scholarly journals Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach

2020 ◽  
Vol 8 (1) ◽  
pp. e001550
Author(s):  
Omar Yaxmehen Bello-Chavolla ◽  
Jessica Paola Bahena-López ◽  
Arsenio Vargas-Vázquez ◽  
Neftali Eduardo Antonio-Villa ◽  
Alejandro Márquez-Salinas ◽  
...  
Keyword(s):  
Risk Factors ◽  
Training Sample ◽  
Population Based ◽  
Data Driven ◽  
Insulin Resistant ◽  
Age Related ◽  
Adult Onset Diabetes ◽  
Design And Methods ◽  
Incident Cases

IntroductionPrevious reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings.Research design and methodsWe trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999–2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup.ResultsSNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89).ConclusionsDiabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications.

scholarly journals Age-Related Risk Factors and Complications of Patients With COVID-19: A Population-Based Retrospective Study

2022 ◽  
Vol 8 ◽  
Author(s):  
Han Zhang ◽  
Yingying Wu ◽  
Yuqing He ◽  
Xingyuan Liu ◽  
Mingqian Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Retrospective Study ◽  
Age Groups ◽  
Clinical Manifestations ◽  
Population Based ◽  
Male Gender ◽  
Poor Correlation ◽  
Age Related ◽  
Related Risk ◽  
Independent Risk Factors

Objective: To study the differences in clinical characteristics, risk factors, and complications across age-groups among the inpatients with the coronavirus disease 2019 (COVID-19).Methods: In this population-based retrospective study, we included all the positive hospitalized patients with COVID-19 at Wuhan City from December 29, 2019 to April 15, 2020, during the first pandemic wave. Multivariate logistic regression analyses were used to explore the risk factors for death from COVID-19. Canonical correlation analysis (CCA) was performed to study the associations between comorbidities and complications.Results: There are 36,358 patients in the final cohort, of whom 2,492 (6.85%) died. Greater age (odds ration [OR] = 1.061 [95% CI 1.057–1.065], p < 0.001), male gender (OR = 1.726 [95% CI 1.582–1.885], p < 0.001), alcohol consumption (OR = 1.558 [95% CI 1.355–1.786], p < 0.001), smoking (OR = 1.326 [95% CI 1.055–1.652], p = 0.014), hypertension (OR = 1.175 [95% CI 1.067–1.293], p = 0.001), diabetes (OR = 1.258 [95% CI 1.118–1.413], p < 0.001), cancer (OR = 1.86 [95% CI 1.507–2.279], p < 0.001), chronic kidney disease (CKD) (OR = 1.745 [95% CI 1.427–2.12], p < 0.001), and intracerebral hemorrhage (ICH) (OR = 1.96 [95% CI 1.323–2.846], p = 0.001) were independent risk factors for death from COVID-19. Patients aged 40–80 years make up the majority of the whole patients, and them had similar risk factors with the whole patients. For patients aged <40 years, only cancer (OR = 17.112 [95% CI 6.264–39.73], p < 0.001) and ICH (OR = 31.538 [95% CI 5.213–158.787], p < 0.001) were significantly associated with higher odds of death. For patients aged >80 years, only age (OR = 1.033 [95% CI 1.008–1.059], p = 0.01) and male gender (OR = 1.585 [95% CI 1.301–1.933], p < 0.001) were associated with higher odds of death. The incidence of most complications increases with age, but arrhythmias, gastrointestinal bleeding, and sepsis were more common in younger deceased patients with COVID-19, with only arrhythmia reaching statistical difference (p = 0.039). We found a relatively poor correlation between preexisting risk factors and complications.Conclusions: Coronavirus disease 2019 are disproportionally affected by age for its clinical manifestations, risk factors, complications, and outcomes. Prior complications have little effect on the incidence of extrapulmonary complications.

scholarly journals Monoclonal gammopathy of undetermined significance is associated with prostate cancer in a population-based cohort study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicola Hornung ◽  
Mirjam Frank ◽  
Nico Dragano ◽  
Jan Dürig ◽  
Ulrich Dührsen ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Cohort Study ◽  
Monoclonal Gammopathy ◽  
Population Based ◽  
Effect Estimate ◽  
Supporting Evidence ◽  
Shared Risk ◽  
Incident Cases ◽  
Undetermined Significance

