To improve the treatment of painful Diabetic Peripheral Neuropathy (DPN) and associated co-morbidities, a better understanding of the pathophysiology and risk factors for painful DPN is required. ...Using harmonised cohorts (N = 1230) we have built models that classify painful versus painless DPN using quality of life (EQ5D), lifestyle (smoking, alcohol consumption), demographics (age, gender), personality and psychology traits (anxiety, depression, personality traits), biochemical (HbA1c) and clinical variables (BMI, hospital stay and trauma at young age) as predictors.
The Random Forest, Adaptive Regression Splines and Naive Bayes machine learning models were trained for classifying painful/painless DPN. Their performance was estimated using cross-validation in large cross-sectional cohorts (N = 935) and externally validated in a large population-based cohort (N = 295). Variables were ranked for importance using model specific metrics and marginal effects of predictors were aggregated and assessed at the global level. Model selection was carried out using the Mathews Correlation Coefficient (MCC) and model performance was quantified in the validation set using MCC, the area under the precision/recall curve (AUPRC) and accuracy.
Random Forest (MCC = 0.28, AUPRC = 0.76) and Adaptive Regression Splines (MCC = 0.29, AUPRC = 0.77) were the best performing models and showed the smallest reduction in performance between the training and validation dataset. EQ5D index, the 10-item personality dimensions, HbA1c, Depression and Anxiety t-scores, age and Body Mass Index were consistently amongst the most powerful predictors in classifying painful vs painless DPN.
Machine learning models trained on large cross-sectional cohorts were able to accurately classify painful or painless DPN on an independent population-based dataset. Painful DPN is associated with more depression, anxiety and certain personality traits. It is also associated with poorer self-reported quality of life, younger age, poor glucose control and high Body Mass Index (BMI). The models showed good performance in realistic conditions in the presence of missing values and noisy datasets. These models can be used either in the clinical context to assist patient stratification based on the risk of painful DPN or return broad risk categories based on user input. Model's performance and calibration suggest that in both cases they could potentially improve diagnosis and outcomes by changing modifiable factors like BMI and HbA1c control and institute earlier preventive or supportive measures like psychological interventions.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
PurposeNeuropathic pain is a common disorder of the somatosensory system that affects 7%–10% of the general population. The disorder places a large social and economic burden on patients as well as ...healthcare services. However, not everyone with a relevant underlying aetiology develops corresponding pain. DOLORisk Dundee, a European Union-funded cohort, part of the multicentre DOLORisk consortium, was set up to increase current understanding of this variation in onset. In particular, the cohort will allow exploration of psychosocial, clinical and genetic predictors of neuropathic pain onset.ParticipantsDOLORisk Dundee has been constructed by rephenotyping two pre-existing Scottish population cohorts for neuropathic pain using a standardised ‘core’ study protocol: Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) (n=5236) consisting of predominantly type 2 diabetics from the Tayside region, and Generation Scotland: Scottish Family Health Study (GS:SFHS; n=20 221). Rephenotyping was conducted in two phases: a baseline postal survey and a combined postal and online follow-up survey. DOLORisk Dundee consists of 9155 participants (GoDARTS=1915; GS:SFHS=7240) who responded to the baseline survey, of which 6338 (69.2%; GoDARTS=1046; GS:SFHS=5292) also responded to the follow-up survey (18 months later).Findings to dateAt baseline, the proportion of those with chronic neuropathic pain (Douleur Neuropathique en 4 Questions questionnaire score ≥3, duration ≥3 months) was 30.5% in GoDARTS and 14.2% in Generation Scotland. Electronic record linkage enables large scale genetic association studies to be conducted and risk models have been constructed for neuropathic pain.Future plansThe cohort is being maintained by an access committee, through which collaborations are encouraged. Details of how to do this will be available on the study website (http://dolorisk.eu/). Further follow-up surveys of the cohort are planned and funding applications are being prepared to this effect. This will be conducted in harmony with similar pain rephenotyping of UK Biobank.
Chronic pain (CP) is a common and often debilitating disorder that has major social and economic impacts. A subset of patients develop CP that significantly interferes with their activities of daily ...living and requires a high level of healthcare support. The challenge for treating physicians is in preventing the onset of refractory CP or effectively managing existing pain. To be able to do this, it is necessary to understand the risk factors, both genetic and environmental, for the onset of CP and response to treatment, as well as the pathogenesis of the disorder, which is highly heterogenous. However, studies of CP, particularly pain with neuropathic characteristics, have been hindered by a lack of consensus on phenotyping and data collection, making comparisons difficult. Furthermore, existing cohorts have suffered from small sample sizes meaning that analyses, especially genome-wide association studies, are insufficiently powered. The key to overcoming these issues is through the creation of large consortia such as DOLORisk and PAINSTORM and biorepositories, such as UK Biobank, where a common approach can be taken to CP phenotyping, which allows harmonisation across different cohorts and in turn increased study power. This review describes the approach that was used for studying neuropathic pain in DOLORisk and how this has informed current projects such as PAINSTORM, the rephenotyping of UK Biobank, and other endeavours. Moreover, an overview is provided of the outputs from these studies and the lessons learnt for future projects.
