Investigating food insecurity, health lifestyles, and self-rated health of older Canadians living alone.

BACKGROUND AND OBJECTIVES: There is a large number of older of this demographic fact. Although many studies have investigated the association between living arrangements and health, little is known about potential underlying mechanisms regarding how living alone may predict older Canadians' health. In this study, we address this research gap intending to contribute to offering policy suggestions for older Canadians who live alone. RESEARCH DESIGN AND METHODS: We applied Cockerham's health lifestyle theory to explore to what degree living alone predicts worse health lifestyles and, further, to what degree these lifestyles can explain the association between living alone and older Canadians' health. We used the 2017-2018 Canadian Community Social Survey (Annual Component) which has a response rate of 58.8%. We focused on respondents aged 60 and above, and the analytical sample size is 39,636. RESULTS: Older Canadians living alone are more likely to have food insecurity problems and higher possibilities of smoking cigarettes compared to those living with spouses/partners with or without children. Compared to those living with spouses/partners only, the odds of solo-living older Canadians drinking regularly is significantly lower. There also exists a significant difference between older Canadians living alone and their counterparts living with spouses/partners that the former reported lower self-rated health compared to the latter. Moreover, food insecurity and the three health lifestyle variables are significantly associated with respondents' self-rated health; food insecurity, cigarette smoking, and alcohol drinking can partially explain the difference in self-rated health due to living arrangements. DISCUSSION AND IMPLICATIONS: According to our findings, health officials are recommended to pay more attention to food insecurity and heavy smoking problems facing older Canadians who live by themselves. Local communities and other stakeholders are suggested to provide older adults living alone with more opportunities for social engagement and involvement since regular drinking may have played such a role in enhancing social life quality of the aged.

Transformation of Sequential Hospital and Outpatient Laboratory Data into Between-Day Reference Change Values.

BACKGROUND: Serial differences between intrapatient consecutive measurements can be transformed into Taylor series of variation vs time with the intersection at time = 0 (y0) equal to the total variation (analytical + biological + preanalytical). With small preanalytical variation, y0, expressed as a percentage of the mean, is equal to the variable component of the reference change value (RCV) calculation: (CVA2 + CVI2)1/2. METHODS: We determined the between-day RCV of patient data for 17 analytes and compared them to healthy participants' RCVs. We analyzed 653 consecutive days of Dartmouth-Hitchcock Roche Modular general chemistry data (4.2 million results: 60% inpatient, 40% outpatient). The serial patient values of 17 analytes were transformed into 95% 2-sided RCV (RCVAlternate), and 3 sets of RCVhealthy were calculated from 3 Roche Modular analyzers' quality control summaries and CVI derived from biological variation (BV) studies using healthy participants. RESULTS: The RCVAlternate values are similar to RCVhealthy derived from known components of variation. For sodium, chloride, bicarbonate calcium, magnesium, phosphate, alanine aminotransferase, albumin, and total protein, the RCVs are equivalent. As expected, increased variation was found for glucose, aspartate aminotransferase, creatinine, and potassium. Direct bilirubin and urea demonstrated lower variation. CONCLUSIONS: Our RCVAlternate values integrate known and unknown components of analytic, biologic, and preanalytic variation, and depict the variations observed by clinical teams that make medical decisions based on the test values. The RCVAlternate values are similar to the RCVhealthy values derived from known components of variation and suggest further studies to better understand the results being generated on actual patients tested in typical laboratory environments.

Remote ischaemic conditioning in ST elevation myocardial infarction: a registry-based randomised trial.

OBJECTIVES: Remote ischaemic conditioning (RIC) has been tested as a possible strategy for mitigating reperfusion injury in ST elevation myocardial infarction (STEMI) with primary percutaneous coronary intervention (PPCI). However, surrogate outcomes have shown inconsistent effects with lack of clinical correlation. METHODS: We performed a registry-based randomised study of patients with STEMI allocated to RIC (4 cycles of blood pressure cuff inflation to 200 mm Hg for 5 min of ischaemia followed by 5 min of reperfusion) or standard of care (SOC) during PPCI. We examined the associations of RIC on core laboratory measurements of myocardial perfusion, infarct size (IS), left ventricular (LV) performance and clinical outcomes. RESULTS: A total of 252 patients were enrolled. The median age was 61 (IQR: 55-70) years and 72.8% were male. Sum ST segment deviation resolution ≥50% was similar between RIC and SOC (65.2% vs 55.7%, p=0.269). In those with 3-day cardiovascular MRI (n=88), no difference in median (25th, 75th percentiles) IS (14.9% (4.5%, 23.1%) vs 16.1% (3.3%, 22.0%), p=0.980), LV dimensions (LV end-diastolic volume index: 78.7 (71.1, 91.2) mL/m2 vs 79.9 (71.2, 88.8) mL/m2, p=0.630; LV end-systolic volume index: 48.8 (35.7, 51.4) mL/m2 vs 37.9 (31.8, 47.5) mL/m2, p=0.551) or ejection fraction (50.0% (41.0%-55.0%) vs 50.0% (43.0%-56.0%), p=0.554) was demonstrated. Similar results were observed with 90-day cardiovascular MRI. At 1 year, the clinical composite of death, congestive heart failure, cardiogenic shock and recurrent myocardial infarction was similar in RIC and SOC (21.7% vs 13.3%, p=0.110). CONCLUSIONS: In a contemporary registry-based randomised study of patients with STEMI undergoing PPCI, adjunctive therapy with RIC did not improve myocardial perfusion, reduce IS or alter LV performance. Consequently, there was no difference in clinical outcomes within 1 year. TRIAL REGISTRATION NUMBER: NCT03930589.