AbstractRegister-based studies indicate a possible association of monoclonal gammopathy of undetermined significance (MGUS) and prostate cancer (PCa). Aim of the present study was to investigate the relationship between MGUS and PCa considering potentially shared risk factors. Data from the prospective population-based Heinz Nixdorf Recall cohort study of 2.385 men (age 45–85) were analyzed. MGUS was determined at three points in time; cases of cancer were assessed annually. Potentially shared risk factors were assessed at baseline. Hazard ratios (HR), adjusted for age and educational attainment, and corresponding 95%-confidence intervals (95%-CI) were calculated. 157 cases of MGUS and 143 incident cases of PCa were detected. Of 19 participants diagnosed with both, MGUS and incident PCa, only in one case MGUS did not clearly occur before PCa. MGUS was associated with PCa presenting a HR of 2.00 (95%-CI: 1.23–3.25). Stratified by isotype, IgM-MGUS showed the strongest association with PCa. There was no relevant change of the effect estimate when adjusting for potentially shared risk factors. We were able to give supporting evidence for an association between MGUS and PCa and pointed out its temporality. There was no indication that the observed association is due to shared risk factors. The present study indicated that different isotypes of MGUS differ in the strength of the effect on PCa-risk. Based on these findings, future studies investigating the pathophysiological background of the association will be needed.

scholarly journals Increasing Incidence of Liposarcoma: A Population-Based Study of National Surveillance Databases, 2001–2016

2020 ◽  
Vol 17 (8) ◽  
pp. 2710 ◽  
Author(s):  
Suzanne Bock ◽  
Douglas G. Hoffmann ◽  
Yi Jiang ◽  
Hao Chen ◽  
Dora Il’yasova
Keyword(s):  
Risk Factors ◽  
Time Trends ◽  
Treatment Options ◽  
Three Dimensional ◽  
Cancer Registries ◽  
Population Based ◽  
Incidence Rates ◽  
Cancer Surveillance ◽  
Retroperitoneal Tumors ◽  
Incident Cases

Rare cancers, affecting 1 in 5 cancer patients, disproportionally contribute to cancer mortality. This research focuses on liposarcoma, an understudied rare cancer with unknown risk factors and limited treatment options. Liposarcoma incident cases were identified from the U.S. Surveillance, Epidemiology, and End Result (SEER) program and the combined SEER-National Program of Cancer Registries (CNPCR) between 2001–2016. Incidence rates (age-adjusted and age-specific), 5-year survival, and the time trends were determined using SEER*stat software. Three-dimensional visualization of age–time curves was conducted for males and females. SEER liposarcoma cases represented ~30% (n = 11,162) of the nationwide pool (N = 37,499). Both sources of data showed males accounting for ~60% of the cases; 82%–86% cases were identified among whites. Age-adjusted incidence was greater among males vs. females and whites vs. blacks, whereas survival did not differ by sex and race. The dedifferentiated (57.2%), pleomorphic (64.1%), and retroperitoneal (63.9%) tumors had the worse survival. Nationwide, liposarcoma rates increased by 19%, with the annual percent increase (APC) of 1.43% (95% confidence interval (CI): 1.12–1.74). The APC was greater for males vs. females (1.67% vs. 0.89%) and retroperitoneal vs. extremity tumors (1.94% vs. 0.58%). Thus, incidence increased faster in the high-risk subgroup (males), and for retroperitoneal tumors, the low-survival subtype. The SEER generally over-estimated the rates and time trends compared to nationwide data but under-estimated time trends for retroperitoneal tumors. The time trends suggest an interaction between genetic and non-genetic modifiable risk factors may play a role in the etiology of this malignancy. Differences between SEER and CNCPR findings emphasize the need for nationwide cancer surveillance.

scholarly journals Characterizing the type 2 diabetes mellitus epidemic in Jordan up to 2050

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Susanne F. Awad ◽  
Peijue Huangfu ◽  
Soha R. Dargham ◽  
Kamel Ajlouni ◽  
Anwar Batieha ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Population Level ◽  
Population Based ◽  
Incident Cases ◽  
Population Based Survey

AbstractWe aimed to characterize the type 2 diabetes mellitus (T2DM) epidemic and the role of key risk factors in Jordan between 1990–2050, and to forecast the T2DM-related costs. A recently-developed population-level T2DM mathematical model was adapted and applied to Jordan. The model was fitted to six population-based survey data collected between 1990 and 2017. T2DM prevalence was 14.0% in 1990, and projected to be 16.0% in 2020, and 20.6% in 2050. The total predicted number of T2DM cases were 218,326 (12,313 were new cases) in 1990, 702,326 (36,941 were new cases) in 2020, and 1.9 million (79,419 were new cases) in 2050. Out of Jordan’s total health expenditure, 19.0% in 1990, 21.1% in 2020, and 25.2% in 2050 was forecasted to be spent on T2DM. The proportion of T2DM incident cases attributed to obesity was 55.6% in 1990, 59.5% in 2020, and 62.6% in 2050. Meanwhile, the combined contribution of smoking and physical inactivity hovered around 5% between 1990 and 2050. Jordan’s T2DM epidemic is predicted to grow sizably in the next three decades, driven by population ageing and high and increasing obesity levels. The national strategy to prevent T2DM needs to be strengthened by focusing it on preventive interventions targeting T2DM and key risk factors.

