Fatigue analysis of restored teeth longitudinally cracked under cyclic loading

ObjectiveTo investigate the fatigue behavior of restored teeth, in particular the mechanisms of longitudinal dentinal cracking under cyclic mechanical loading, using finite element analysis (FEA) and the stress-life (S-N) approach.MethodsTen root-filled premolars restored with resin composites were subjected to step-stress cyclic loading to produce longitudinal cracks. Fracture loads and number of cycles completed at each load level were recorded. FEA was used to predict the stress amplitude of each component under the global cyclic load. Both intact and debonded conditions were considered for the dentin-composite interface in the FEA. The predicted stress concentrations were compared with the fracture patterns to help elucidate the failure mechanisms. The S-N approach was further used to predict the lifetimes of the different components in the restored teeth. Cumulative fatigue damage was represented by the sum of the fractions of life spent under the different stress amplitudes.ResultsLongitudinal cracks were seen in ~50% of the samples with a mean fracture load of 770 ± 45 N and a mean number of cycles to failure of 32,297 ± 12,624. The longitudinal dentinal cracks seemed to start near the line angle of the cavity, and propagated longitudinally towards the root. The sum of fractions of life spent for the dentin-composite interface exceeded 1 after ~7000 cycles when that for dentin was much lower than 1, indicating that interfacial debonding would occur prior to dentin fracture. This was supported by micro-CT images showing widened interfacial space in the cracked samples. In the debonded tooth, FEA showed dentinal stress concentrations at the gingival wall of the cavity, which coincided with the longitudinal cracks found in the cyclic loading test. The sum of fractions of life spent for dentin was close to 1 at ~30,000 cycles, similar to the experimental value.SignificanceDebonding of the dentin-composite interface may occur prior to longitudinal cracking of dentin in root-filled teeth under cyclic loading. The approximate time of occurrence for these events could be estimated using fatigue analysis with stresses provided by FEA. This methodology can therefore be used to evaluate the longevity of restoration designs for root-filled teeth.     

Intervention rates and outcomes in medically managed uncomplicated descending thoracic aortic dissections

ObjectiveTo evaluate the long-term incidence and outcome of aortic interventions for medically managed uncomplicated thoracic aortic dissections.MethodsBetween January 2012 and December 2018, 91 patients were discharged home with an uncomplicated, medically treated aortic dissection (involving the descending aorta with or without aortic arch involvement, no ascending involvement). After a median period of 4 (first quartile: 2, third quartile: 11) months, 30 patients (33%) required an aortic intervention. Patient characteristics, radiographic, treatment, and follow-up data were compared for patients with and without aortic interventions. A competing risk regression model was analyzed to identify independent predictors of aortic intervention and to predict the risk for intervention.ResultsPatients who underwent aortic interventions had significantly larger thoracic (P = .041) and abdominal (P = .015) aortic diameters, the dissection was significantly longer (P = .035), there were more communications between both lumina (P = .040), and the first communication was significantly closer to the left subclavian artery (P = .049). A descending thoracic aortic diameter exceeding 45 mm was predictive for an aortic intervention (P = .001; subdistribution hazard ratio: 3.51). The risk for aortic intervention was 27% ± 10% and 36% ± 11% after 1 and 3 years, respectively. Fourteen patients (47%) underwent thoracic endovascular aortic repair, 11 patients (37%) thoracic endovascular aortic repair and left carotid to subclavian bypass, 3 patients (10%) total arch replacement with the frozen elephant trunk technique, and 2 patients (7%) thoracoabdominal aortic replacement. We observed no in-hospital mortality.ConclusionsThe need for secondary aortic interventions in patients with initially medically managed, uncomplicated descending aortic dissections is substantial. The full spectrum of aortic treatment options (endovascular, hybrid, conventional open surgical) is required in these patients.     

Trends of self-reported non-adherence among type 2 diabetes medication users in the United States across three years using the self-reported Medication Adherence Reasons Scale

Background & aimsTo determine the trends of self-reported non-adherence rates among adults taking Type 2 medicines (T2D) medicines between 2017 and 2019 and to identify the patterns for the frequently reported reasons for non-adherence in the United States.Methods & resultsData from the National Health and Wellness Survey, a self-administered, internet-based cross-sectional survey of US adults from 2017 to 2019 was used. Non-adherence was measured using the self-reported Medication Adherence Reasons Scale (MAR-Scale). Frequencies were used to identify the reasons for non-adherence for insulin and non-insulin therapies for T2D.Data were obtained from 2983 respondents in 2017, 5416 in 2018, and 5268 in 2019. Based on the MAR-Scale, the self-reported medication non-adherence rate was 25% in 2017, 21% in 2018, and 27% in 2019. The most common reason for non-adherence across all the three years was simple forgetfulness, yet patients reported the lowest mean number of days missing medication for that reason. Though less frequently reported, non-adherence lasted longer when patient did not know how to take their medicines, cost was a reason, or had concerns about the long term effects of the medicines.ConclusionsWith no significant improvement in adherence with T2D medicines over time, regardless of better awareness and extensive diabetes education, focus should be on individualized non-adherence reasons-based interventions.     

