially in a chronic phase.Using brain age prediction based on MRI based brain morphometry and machine learning, we tested the hypotheses that stroke patients with a younger-appearing brain relative to their chronological age perform better on cognitive tests and benefit more from cognitive training compared to patients with an older-appearing brain. In this randomized double-blind study, 54 patients who suffered mild stroke (>6 months since hospital admission, NIHSS<7 at hospital discharge) underwent 3-weeks CCT and MRI before and after the intervention. In addition, patients were randomized to one of two groups receiving either active or sham transcranial direct current stimulation (tDCS). We tested for main effects of brain age gap (estimated age – chronological age) on cognitive performance, and associations between brain age gap and task improvement. Finally, we tested if longitudinal changes in brain age gap during the intervention were sensitive to treatment response. Briefly, our results suggest that longitudinal brain age prediction based on automated brain morphometry is feasible and reliable in stroke patients. However, no significant association between brain age and both performance and response to cognitive training were found.

scholarly journals Aspirin and Risk of Dementia in Patients with Late-Onset Depression: A Population-Based Cohort Study

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Ya-Hsu Yang ◽  
Chih-Chiang Chiu ◽  
Hao-Wei Teng ◽  
Chun-Teng Huang ◽  
Chun-Yu Liu ◽  
...  
Keyword(s):  
Cumulative Incidence ◽  
Propensity Scores ◽  
Nearest Neighbor ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Late Onset ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Incident Dementia

Background. Late onset depression (LOD) often occurs in the context of vascular disease and may be associated with risk of dementia. Aspirin is widely used to reduce the risk of cardiovascular disease and stroke. However, its role in patients with LOD and risk of dementia remains inconclusive. Materials and Methods. A population-based study was conducted using data from National Health Insurance of Taiwan during 1996–2009. Patients fulfil diagnostic criteria for LOD with or without subsequent dementia (incident dementia) and among whom users of aspirin (75 mg daily for at least 6 months) were identified. The time-dependent Cox proportional hazards model was applied for multivariate analyses. Propensity scores with the one-to-one nearest-neighbor matching model were used to select matching patients. Cumulative incidence of incident dementia after diagnosis of LOD was calculated by Kaplan–Meier Method. Results. A total of 6028 (13.4%) and 40,411 (86.6%) patients were defined as, with and without diagnosis of LOD, among whom 2,424 (41.9%) were aspirin users. Patients with LOD had more comorbidities such as cardiovascular diseases, diabetes, and hypertension comparing to those without LOD. Among patients with LOD, aspirin users had lower incidence of subsequent incident dementia than non-users (Hazard Ratio = 0.734, 95% CI 0.641–0.841, p<0.001). After matching aspirin users with non-users by propensity scores-matching method, the cumulative incidence of incident dementia was significantly lower in aspirin users of LOD patients (p=0.022). Conclusions. Aspirin may be associated with a lower risk of incident dementia in patients with LOD. This beneficial effect of aspirin in LOD patients needs validation in prospective clinical trials and our results should be interpreted with caution.

scholarly journals Endoscopic and Surgical Treatment of T1N0M0 Colorectal Neuroendocrine Tumors: A Population-Based Comparative Study

2020 ◽  
Author(s):  
Hanlong Zhu ◽  
Si Zhao ◽  
Kun Ji ◽  
Wei Wu ◽  
Jian Zhou ◽  
...  
Keyword(s):  
Neuroendocrine Tumors ◽  
Tumor Size ◽  
Proportional Hazards ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Treatment Modalities ◽  
Cancer Specific Survival ◽  
Term Survival ◽  
Population Based Study

Abstract Background: With the rapid advances in endoscopic technology, endoscopic therapy (ET) is increasingly applied to the treatment of small (≤20 mm) colorectal neuroendocrine tumors (NETs). However, long-term data comparing ET and surgery for management of T1N0M0 colorectal NETs are lacking. The purpose of this work was to compare overall survival (OS) and cancer-specific survival (CSS) of such patients with ET or surgery.Methods: Patients with T1N0M0 colorectal NETs were identified within the Surveillance Epidemiology and End Results (SEER) database (2004-2016). Demographics, tumor characteristics, therapeutic methods, and survival were compared. Propensity score matching (PSM) was used 1:3 and among this cohort, Cox proportional hazards regression models were performed to evaluate correlation between treatment and outcomes.Results: Of 4487 patients with T1N0M0 colorectal NETs, 1125 were identified in the matched cohort, among whom 819 (72.8%) underwent ET and 306 (27.2%) underwent surgery. There was no difference in the 5-year and 10-year OS and CSS rates between the 2 treatment modalities. Likewise, analyses stratified by tumor size and site showed that patients did not benefit more from surgery compared with ET. Moreover, multivariate analyses found no significant differences in OS [Hazard Ratio (HR) = 0.857, 95% Confidence Interval (CI): 0.513–1.431, P = 0.555] and CSS (HR = 0.925, 95% CI: 0.282–3.040, P = 0.898) between the 2 groups. Similar results were observed when comparisons were limited to patients with different tumor size and site.Conclusions: In this population-based study, patients treated endoscopically had comparable long-term survival compared with those treated surgically, which demonstrates ET as an alternative to surgery in T1N0M0 colorectal NETs.