scholarly journals Brain deep medullary veins on 3-T MRI in a population-based cohort

2020 ◽  
pp. 0271678X2091846
Author(s):  
Dong-Hui Ao ◽  
Ding-Ding Zhang ◽  
Fei-Fei Zhai ◽  
Jiang-Tao Zhang ◽  
Fei Han ◽  
...  
Keyword(s):  
Risk Factors ◽  
Brain Atrophy ◽  
Small Vessel Disease ◽  
Population Based ◽  
Vascular Risk Factors ◽  
Vascular Risk ◽  
Neurodegenerative Process ◽  
Age Related ◽  
Deep Medullary Veins

Our aim is to investigate whether vascular risk factors are associated with cerebral deep medullary veins (DMVs) and whether DMVs are associated with MRI markers of cerebral small vessel disease (CSVD) or risk of stroke. In a community-based cohort of 1056 participants (mean age 55.7 years), DMVs were identified on susceptibility-weighted imaging (SWI) and counted in periventricular regions. Neuroimaging markers including lacunes, whiter matter hyperintensity (WMH), microbleeds, enlarged perivascular space, and brain atrophy were evaluated. The number of DMVs decreased with age (p = 0.007). After adjusting for age and sex, the number of DMVs was not associated with traditional vascular risk factors. Fewer DMVs was associated with increase of WMH and lacunes, but the association vanished after adjustment for vascular risk factors. However, fewer DMVs were independently associated with brain atrophy (p < 0.001). DMVs were not associated with three-year risk of stroke. Our results suggest that DMV is significantly different from other MRI markers of CSVD regarding risk factors, association with other CSVD markers, and risk of stroke. Nonetheless, the significant association between DMV and brain atrophy suggested the potential role of venules in age-related neurodegenerative process, which deserves further investigation.

scholarly journals What factors explain the much higher diabetes prevalence in Russia compared with Norway? Major sex differences in the contribution of adiposity

2021 ◽  
Vol 9 (1) ◽  
pp. e002021
Author(s):  
Olena Iakunchykova ◽  
Maria Averina ◽  
Tom Wilsgaard ◽  
Sofia Malyutina ◽  
Alexander V Kudryavtsev ◽  
...  
Keyword(s):  
Risk Factors ◽  
Glycated Hemoglobin ◽  
Population Based ◽  
Marginal Structural Models ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
High Prevalence ◽  
The Difference ◽  
Design And Methods

IntroductionCompared with many other countries Russia has a high prevalence of diabetes in men and women. However, contrary to what is found in most other populations, the risk is greater among women than men. The reasons for this are unclear.Research design and methodsPrevalence and risk factors for diabetes at ages 40–69 years were compared in two population-based studies: Know Your Heart (KYH) (Russia, 2015–2018, n=4121) and the seventh wave of the Tromsø Study (Tromsø 7) (Norway, 2015–2016, n=17 649). Diabetes was defined by the level of glycated hemoglobin and/or self-reported diabetes and/or diabetes medication use. Marginal structural models were used to estimate the role of key risk factors for diabetes in differences between the studies.ResultsAge-standardized prevalence of diabetes was higher in KYH compared with Tromsø 7 in men (11.6% vs 6.2%) and in women (13.2% vs 4.3%). Age-adjusted ORs for diabetes in KYH compared with Tromsø 7 were 2.01 (95% CI 1.68 to 2.40) for men and 3.66 (95% CI 3.13 to 4.26) for women. Adiposity (body mass index and waist circumference) explained none of this effect for men but explained 46.0% (39.6, 53.8) for women. Addition of smoking and C reactive protein, as further mediators, slightly increased the percentage explained of the difference between studies to 55.5% (46.5, 66.0) for women but only to 9.9% (−0.6, 20.8) for men.ConclusionsAdiposity is a key modifiable risk factor that appears to explain half of the almost threefold higher female prevalence of diabetes in Russia compared with Norway, but none of the twofold male difference.

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