Background:
Neuropathic pain is an increasingly prevalent condition and has a major impact on health and quality of life. However, the risk factors for the development and maintenance of neuropathic ...pain are poorly understood. Clinical, genetic and psychosocial factors all contribute to chronic pain, but their interactions have not been studied in large cohorts. The DOLORisk study aims to study these factors.
Protocol:
Multicentre cross-sectional and longitudinal cohorts covering the main causes leading to neuropathic pain (e.g. diabetes, surgery, chemotherapy, traumatic injury), as well as rare conditions, follow a common protocol for phenotyping of the participants. This core protocol correlates answers given by the participants on a set of questionnaires with the results of their genetic analyses. A smaller number of participants undergo deeper phenotyping procedures, including neurological examination, nerve conduction studies, threshold tracking, quantitative sensory testing, conditioned pain modulation and electroencephalography.
Ethics and dissemination:
All studies have been approved by their regional ethics committees as required by national law. Results are disseminated through the
DOLORisk website
, scientific meetings, open-access publications, and in partnership with patient organisations.
Strengths and limitations:
Large cohorts covering many possible triggers for neuropathic pain
Multi-disciplinary approach to study the interaction of clinical, psychosocial and genetic risk factors
High comparability of the data across centres thanks to harmonised protocols
One limitation is that the length of the questionnaires might reduce the response rate and quality of responses of participants
Abstract It is still unclear how and why some patients develop painful and others painless polyneuropathy. The aim of this study was to identify multiple factors associated with painful ...polyneuropathies (NeuP). A total of 1181 patients of the multicenter DOLORISK database with painful (probable or definite NeuP) or painless (unlikely NeuP) probable or confirmed neuropathy were investigated clinically, with questionnaires and quantitative sensory testing. Multivariate logistic regression including all variables (demographics, medical history, psychological symptoms, personality items, pain-related worrying, life-style factors, as well as results from clinical examination and quantitative sensory testing) and machine learning was used for the identification of predictors and final risk prediction of painful neuropathy. Multivariate logistic regression demonstrated that severity and idiopathic etiology of neuropathy, presence of chronic pain in family, Patient-Reported Outcomes Measurement Information System Fatigue and Depression T-Score, as well as Pain Catastrophizing Scale total score are the most important features associated with the presence of pain in neuropathy. Machine learning (random forest) identified the same variables. Multivariate logistic regression archived an accuracy above 78%, random forest of 76%; thus, almost 4 out of 5 subjects can be classified correctly. This multicenter analysis shows that pain-related worrying, emotional well-being, and clinical phenotype are factors associated with painful (vs painless) neuropathy. Results may help in the future to identify patients at risk of developing painful neuropathy and identify consequences of pain in longitudinal studies.
Abstract
Introduction:
Previous epidemiological studies of neuropathic pain have reported a range of prevalences and factors associated with the disorder.
Objectives:
This study aimed to verify these ...characteristics in a large UK cohort.
Methods:
A cross-sectional analysis was conducted of 148,828 UK Biobank participants who completed a detailed questionnaire on chronic pain. The
Douleur Neuropathique en Quatre Questions
(DN4) was used to distinguish between neuropathic pain (NeuP) and non-neuropathic pain (non-NeuP) in participants with pain of at least 3 months' duration. Participants were also identified with less than 3 months' pain or without pain (NoCP). Multivariable regression was used to identify factors associated with NeuP compared with non-NeuP and NoCP, respectively.
Results:
Chronic pain was present in 76,095 participants (51.1%). The overall prevalence of NeuP was 9.2%. Neuropathic pain was significantly associated with worse health-related quality of life, having a manual or personal service type occupation, and younger age compared with NoCP. As expected, NeuP was associated with diabetes and neuropathy, but also other pains (pelvic, postsurgical, and migraine) and musculoskeletal disorders (rheumatoid arthritis, osteoarthritis, and fibromyalgia). In addition, NeuP was associated with pain in the limbs and greater pain intensity and higher body mass index compared with non-NeuP. Female sex was associated with NeuP when compared with NoCP, whereas male sex was associated with NeuP when compared with non-NeuP.
Conclusion:
This is the largest epidemiological study of neuropathic pain to date. The results confirm that the disorder is common in a population of middle- to older-aged people with mixed aetiologies and is associated with a higher health impact than non-neuropathic pain.
Evidence on the short-term effects of fine and coarse particles on morbidity in Europe is scarce and inconsistent.
We aimed to estimate the association between daily concentrations of fine and coarse ...particles with hospitalizations for cardiovascular and respiratory conditions in eight Southern European cities, within the MED-PARTICLES project.