scholarly journals Incidence of Venous Thromboembolism and Impact on Mortality in Patients with Primary CNS Lymphoma: A Population Based Study

Blood ◽  
2017 ◽  
Vol 130 (Suppl_1) ◽  
pp. 754-754
Author(s):  
Anjlee Mahajan ◽  
Ann M Brunson ◽  
Theresa H.M. Keegan ◽  
Aaron S. Rosenberg ◽  
Ted Wun
Keyword(s):  
Major Bleeding ◽  
Proportional Hazards ◽  
Large Population ◽  
Steering Committee ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Population Based Study ◽  
Risk Of Death ◽  
Proportional Hazards Regression ◽  
Increased Risk

Abstract Background: Venous thromboembolism (VTE) is a known complication of cancer, with a high incidence in patients with both gliomas and lymphoma. Recent studies have shown a high risk of intracranial bleeding in glioma patients treated for VTE with anticoagulation. To date, there are no large, population-based studies describing the incidence of VTE in patients with primary central nervous system lymphoma (PCNSL). Methods: Using the California Cancer Registry, we identified patients with a first histologic diagnosis of PCNSL from 2005-2014 and linked these cases to the California hospitalization and emergency department databases. Patients with a VTE within 6 months prior to PCNSL diagnosis were excluded (n=11). We calculated cumulative incidence of VTE and major bleeding and associated 95% confidence intervals (CI), adjusted for the competing risk of death. Multivariable Cox proportional hazards regression models, using the methods of Fine and Gray to adjust for competing risk of death, were used to analyze factors associated with VTE and major bleeding. Models included sex, race/ethnicity, age at diagnosis, neighborhood sociodemographic status, health insurance at diagnosis, Elixhauser comorbidities, HIV status, initial treatment (chemotherapy, radiation, or CNS procedure), and prior VTE (&gt; 6 months prior to diagnosis). The major bleeding model additionally included VTE type as a time dependent covariate. The association of VTE and major bleeding with PCNSL-specific mortality was analyzed using multivariable Cox proportional hazards regression models; VTE and major bleeding were included as time dependent covariates. Results are presented as adjusted hazard ratios (HR) and 95% CI. Results: There were 992 patients with a PCNSL identified. VTE occurred in 143 patients (14.4%). Of the VTE events, 52% were pulmonary emboli [(PE +/- deep vein thrombosis (DVT)], 23% proximal DVT and 22% distal DVT. The 3- and 12-month cumulative incidences of VTE were 10.2% (CI: 8.4-12.2%) and 13.6% (CI: 11.5-15.8%), respectively (Figure 1). Patients who received chemotherapy had over 2-fold increased risk of developing VTE (HR=2.42, CI: 1.33-4.42) compared to those who did not receive chemotherapy, and those who received radiation were also at increased risk of VTE (HR=1.56 CI: 1.07-2.27). Asian/Pacific Islanders had a decreased risk of VTE compared to non-Hispanic Whites (HR=0.37, CI: 0.21-0.66). Major bleeding occurred in 156 patients (15.7%). Of the major bleeding events, 53% were intracranial hemorrhage, 33% were gastrointestinal bleeds, 12% of patients required a transfusion and 3% had unspecified bleeding. The 3- and 12-month cumulative incidences of major bleeding were 9.8% (CI: 8.1-11.8%) and 13.2% (CI: 11.1-15.3%), respectively (Figure 2). PE and proximal DVT were associated with increased risk of major bleeding (HR=4.57, CI: 2.43-8.60 and HR=5.95, CI: 2.47-14.34, respectively). In the PCNSL specific mortality models, PE was associated with increased risk of death (HR=1.81, CI: 1.14-2.87), though DVT (proximal or distal) was not. Patients with major bleeding were at over 2-fold increased risk of PCNSL death compared to those without major bleeding (HR=2.34, CI: 1.71-3.19). Conclusions: The incidence of VTE in this large population-based study of patients with PCNSL was high at 14.4%, with most VTE events occurring within the first 3 months after diagnosis. Risk factors associated with VTE included treatment with either chemotherapy or radiation. PE and proximal DVT were associated with increased risk of major bleeding, suggesting these patients may have received anticoagulation, and as recently shown in glioma patients, are at a high risk of intracranial hemorrhage. In addition, PE and major bleeding were both independently associated with higher PCNSL mortality. Disclosures Wun: Janssen: Other: Study steering committee and research support (site PI); Pfizer: Other: Study steering committee and research support (site PI).

