Comorbidities and crash involvement among younger and older drivers

Previous studies identified comorbidities as predictors of older driver performance and driving pattern, while the direct impact of comorbidities on road crash risk in elderly drivers is still unknown. The present study is a cross-sectional aimed at investigating the association between levels of comorbidity and crash involvement in adult and elderly drivers. 327 drivers were stratified according to age range in two groups: elderly drivers (age >= 70 years old, referred as older) and adult drivers (age <70 years old, referred as younger). Driving information was obtained through a driving questionnaire. Distance traveled was categorized into low, medium and high on the basis of kilometers driven in a year. CIRS-illness severity (IS) and CIRS-comorbidity indices (CI) in all populations were calculated. Older drivers had a significantly higher crash involvements rate (p = .045) compared with the younger group based on the number of licensed drivers. Dividing comorbidity indices into tertiles among all licensed subjects, the number of current drivers significantly decreased (p < .0001) with increasing level of comorbidity. The number of current drivers among older subjects significantly decreased with increasing comorbidity level (p = .026) while no difference among younger group was found (p = .462). Among younger drivers with increasing comorbidity level, the number of road accidents significantly increased (p = .048) and the logistic regression analysis showed that comorbidity level significantly associated with crash involvement independent of gender and driving exposure. Older subjects with high level of comorbidity are able to self-regulate driving while comorbidity burden represents a significant risk factor for crash involvements among younger drivers

Combining Wireless Technology and Behavioral Economics to Engage Patients (WiBEEP) with cardiometabolic disease: a pilot study

Abstract Background The long-term management of cardiometabolic diseases, such as type 2 diabetes and hypertension, is complex and can be facilitated by supporting patient-directed behavioral changes. The concurrent application of wireless technology and personalized text messages (PTMs) based on behavioral economics in managing cardiometabolic diseases, although promising, has not been studied. The aim of this pilot study was to evaluate the feasibility and acceptability of the concurrent application of wireless home blood pressure (BP) monitoring (as an example of “automated hovering”) and PTMs (as an example of “nudging”) targeting pharmacotherapy and lifestyle habits in patients with cardiometabolic disease (type 2 diabetes and/or hypertension). Methods The Wireless Technology and Behavioral Economics to Engage Patients (WiBEEP) with cardiometabolic disease study was a single-arm, open-label, 7-week-long pilot study in 12 patients (mean age 58.5 years) with access to a mobile phone. The study took place at Tufts Medical Center (Boston, MA) between March and September 2017. All patients received PTMs; nine patients received wireless home BP monitoring. At baseline, patients completed questionnaires to learn about their health goals and to assess medication adherence; at the end of week 7, all patients completed questionnaires to evaluate the feasibility and acceptability of the intervention and assess medication adherence. Hemoglobin A1c was ascertained from data collected during routine clinical care in 7 patients with available data. Results The majority of patients reported the text messages to be easy to understand (88%) and appropriate in frequency (71%) and language (88%). All patients reported BP monitoring to be useful. Mean arterial pressure was lower at the end-of-study compared to baseline (− 3.4 mmHg [95% CI, − 5 to − 1.8]. Mean change in hemoglobin A1c was − 0.31% [95% CI, − 0.56 to − 0.06]. Conclusions Among patients with cardiometabolic disease, the combination of wireless BP monitoring and lifestyle-focused text messaging was feasible and acceptable. Larger studies will determine the long-term effectiveness of such an approach

Association of genetic variation in adaptor protein APPL1/APPL2 loci with non-alcoholic fatty liver disease.

The importance of genetics and epigenetic changes in the pathogenesis of non alcoholic fatty liver disease (NAFLD) has been increasingly recognized. Adiponectin has a central role in regulating glucose and lipid metabolism and controlling inflammation in insulin-sensitive tissues and low adiponectin levels have been linked to NAFLD. APPL1 and APPL2 are adaptor proteins that interact with the intracellular region of adiponectin receptors and mediate adiponectin signaling and its effects on metabolism. The aim of our study was the evaluation of a potential association between variants at APPL1 and APPL2 loci and NAFLD occurrence. The impact on liver damage and hepatic steatosis severity has been also evaluated. To this aim allele frequency and genotype distribution of APPL1- rs3806622 and -rs4640525 and APPL2-rs 11112412 variants were evaluated in 223 subjects with clinical diagnosis of NAFLD and compared with 231 healthy subjects. The impact of APPL1 and APPL2 SNPs on liver damage and hepatic steatosis severity has been also evaluated. The minor-allele combination APPL1-C/APPL2-A was associated with an increased risk of NAFLD (OR = 2.50 95% CI 1.45-4.32; p<0.001) even after adjustment for age, sex, body mass index, insulin resistance (HOMA-IR), triglycerides and adiponectin levels. This allele combination carrier had higher plasma alanine aminotransferase levels (Diff = 15.08 [7.60-22.57] p = 0.001) and an increased frequency of severe steatosis compared to the reference allele combination (OR = 3.88; 95% CI 1.582-9.531; p<0.001). In conclusion, C-APPL1/A-APPL2 allele combination is associated with NAFLD occurrence, with a more severe hepatic steatosis grade and with a reduced adiponectin cytoprotective effect on liver

Hepatic steatosis severity among APPL1 and APPL2 genotype groups.

<p>Hepatic steatosis severity among APPL1 and APPL2 genotype groups.</p

Levels of alanine transaminase (ALT) and aspartate transaminase (AST) among different APPL1 and APPL2 genotypes.

*<p>p<0.05 vs GG genotype; § p<0.05 vs No carrier.</p

Allele combination effect on plasma ALT levels and hepatic steatosis severity.

*<p>Phenotypic Mean = 55.39; Standard Error = 36.46; Residual Standard Error = 35.74.</p

Allele combination effect on NAFLD risk.

*<p>adjusted for age, BMI, IR HOMA index, plasma adiponectin and triglycerides levels.</p

Genotype and allele frequencies distribution of rs4640525- APPL1 and rs11112412-APPL2 in NAFLD patients and control.

<p>Data are presented as % (n);</p>*<p>adjusted for age, BMI, IR HOMA index, plasma adiponectin and triglycerides levels.</p

Clinical characteristics of NAFLD patients and control subjects.

<p>Clinical characteristics of NAFLD patients and control subjects.</p