Association of temporomandibular disorder-related pain with severe headaches—a Bayesian view

Abstract Objectives Association of temporomandibular disorders (TMD)-related pain with severe headaches (migraine and tension-type headaches [TTH]) was studied over a follow-up period of 11 years. Materials and methods The data used was from two nationally representative health surveys in Finland—the Health 2000 Survey (baseline) and the Health 2011 Survey (follow-up) (Bioresource Research Impact Factor [BRIF] 8901)—conducted by the Finnish Institute for Health and Welfare (THL). The primary dataset of the current study included a subset of the population undergoing a clinical oral examination, including TMD examination, at baseline, and answering the questions related to severe headaches, both at baseline and at follow-up (n = 530). From the primary dataset, two datasets were created to study the onset of migraine (dataset 1) and TTH (dataset 2) separately. Dataset 1 included participants healthy of migraine, but not other headaches, at baseline (n = 345), and dataset 2 participants healthy of TTH and other headaches, except migraine, at baseline (n = 464). Bayesian logistic regression models with weakly informative priors were utilized to assess the association of muscle-related TMD pain (mTMD) at baseline and temporomandibular joint-related TMD pain (jTMD) at baseline with the presence of migraine and TTH at follow-up. Results Neither of the baseline TMD-related pain variables were associated with the presence of migraine at follow-up (posterior effect estimates-0.12, 95% credible interval [CI] -0.49–0.24, and 0.11, 95% CI -0.38–0.59, for mTMD and jTMD, respectively), whereas mTMD at baseline (posterior effect estimate 0.36, 95% CI 0.02–0.69), but not jTMD at baseline (posterior effect estimate -0.32, 95% CI -0.94–0.25), was associated with the presence of TTH at follow-up. Bayesian sensitivity analyses revealed that the estimates of the regression models were stable, demonstrating sufficient validity and consistency of the estimates. Conclusion These results indicate that diverse mechanisms may exist behind the associations of TMD-related painful conditions with different types of severe headaches. Clinical relevance TMD-related pain is a frequent comorbidity of severe primary headaches. Therapy of severe primary headaches may thus benefit significantly with the incorporation of a multi-disciplinary clinical team.

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Demographic factors associated with missed follow-up among solid tumor patients treated at a large multi-site academic institution

Future Oncology ◽

10.2217/fon-2020-0425 ◽

2020 ◽

Vol 16 (32) ◽

pp. 2635-2643

Author(s):

Samantha L Freije ◽

Jordan A Holmes ◽

Saleh Rachidi ◽

Susannah G Ellsworth ◽

Richard C Zellars ◽

...

Keyword(s):

Cancer Patients ◽

Odds Ratio ◽

Regression Models ◽

Tumor Patients ◽

Logistic Regression Models ◽

Factors Associated ◽

Follow Up Care ◽

Risk Patients ◽

African American Race

Aim: To identify demographic predictors of patients who miss oncology follow-up, considering that missed follow-up has not been well studies in cancer patients. Methods: Patients with solid tumors diagnosed from 2007 to 2016 were analyzed (n = 16,080). Univariate and multivariable logistic regression models were constructed to examine predictors of missed follow-up. Results: Our study revealed that 21.2% of patients missed ≥1 follow-up appointment. African–American race (odds ratio [OR] 1.33; 95% CI: 1.17–1.51), Medicaid insurance (OR 1.59; 1.36–1.87), no insurance (OR 1.66; 1.32–2.10) and rural residence (OR 1.78; 1.49–2.13) were associated with missed follow-up. Conclusion: Many cancer patients miss follow-up, and inadequate follow-up may influence cancer outcomes. Further research is needed on how to address disparities in follow-up care in high-risk patients.

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Low HbA1c levels and all-cause or cardiovascular mortality among people without diabetes: the US National Health and Nutrition Examination Survey 1999–2015

International Journal of Epidemiology ◽

10.1093/ije/dyaa263 ◽

2020 ◽

Author(s):

Kosuke Inoue ◽

Roch Nianogo ◽

Donatello Telesca ◽

Atsushi Goto ◽

Vahe Khachadourian ◽

...