City-specific Poisson models were fitted to estimate associations of daily concentrations of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and their difference (PM2.5-10) with daily counts of emergency hospitalizations for cardiovascular and respiratory diseases. We derived pooled estimates from random-effects meta-analysis and evaluated the robustness of results to co-pollutant exposure adjustment and model specification. Pooled concentration-response curves were estimated using a meta-smoothing approach.
We found significant associations between all PM fractions and cardiovascular admissions. Increases of 10 μg/m3 in PM2.5, 6.3 μg/m3 in PM2.5-10, and 14.4 μg/m3 in PM10 (lag 0-1 days) were associated with increases in cardiovascular admissions of 0.51% (95% CI: 0.12, 0.90%), 0.46% (95% CI: 0.10, 0.82%), and 0.53% (95% CI: 0.06, 1.00%), respectively. Stronger associations were estimated for respiratory hospitalizations, ranging from 1.15% (95% CI: 0.21, 2.11%) for PM10 to 1.36% (95% CI: 0.23, 2.49) for PM2.5 (lag 0-5 days).
PM2.5 and PM2.5-10 were positively associated with cardiovascular and respiratory admissions in eight Mediterranean cities. Information on the short-term effects of different PM fractions on morbidity in Southern Europe will be useful to inform European policies on air quality standards.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Neuropathic pain is an increasingly prevalent condition and has a major impact on health and quality of life. However, the risk factors for the development and maintenance of neuropathic pain are ...poorly understood. Clinical, genetic and psychosocial factors all contribute to chronic pain, but their interactions have not been studied in large cohorts. The DOLORisk study aims to study these factors.
Multicentre cross-sectional and longitudinal cohorts covering the main causes leading to neuropathic pain (e.g. diabetes, surgery, chemotherapy, traumatic injury), as well as rare conditions, follow a common protocol for phenotyping of the participants. This core protocol correlates answers given by the participants on a set of questionnaires with the results of their genetic analyses. A smaller number of participants undergo deeper phenotyping procedures, including neurological examination, nerve conduction studies, threshold tracking, quantitative sensory testing, conditioned pain modulation and electroencephalography.
All studies have been approved by their regional ethics committees as required by national law. Results are disseminated through the DOLORisk website, scientific meetings, open-access publications, and in partnership with patient organisations.
Large cohorts covering many possible triggers for neuropathic painMulti-disciplinary approach to study the interaction of clinical, psychosocial and genetic risk factorsHigh comparability of the data across centres thanks to harmonised protocolsOne limitation is that the length of the questionnaires might reduce the response rate and quality of responses of participants.
Soil life supports the functioning and biodiversity of terrestrial ecosystems. Springtails (Collembola) are among the most abundant soil arthropods regulating soil fertility and flow of energy ...through above- and belowground food webs. However, the global distribution of springtail diversity and density, and how these relate to energy fluxes remains unknown. Here, using a global dataset representing 2470 sites, we estimate the total soil springtail biomass at 27.5 megatons carbon, which is threefold higher than wild terrestrial vertebrates, and record peak densities up to 2 million individuals per square meter in the tundra. Despite a 20-fold biomass difference between the tundra and the tropics, springtail energy use (community metabolism) remains similar across the latitudinal gradient, owing to the changes in temperature with latitude. Neither springtail density nor community metabolism is predicted by local species richness, which is high in the tropics, but comparably high in some temperate forests and even tundra. Changes in springtail activity may emerge from latitudinal gradients in temperature, predation and resource limitation in soil communities. Contrasting relationships of biomass, diversity and activity of springtail communities with temperature suggest that climate warming will alter fundamental soil biodiversity metrics in different directions, potentially restructuring terrestrial food webs and affecting soil functioning.
To assess the association between early empirical antibiotics and neonatal adverse outcomes in very preterm infants without risk factors for early-onset sepsis (EOS).
This is a secondary analysis of ...the EPIPAGE-2 study, a prospective national population-based cohort that included all liveborn infants at 22-31 completed weeks of gestation in France in 2011. Infants at high risk of EOS (ie, born after preterm labor or preterm premature rupture of membranes or from a mother who had clinical chorioamnionitis or had received antibiotics during the last 72 hours) were excluded. Early antibiotic exposure was defined as antibiotic therapy started at day 0 or day 1 of life, irrespective of the duration and type of antibiotics. We compared treated and untreated patients using inverse probability of treatment weighting based on estimated propensity scores.
Among 648 very preterm infants at low risk of EOS, 173 (26.2%) had received early antibiotic treatment. Early antibiotic exposure was not associated with death or late-onset sepsis or necrotizing enterocolitis (OR, 1.04; 95% CI, 0.72-1.50); however, it was associated with higher odds of severe cerebral lesions (OR, 2.71; 95% CI, 1.25-5.86) and moderate-severe bronchopulmonary dysplasia (BPD) (OR, 2.30; 95% CI, 1.21-4.38).
Early empirical antibiotic therapy administrated in very preterm infants at low risk of EOS was associated with a higher risk of severe cerebral lesions and moderate-severe BPD.
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