scholarly journals O2.3. ABNORMAL BRAIN AGING IN YOUTH WITH SUBCLINICAL PSYCHOSIS AND OBSESSIVE-COMPULSIVE SYMPTOMS

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S4-S4
Author(s):  
Vanessa Cropley ◽  
Ye Tian ◽  
Kavisha Fernando ◽  
Sina Mansour ◽  
Christos Pantelis ◽  
...  
Keyword(s):  
Brain Structure ◽  
Grey Matter ◽  
Psychiatric Symptoms ◽  
Chronological Age ◽  
Typically Developing ◽  
Obsessive Compulsive ◽  
General Psychopathology ◽  
Age Gap ◽  
Brain Age ◽  
Age And Sex

Abstract Background Psychiatric symptoms in childhood and adolescence have been associated with both delayed and accelerated patterns of grey matter development. This suggests that deviation in brain structure from a normative range of variation for a given age might be important in the emergence of psychopathology. Distinct from chronological age, brain age refers to the age of an individual that is inferred from a normative model of brain structure for individuals of the same age and sex. We predicted brain age from a common set of grey matter features and examined whether the difference between an individual’s chronological and brain age was associated with the severity of psychopathology in children and adolescents. Methods Participants included 1313 youths (49.8% male) aged 8–21 who underwent structural imaging as part of the Philadelphia Neurodevelopmental Cohort. Independent Component Analysis was used to obtain 7 psychopathology dimensions representing Conduct, Anxiety, Obsessive-Compulsive, Attention, Depression, Bipolar, and Psychosis symptoms and an overall measure of severity (General Psychopathology). Using 10-fold cross-validation, support vector machine regression was trained in 402 typically developing youth to predict individual age based on a feature space comprising 111 grey matter regions. This yielded a brain age prediction for each individual. Brain age gap was calculated for each individual by subtracting chronological age from predicted brain age. The general linear model was used to test for an association between brain age gap and each of the 8 dimensions of psychopathology in a test sample of 911 youth. The regional specificity and spatial pattern of brain age gap was also investigated. Error control across the 8 models was achieved with a false discovery rate of 5%. Results Brain age gap was significantly associated with dimensions characterizing obsessive-compulsive (t=2.5, p=0.01), psychosis (t=3.16, p=0.0016) and general psychopathology (t=4.08, p&lt;0.0001). For all three dimensions, brain age gap was positively associated with symptom severity, indicating that individuals with a brain that was predicted to be ‘older’ than expectations set by youth of the same chronological age and sex tended to have higher symptom scores. Findings were confirmed with a categorical approach, whereby higher brain age gap was observed in youth with a lifetime endorsement of psychosis (t=2.35, p=0.02) and obsessive-compulsive (t=2.35, p=0.021) symptoms, in comparison to typically developing individuals. Supplementary analyses revealed that frontal grey matter was the most important feature mediating the association between brain age gap and psychosis symptoms, whereas subcortical volumes were most important for the association between brain age gap and obsessive-compulsive and general symptoms. Discussion We found that the brain was ‘older’ in youth experiencing higher subclinical symptoms of psychosis, obsession-compulsion, and general psychopathology, compared to normally developing youth of the same chronological age. Our results suggest that deviations in normative brain age patterns in youth may contribute to the manifestation of specific psychiatric symptoms of subclinical severity that cut across psychopathology dimensions.

scholarly journals Parity and the risk of incident dementia: a COSMIC study

2020 ◽  
Vol 29 ◽  
Author(s):  
J. B. Bae ◽  
D. M. Lipnicki ◽  
J. W. Han ◽  
P. S. Sachdev ◽  
T. H. Kim ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Community Dwelling ◽  
Alzheimer Dementia ◽  
Grand Multiparity ◽  
Incident Dementia

Abstract Aims To investigate the association between parity and the risk of incident dementia in women. Methods We pooled baseline and follow-up data for community-dwelling women aged 60 or older from six population-based, prospective cohort studies from four European and two Asian countries. We investigated the association between parity and incident dementia using Cox proportional hazards regression models adjusted for age, educational level, hypertension, diabetes mellitus and cohort, with additional analysis by dementia subtype (Alzheimer dementia (AD) and non-Alzheimer dementia (NAD)). Results Of 9756 women dementia-free at baseline, 7010 completed one or more follow-up assessments. The mean follow-up duration was 5.4 ± 3.1 years and dementia developed in 550 participants. The number of parities was associated with the risk of incident dementia (hazard ratio (HR) = 1.07, 95% confidence interval (CI) = 1.02–1.13). Grand multiparity (five or more parities) increased the risk of dementia by 30% compared to 1–4 parities (HR = 1.30, 95% CI = 1.02–1.67). The risk of NAD increased by 12% for every parity (HR = 1.12, 95% CI = 1.02–1.23) and by 60% for grand multiparity (HR = 1.60, 95% CI = 1.00–2.55), but the risk of AD was not significantly associated with parity. Conclusions Grand multiparity is a significant risk factor for dementia in women. This may have particularly important implications for women in low and middle-income countries where the fertility rate and prevalence of grand multiparity are high.