Keyword(s):

Cardiovascular Mortality ◽

Regression Models ◽

Machine Learning Algorithms ◽

Logistic Regression Models ◽

Health And Nutrition ◽

Increased Risk ◽

The Us ◽

All Cause Mortality ◽

Hba1c Levels

Abstract Objective It is unclear whether relatively low glycated haemoglobin (HbA1c) levels are beneficial or harmful for the long-term health outcomes among people without diabetes. We aimed to investigate the association between low HbA1c levels and mortality among the US general population. Methods This study includes a nationally representative sample of 39 453 US adults from the National Health and Nutrition Examination Surveys 1999–2014, linked to mortality data through 2015. We employed the parametric g-formula with pooled logistic regression models and the ensemble machine learning algorithms to estimate the time-varying risk of all-cause and cardiovascular mortality by HbA1c categories (low, 4.0 to <5.0%; mid-level, 5.0 to <5.7%; prediabetes, 5.7 to <6.5%; and diabetes, ≥6.5% or taking antidiabetic medication), adjusting for 72 potential confounders including demographic characteristics, lifestyle, biomarkers, comorbidities and medications. Results Over a median follow-up of 7.5 years, 5118 (13%) all-cause deaths, and 1116 (3%) cardiovascular deaths were observed. Logistic regression models and machine learning algorithms showed nearly identical predictive performance of death and risk estimates. Compared with mid-level HbA1c, low HbA1c was associated with a 30% (95% CI, 16 to 48) and a 12% (95% CI, 3 to 22) increased risk of all-cause mortality at 5 years and 10 years of follow-up, respectively. We found no evidence that low HbA1c levels were associated with cardiovascular mortality risk. The diabetes group, but not the prediabetes group, also showed an increased risk of all-cause mortality. Conclusions Using the US national database and adjusting for an extensive set of potential confounders with flexible modelling, we found that adults with low HbA1c were at increased risk of all-cause mortality. Further evaluation and careful monitoring of low HbA1c levels need to be considered.

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Ethnic differences in the incidence of pterygium in a multi-ethnic Asian population: the Singapore Epidemiology of Eye Diseases Study

Scientific Reports ◽

10.1038/s41598-020-79920-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Xiao Ling Fang ◽

Crystal Chun Yuen Chong ◽

Sahil Thakur ◽

Zhi Da Soh ◽

Zhen Ling Teo ◽

...

Keyword(s):

Ethnic Differences ◽

Regression Models ◽

Multivariable Analysis ◽

Anterior Segment ◽

Asian Population ◽

Eye Diseases ◽

Logistic Regression Models ◽

Income Status ◽

Baseline Visit

AbstractWe evaluated the 6-year incidence and risk factors of pterygium in a multi-ethnic Asian population. Participants who attended the baseline visit of the Singapore Epidemiology of Eye Diseases Study (year 2004–2011) and returned six years later, were included in this study. Pterygium was diagnosed based on anterior segment photographs. Incident pterygium was defined as presence of pterygium at 6-year follow-up in either eye, among individuals without pterygium at baseline. Multivariable logistic regression models were used to determine factors associated with incident pterygium, adjusting for baseline age, gender, ethnicity, body mass index, occupation type, educational level, income status, smoking, alcohol consumption, presence of hypertension, diabetes and hyperlipidemia. The overall age-adjusted 6-year incidence of pterygium was 1.2% (95% confidence interval [CI] 1.0–1.6%); with Chinese (1.9%; 95% CI 1.4%-2.5%) having the highest incidence rate followed by Malays (1.4%; 95% CI 0.9%-2.1%) and Indians (0.3%; 95% CI 0.3–0.7%). In multivariable analysis, Chinese (compared with Indians; odds ratio [OR] = 4.21; 95% CI 2.12–9.35) and Malays (OR 3.22; 95% CI 1.52–7.45), male (OR 2.13; 95% CI 1.26–3.63), outdoor occupation (OR 2.33; 95% CI 1.16–4.38), and smoking (OR 0.41; 95% CI 0.16–0.87) were significantly associated with incident pterygium. Findings from this multi-ethnic Asian population provide useful information in identifying at-risk individuals for pterygium.

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The prospective relationship between social cohesion and depressive symptoms among older adults from Central and Eastern Europe

Journal of Epidemiology & Community Health ◽

10.1136/jech-2018-211063 ◽

2018 ◽

Vol 73 (2) ◽

pp. 117-122 ◽

Cited By ~ 5

Author(s):

Carla Bertossi Urzua ◽

Milagros A Ruiz ◽

Andrzej Pajak ◽

Magdalena Kozela ◽

Ruzena Kubinova ◽

...