护士"互联网+护理服务"参与行为意愿量表的编制及信效度检验

目的编制护士"互联网+护理服务"参与行为意愿量表,并进行信效度检验。方法以计划行为理论为框架,采用文献回顾、半结构式访谈法形成量表的条目池;通过专家咨询、项目分析对量表条目进行筛选,初步形成护士"互联网+护理服务"参与行为意愿量表。采用方便抽样法,于2020年10—12月选取江苏省6所医院(2所三级医院、2所二级医院、2所一级医院)的825名护士进行正式调查,检验问卷的信效度。结果护士"互联网+护理服务"参与行为意愿量表包括3个分量表(参与行为态度、主观行为规范、感知行为控制)、8个维度、17个条目。总量表的Cronbach'sα系数为0.927、重测信度系数为0.805。护士"互联网+护理服务"参与行为意愿与参与行为的相关系数为0.743(P<0.01)。因子分析提取出8个公因子,累积方差贡献率为72.33%。结论护士"互联网+护理服务"参与行为意愿量表具有较好的信效度,可用于护士"互联网+护理服务"参与行为意愿的评估。     

Do social support and community engagement act as mechanisms in the association between neighbourhood income inequality and the mental health of mothers in Calgary,Canada? A mediation analysis

PurposeAccording to the social determinants of health framework, income inequality is a potential risk factor for adverse mental health. However, few studies have explored the mechanisms suspected to mediate this relationship. The current study addresses this gap through a mediation analysis to determine if social support and community engagement act as mediators linking neighbourhood income inequality to maternal anxiety and depressive symptoms within a cohort of new mothers living in the City of Calgary, Canada.MethodsData collected at three years postpartum from mothers belonging to the All Our Families (AOF) cohort were used in the current study. Maternal data were collected between 2012 and 2015 and linked to neighbourhood socioeconomic data from the 2006 Canadian Census. Income inequality was measured using Gini coefficients derived from 2006 after-tax census data. Generalized structural equation models were used to quantify the associations between income inequality and mental health symptoms, and to assess the potential direct and indirect mediating effects of maternal social support and community engagement.ResultsIncome inequality was not significantly associated with higher depressive symptoms (β = 0.32, 95%CI = −0.067, 0.70), anxiety symptoms (β = 0.11, 95%CI = −0.39, 0.60), or lower social support. Income inequality was not associated with community engagement. For the depression models, higher social support was significantly associated with lower depressive symptoms (β = −0.13, 95%CI = −0.15, −0.097), while community engagement was not significantly associated with depressive symptoms (β = 0.059, 95%CI = −0.15, 0.27). Similarly, for the anxiety models, lower anxiety symptoms were significantly associated with higher levels of social support (β = −0.17, 95%CI = −0.20, −0.13) but not with higher levels of community engagement (β = 0.14, 95%CI = −0.14, 0.41).ConclusionThe current study did not find clear evidence for social support or community engagement mediating the relationship between neighbourhood income inequality and maternal mental health. Future investigations should employ a broader longitudinal approach to capture changes in income inequality, potential mediators, and mental health symptomatology over time.     

Clinical implications of additional posterior fractures in combined anterior-posterior pelvic ring fractures in elderly patients

ObjectivesHistorically, pelvic ring fractures (PRF) are considered to occur predominantly in the anterior ring and therfore to be mechanically stable. Combined anterior and posterior (A + P) PRF are expected to be less mechanically stable and therefore to be associated with higher levels of pain and reduced mobility compared to isolated anterior fractures. The current study investigates the clinical relevance of combined A + P PRF in elderly patients.MethodsA prospective multicentre cohort study was conducted in patients >70 years of age with anterior PRF after low-energy trauma diagnosed on conventional radiographs. All patients underwent an additional CT-scan. Patients were divided into two groups; isolated anterior or combined A + P fractures. Patients were treated conservatively with adequate analgesia for at least one week. If patients could not be mobilised after conservative treatment, surgical fixation was performed. Numerical Rating Scale (NRS) pain scores, dependence on walking aids and Activities of Daily Living scores (ADL) were measured at 2–4 weeks, and 3, 6 and 12 months after fracture.Results102 patients (age 81.1 ± 7.6 years) were included. Isolated anterior fractures were diagnosed in 25 (24.5%) and A + P fractures in 77 (75.5%) patients. Baseline characteristics did not differ between the two groups. Most patients were successfully treated conservatively and 5 (4.9%) underwent percutaneous trans-iliac, trans-sacral screw fixation after failure of conservative treatment. At 2–4 weeks post trauma, patients with A + P fractures had similar median pain scores (3 (range 0–8) vs. 5 (0–10), p = 0.19) and ADL scores (85 (25–100) vs. 78.6 (5–100), p = 0.67), but were more dependent on walking aids (92.8% vs. 72.2%; p = 0.02) compared to patients with isolated anterior fractures. There were no significant differences at 3 months. At one year follow-up the median NRS pain and ADL scores for both fracture groups were 0 and 100, respectively. Mortality was 10.8%, and additional loss to follow-up was 17.6%.ConclusionsThe vast majority of elderly patients with PRF have combined A + P fractures. The clinical implications of additional posterior pelvic ring fractures in elderly patients appears to be limited.     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.