scholarly journals Haematological abnormalities in new-onset rheumatoid arthritis and risk of common infections: a population-based study

Rheumatology ◽  
2019 ◽  
Vol 59 (5) ◽  
pp. 997-1005 ◽  
Author(s):  
Elena Nikiphorou ◽  
Simon de Lusignan ◽  
Christian Mallen ◽  
Kaivan Khavandi ◽  
Jacqueline Roberts ◽  
...  
Keyword(s):  
Primary Care ◽  
Influenza Vaccination ◽  
Proportional Hazards ◽  
Population Based ◽  
Infection Risk ◽  
Cox Proportional Hazards ◽  
Population Based Study ◽  
Cox Proportional Hazards Models ◽  
The Uk ◽  
Common Infections

Abstract Objectives To describe the prevalence of haematological abnormalities in individuals with RA at the point of diagnosis in primary care and the associations between haematological abnormalities, vaccinations and subsequent risk of common infections. Methods We studied 6591 individuals with newly diagnosed RA between 2004 and 2016 inclusive using the UK Royal College of General Practitioners Research and Surveillance Centre primary care database. The prevalence of haematological abnormalities at diagnosis (anaemia, neutropenia and lymphopenia) was established. Cox proportional hazards models were used to evaluate the association between each haematological abnormality and time to common infections and the influence of vaccination status (influenza and pneumococcal vaccine) on time to common infections in individuals with RA compared with a matched cohort of individuals without RA. Results Anaemia was common at RA diagnosis (16.1% of individuals), with neutropenia (0.6%) and lymphopenia (1.4%) less so. Lymphopenia and anaemia were associated with increased infection risk [hazard ratio (HR) 1.18 (95% CI 1.08, 1.29) and HR 1.37 (95% CI 1.08, 1.73), respectively]. There was no evidence of an association between neutropenia and infection risk [HR 0.94 (95% CI 0.60, 1.47)]. Pneumonia was much more common in individuals with early RA compared with controls. Influenza vaccination was associated with reduced risk of influenza-like illness only for individuals with RA [HR 0.58 (95% CI 0.37, 0.90)]. Conclusion At diagnosis, anaemia and lymphopenia, but not neutropenia, increase the risk of common infections in individuals with RA. Our data support the effectiveness of the influenza vaccination in individuals with RA.

scholarly journals Multimorbidity among persons aged 25–64 years: a population-based study of social determinants and all-cause mortality

2020 ◽  
Author(s):  
F R Ferry ◽  
M G Rosato ◽  
E J Curran ◽  
D O’Reilly ◽  
G Leavey
Keyword(s):  
Social Determinants ◽  
Proportional Hazards ◽  
Strong Association ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Younger Adults ◽  
Population Based Study ◽  
Cox Proportional Hazards Models ◽  
Health And Social Care ◽  
All Cause Mortality

Abstract Background Despite increasing multimorbidity across the lifespan, little is known about the co-occurrence of conditions and risk factors among younger adults. This population-based study examines multimorbidity, social determinants and associated mortality among younger and middle-age adults. Method Analysis was based on the Northern Ireland population aged 25–64 years enumerated in the 2011 Census (n = 878 345), with all-cause mortality follow-up to 2014 (8659 deaths). Logistic regression was used to examine social determinants and Cox proportional hazards models in the analysis of associated mortality. Results Prevalence of multimorbidity was 13.7% in females and 12.7% in males. There was a strong association between multimorbidity that included mental/cognitive illness and deprivation. Among those never married, multimorbid physical conditions were less likely [relative risk ratios (RRR) = 0.92: 95% confidence interval (CI) = 0.88, 0.95 for males; and RRR = 0.90: 0.87, 0.94 for females]. Rurality was associated with lower physical multimorbidity (RRR = 0.92: 0.89, 0.95) but higher mental/cognitive multimorbidity (RRR = 1.35: 1.12, 1.64) among females. All multimorbid categories were associated with elevated risk of mortality. Conclusion The health and economic challenges created by multimorbidity should be addressed further ‘upstream’. Future multimorbidity research should include younger adults to inform the development of preventative interventions and align health and social care services more closely with patients’ needs.

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