Keyword(s):

Depressive Symptoms ◽

Eastern Europe ◽

Social Cohesion ◽

Regression Models ◽

Central And Eastern Europe ◽

The Czech Republic ◽

Logistic Regression Models ◽

Z Scores ◽

Prospective Association

BackgroundSocial cohesion has a potential protective effect against depression, but evidence for Central and Eastern Europe is lacking. We investigated the prospective association between social cohesion and elevated depressive symptoms in the Czech Republic, Russia and Poland, and assessed whether alcohol drinking and smoking mediated this association.MethodsCohort data from 15 438 older urban participants from the Health, Alcohol and Psychosocial factors In Eastern Europe project were analysed. Baseline social cohesion was measured by five questions, and depressive symptoms were measured 3 years later by the 10-item Center for Epidemiological Depression (CES-D) Scale. Nested logistic regression models estimated ORs of elevated depressive symptoms (CES-D 10 score ≥4) by z-scores and tertiles of social cohesion.ResultsPer 1 SD decrease in social cohesion score, adjusted ORs of elevated depressive symptoms were 1.13 (95% CI 1.05 to 1.23) and 1.05 (95% CI 0.99 to 1.13) in men and women, respectively. Further adjustment for smoking and drinking did not attenuate these associations in either men (OR=1.13, 95% CI 1.05 to 1.22) or women (OR=1.05, 95% CI 0.99 to 1.13). Similarly, the fully adjusted ORs comparing the lowest versus highest social cohesion tertile were 1.33 (95% CI 1.10 to 1.62) in men and 1.18 (95% CI 1.01 to 1.39) in women.ConclusionsLower levels of social cohesion was associated with heightened depressive symptoms after a 3-year follow-up among older Czech, Russian and Polish adults. These effects appeared stronger in men, and alcohol and smoking played no appreciable role in this association.

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Alcohol consumption and pregnancy in the Mexican national addiction survey

Cadernos de Saúde Pública ◽

10.1590/s0102-311x1997000200009 ◽

1997 ◽

Vol 13 (2) ◽

pp. 205-211 ◽

Cited By ~ 5

Author(s):

Guilherme Borges ◽

Roberto Tapia-Conyer ◽

Malaquías López-Cervantes ◽

María Elena Medina-Mora ◽

Blanca Pelcastre ◽

...

Keyword(s):

Alcohol Consumption ◽

Spontaneous Abortion ◽

Regression Models ◽

Congenital Abnormalities ◽

Adverse Outcomes ◽

Multiple Logistic Regression ◽

National Data ◽

Logistic Regression Models ◽

Important Relationship

In 1988, the General Directorate of Epidemiology and the Mexican Institute of Psychiatry conducted the first National Addiction Survey (ENA), providing regional and national data on alcohol, tobacco, and drug use. The ENA providing a subsample of women who have been pregnant at some time in their lives. There were 5,234 affirmative responses. Women were asked if they had suffered any of three adverse outcomes during their last pregnancy: spontaneous abortion, stillbirth, and congenital abnormalities. Prevalence of spontaneous abortion was 3.8%, stillbirth 1.2%, and congenital abnormalities 1.1 %. Multiple logistic-regression models were used to analyze the effect of alcohol consumption on these problems. Consumption during pregnancy was related only with the prevalence of congenital abnormalities, with prevalence odds of 3.4. Among habitual users during the last 12 months, oniy women in the highest use category showed an important relationship with the three problems mentioned. Follow-up studies on the Mexican population are recommended in order to obtain more conclusive findings.

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Coffee Consumption, Genetic Polymorphisms, and the Risk of Type 2 Diabetes Mellitus: A Pooled Analysis of Four Prospective Cohort Studies

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17155379 ◽

2020 ◽

Vol 17 (15) ◽

pp. 5379

Author(s):

An Na Kim ◽

Hyun Jeong Cho ◽

Jiyoung Youn ◽

Taiyue Jin ◽

Moonil Kang ◽

...

Keyword(s):

Type 2 Diabetes ◽

Regression Models ◽

Coffee Consumption ◽

Pooled Analysis ◽

Random Effects Model ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Logistic Regression Models

The association between coffee consumption and the risk of type 2 diabetes may vary by genetic variants. Our study addresses the question of whether the incidence of type 2 diabetes is related to the consumption of coffee and whether this relationship is modified by polymorphisms related to type 2 diabetes. We performed a pooled analysis of four Korean prospective studies that included 71,527 participants; median follow-up periods ranged between 2 and 13 years. All participants had completed a validated food-frequency questionnaire (FFQ) at baseline. The odds ratios (ORs) and 95% confidence intervals (CIs) for type 2 diabetes were calculated using logistic regression models. The ORs were combined using a fixed or random effects model depending on the heterogeneity across the studies. Compared with 0 to <0.5 cups/day of coffee consumption, the OR for type 2 diabetes was 0.89 (95% CI: 0.80–0.98, p for trend = 0.01) for ≥3 cups/day of coffee consumption. We did not observe significant interactions by five single nucleotide polymorphisms (SNPs) related to type 2 diabetes (CDKAL1 rs7756992, CDKN2A/B rs10811661, KCNJ11 rs5215, KCNQ1 rs163184, and PEPD rs3786897) in the association between coffee and the risk of type 2 diabetes. We found that coffee consumption was inversely associated with the risk of type 2 diabetes.