Intellectual Structure of Coronavirus Research: A Perspective From an Author Cocitation Analysis.

The present study examines the intellectual structure of research on coronavirus, as revealed from an author co-citation analysis using citation data retrieved from the Web of Science Core Collection and mapped to the PubMed database. Four major dimensions are identified: I) outbreaks, II) viral structure and function, III) vaccine and therapeutic development, and IV) coronaviruses found in a range of animals. The "outbreaks" dimension is by far the most prominent, dominated by reports on the three recent major outbreaks: COVID-19, severe acute respiratory syndrome, and Middle East respiratory syndrome. The focus of research on major outbreaks is on public health and clinical research, with focus on disease characterization, diagnosis, transmission, and clinical course. Notably, certain clinically important areas, such as mental health during outbreaks and viral surveillance, among others, did not stand out as identifiable specialties or topics in the coronavirus research landscape. Results from this study should contribute to the understanding of the coronavirus research landscape and to the identification of strengths and weaknesses of current research on COVID-19.

Five-Year Two-Center Retrospective Comparison of Central Laboratory Glucose to GEM 4000 and ABL 800 Blood Glucose: Demonstrating the (In)adequacy of Blood Gas Glucose.

PURPOSE: To evaluate the glucose assays of two blood gas analyzers (BGAs) in intensive care unit (ICU) patients by comparing ICU BGA glucoses to central laboratory (CL) glucoses of almost simultaneously drawn specimens. METHODS: Data repositories provided five years of ICU BGA glucoses and contemporaneously drawn CL glucoses from a Calgary, Alberta ICU equipped with IL GEM 4000 and CL Roche Cobas 8000-C702, and an Edmonton, Alberta ICU equipped with Radiometer ABL 800 and CL Beckman-Coulter DxC. Blood glucose analyzer and CL glucose differences were evaluated if they were both drawn either within ±15 or ±5 minutes. Glucose differences were assessed graphically and quantitatively with simple run charts and the surveillance error grid (SEG) and quantitatively with the 2016 Food and Drug Administration guidance document, with ISO 15197 and SEG statistical summaries. As the GEM glucose exhibits diurnal variation, CL-arterial blood gas (ABG) differences were evaluated according to time of day. RESULTS: Compared to the GEM glucoses measured between 0200 and 0800, the run charts of (GEM-CL) glucose demonstrate significant outliers between 0800 and 0200 which are identified as moderate to severe clinical outliers by SEG analysis (P < .002 and P < .0005 for 5- and 15-minute intervals). Over the entire 24-hour period, the rates of moderate to severe glucose clinical outliers are 3.5/1000 (GEM) and 0.6/1000 glucoses (ABL), respectively, using the 15-minute interval (P < .0001). DISCUSSION: The GEM ABG glucose is associated with a higher frequency of moderate to severe glucose clinical outliers, especially between 0800 and 0200, increased CL testing and higher average patient glucoses.

Impaired clinical utility of sequential patient GEM blood gas measurements associated with calibration schedule.

BACKGROUND: Within- and/or between-instrument variation may falsely indicate patient trends or obscure real trends. We employ a methodology that transforms sequential intra-patient results into estimates of biologic and analytic variation. We previously derived realistic biologic variation (sb) of blood gas (BG) and hematology analytes. We extend this methodology to derive the imprecision of two GEM 4000 BG analyzers. METHODS: A laboratory data repository provided arterial BG, electrolyte and metabolite results generated by two GEM 4000s on ICU patients in 2012-2013. We tabulated consecutive pairs of intra-patient results separated by increasing time interval between consecutive tests. The average between pair variations were regressed against time with the y-intercept representing the sum of the biologic variation and short term analytic variation: yo2=sb2+sa2. Using an equivalent equation for the Radiometer ABL, the imprecision of the two GEMs was calculated: saGEM=(yoGEM2-yoABL2+saABL2)1/2. This analysis was performed for nearly all measurements, regardless of time as well for values obtained over two 12h mutually exclusive periods, starting either at 2am or 2pm. RESULTS: Regression graphs were derived from 1800 patients' blood gas results with least 10,000 data pairs grouped into 2h intervals. The calculated saGEM exceed the directly measured saABL with many GEM sigma ratios of biologic variation/analytic variation being close to unity. All of the afternoon saGEM exceeded their morning counterparts with pH, pCO2, K and bicarbonate being statistically significant. CONCLUSION: For many analytes, the average analytical variation of tandem GEMs approximates the biologic variation, indicating impaired clinical usefulness of tandem sequential measurements. A significant component of this variation is due to increased variation of the GEMs between 2pm and 2am.