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Understanding the Association Between Spontaneous Quit Attempts and Improved Smoking Cessation Success Rates: A Population Survey in England With 6-Month Follow-up

Nicotine & Tobacco Research ◽

10.1093/ntr/ntz115 ◽

2019 ◽

Vol 22 (9) ◽

pp. 1460-1467 ◽

Cited By ~ 6

Author(s):

Claire Garnett ◽

Lion Shahab ◽

Tobias Raupach ◽

Robert West ◽

Jamie Brown

Keyword(s):

Regression Models ◽

Population Survey ◽

Adult Population ◽

Success Rates ◽

Logistic Regression Models ◽

The Past ◽

Quit Attempt ◽

Quit Attempts ◽

Adjusted Model

Abstract Introduction Almost half of smoking quit attempts are “spontaneous” (initiated as soon as the decision to quit has been made) and are associated with increased success rates. This study aimed to assess to what extent other factors may account for this association. Methods Data were used from respondents to a survey representative of the adult population in England from 2006 to 2016. We included 2018 respondents who were current smokers at baseline and had attempted to quit between baseline and 6-month follow-up. Logistic regression models assessed the association between quit success and spontaneous quit attempts while adjusting for smoking, sociodemographic, and quit attempt characteristics. Results Spontaneous quit attempts were associated with greater odds of quit success (OR = 1.31, 95% CI = 1.07 to 1.60) but the association was not significant in the fully adjusted model (ORadj = 1.19, 95% CI = 0.95 to 1.49). In this adjusted model, those who attempted to quit without cutting down first (ORadj = 3.08, 95% CI = 2.46 to 3.88) and were male (ORadj = 1.44, 95% CI = 1.16 to 1.80) had greater odds of success; although a greater number of attempts in the past 6 months, stronger urges to smoke (strong vs. none), higher daily cigarette consumption, and lower social grade (E vs. AB) were associated with lower odds of success (ORadj range = 0.32–0.98, p < .030). Quit attempts made without cutting down first were correlated with spontaneous quit attempts (r = .150, p < .001) and appeared to account for the diminished association between spontaneous quitting and success (ORadj = 1.18, 95% CI = 0.96 to 1.46). Conclusions The increased success rate of spontaneous quit attempts appears to be because spontaneous quit attempts are more likely to be made without cutting down first. Implications The apparent benefit of spontaneous over planned quit attempts may be attributable to the former being more likely to involve quitting without cutting down first (ie, abrupt cessation) than cutting down first (ie, gradual cessation) and so this may be a more useful target for advice to improve the chances of successful quitting.

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Does Flipping the Tubercle for Improved Cartilage Repair Exposure Increase the Risk for Arthrofibrosis?

Cartilage ◽

10.1177/1947603520968209 ◽

2020 ◽

pp. 194760352096820

Author(s):

Gergo Merkely ◽

Jakob Ackermann ◽

Emily Sheehy ◽

Andreas H. Gomoll

Keyword(s):

Logistic Regression ◽

Cartilage Repair ◽

Regression Models ◽

Case Control Study ◽

Level Of Evidence ◽

Logistic Regression Models ◽

Increased Risk ◽

Repair Procedure ◽

Control Study

Objective We sought to determine whether rates of postoperative arthrofibrosis following tibial tuberosity osteotomy (TTO) with complete mobilization of the fragment (TTO-HD) are comparable to TTOs where the hinge remained intact (TTO-HI). Design Patients who underwent TTO with concomitant cartilage repair procedure between January 2007 and May 2017, with at least 2 years of follow-up were included in this study. Postoperative reinterventions following TTO-HD and TTO-HI were assessed and multivariant logistic regression models were used to identify whether postoperative reinterventions can be attributed to either technique when controlled for defect size or defect number. Results A total of 127 patients (TTO-HD, n = 80; TTO-HI, n = 47) were included in this study. Significantly more patients in the TTO-HD group (31.2%) developed postoperative arthrofibrosis compared with TTO-HI (6.4%; P < 0.05). Multivariant logistic regression revealed that TTO-HD is an independent risk factor for predicting postoperative arthrofibrosis (OR 6.5, CI = 1.7-24.2, P < 0.05). Conclusion Patients who underwent TTO with distal hinge detachment and a proximally flipped tubercle for better exposure during concomitant cartilage repair were at a significantly higher risk of postoperative arthrofibrosis than patients with similar size and number of defects treated without mobilization of the tubercle. While certain procedures can benefit from larger exposure, surgeons should be aware of the increased risk of postoperative arthrofibrosis. Level of Evidence Level III, case-control study.

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Low blood pressure and risk of depression in the elderly

The British Journal of Psychiatry ◽

10.1192/bjp.176.5.464 ◽

2000 ◽

Vol 176 (5) ◽

pp. 464-467 ◽

Cited By ~ 63

Author(s):

Sabrina Paterniti ◽

Marie-Hélène Verdier-Taillefer ◽

Catherine Geneste ◽

Jean-Claude Bisserbe ◽

Annick Alpérovitch

Keyword(s):

Blood Pressure ◽

Regression Models ◽

Depressive Symptomatology ◽

The Elderly ◽

Epidemiological Studies ◽

Logistic Regression Models ◽

Drinking Habits ◽

Low Blood Pressure ◽

The Relationship

BackgroundThe relationship between depression and low blood pressure is unclear.AimsTo examine the temporal relation between low blood pressure and depression in a two-year follow-up.MethodThe study group consisted of 1389 subjects aged 59–71 years; 1272 (92%) were examined after two years. Subjects completed the Center for Epidemiological Studies–Depression (CES–D) and the Spielberger inventory scales to assess depressive and anxiety symptoms respectively. Data were collected on socio-demographic characteristics, smoking and drinking habits, medical history, drug use and blood pressure measures.ResultsAmong 1112 subjects who were considered as non-depressed at baseline, logistic regression models showed that low diastolic blood pressure (DBP) and decrease of blood pressure were predictors of high depressive symptomatology at follow-up. Baseline high CES–D scores did not predict low blood pressure two years after.ConclusionsIn our study, low blood pressure was a risk factor for, but not a consequence of, high depressive symptomatology.

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Urine proteomics identifies biomarkers for diabetic kidney disease at different stages

Clinical Proteomics ◽

10.1186/s12014-021-09338-6 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Guanjie Fan ◽

Tongqing Gong ◽

Yuping Lin ◽

Jianping Wang ◽

Lu Sun ◽

...

Keyword(s):

Logistic Regression ◽

Kidney Disease ◽

Regression Models ◽

Diabetic Kidney Disease ◽

Kidney Biopsy ◽

Invasive Procedure ◽

Urinary Proteins ◽

Diabetic Kidney ◽

Logistic Regression Models

Abstract Background Type 2 diabetic kidney disease is the most common cause of chronic kidney diseases (CKD) and end-stage renal diseases (ESRD). Although kidney biopsy is considered as the ‘gold standard’ for diabetic kidney disease (DKD) diagnosis, it is an invasive procedure, and the diagnosis can be influenced by sampling bias and personal judgement. It is desirable to establish a non-invasive procedure that can complement kidney biopsy in diagnosis and tracking the DKD progress. Methods In this cross-sectional study, we collected 252 urine samples, including 134 uncomplicated diabetes, 65 DKD, 40 CKD without diabetes and 13 follow-up diabetic samples, and analyzed the urine proteomes with liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS). We built logistic regression models to distinguish uncomplicated diabetes, DKD and other CKDs. Results We quantified 559 ± 202 gene products (GPs) (Mean ± SD) on a single sample and 2946 GPs in total. Based on logistic regression models, DKD patients could be differentiated from the uncomplicated diabetic patients with 2 urinary proteins (AUC = 0.928), and the stage 3 (DKD3) and stage 4 (DKD4) DKD patients with 3 urinary proteins (AUC = 0.949). These results were validated in an independent dataset. Finally, a 4-protein classifier identified putative pre-DKD3 patients, who showed DKD3 proteomic features but were not diagnosed by clinical standards. Follow-up studies on 11 patients indicated that 2 putative pre-DKD patients have progressed to DKD3. Conclusions Our study demonstrated the potential for urinary proteomics as a noninvasive method for DKD diagnosis and identifying high-risk patients for progression monitoring.

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