Building an allostatic load index from data of occupational medical checkup examinations: a feasibility study.

The allostatic load index (ALI) assesses the physiological adaption to chronic stress by cumulative changes in the circulation, respiration, inflammation, metabolic and anthropometric systems. The ALI thus can function as a risk marker for secondary prevention in occupational medicine. The aim of this study was to investigate the feasibility of creating a predictive marker by using data from an executive checkup program of an international company and to examine its relationship to work-related surrogate health parameters. Datasets from 307 examinations of 151 executives (19 males and 132 females) were available. Each participant attended at least one checkup examination between 2003 and 2015. The mean age was 43.6 (SD ±6.6, 31-64y). We developed four different ALIs with different biomarkers of the cardio-vascular, immune, metabolic and anthropometric systems. As a primary mediator, the thyroid-stimulating hormone was used as a proxy. For each ALI, the associations with the work ability index (WAI) and categories of sick leave days (SLD) were examined. Zero inflation was considered for SLD. One ALI showed a significant negative association with the WAI (B = -0.680, SE =0.266, p = .049). The results of a second ALI had a similar trend (B= -0.355, SE =0.201, p = .081). After adjustment for zero inflation two other ALIs showed a positive association with SLD. This study provides the first hints that biomarkers form a secondary prevention program are useful in calculating a meaningful ALI. Thus, the concept of allostatic load could be used in workplace health-promotion.

A dried blood spot protocol for high throughput analysis of SARS-CoV-2 serology based on the Roche Elecsys anti-N assay.

BACKGROUND: Since 2020 SARS-CoV-2 spreads pandemically, infecting more than 119 million people, causing >2·6 million fatalities. Symptoms of SARS-CoV-2 infection vary greatly, ranging from asymptomatic to fatal. Different populations react differently to the disease, making it very hard to track the spread of the infection in a population. Measuring specific anti-SARS-CoV-2 antibodies is an important tool to assess the spread of the infection or successful vaccinations. To achieve sufficient sample numbers, alternatives to venous blood sampling are needed not requiring medical personnel or cold-chains. Dried-blood-spots (DBS) on filter-cards have been used for different studies, but not routinely for serology. METHODS: We developed a semi-automated protocol using self-sampled DBS for SARS-CoV-2 serology. It was validated in a cohort of matched DBS and venous-blood samples (n = 1710). Feasibility is demonstrated with two large serosurveys with 10247 company employees and a population cohort of 4465 participants. FINDINGS: Sensitivity and specificity reached 99·20% and 98·65%, respectively. Providing written instructions and video tutorials, 99·87% (4465/4471) of the unsupervised home sampling DBS cards could be analysed. INTERPRETATION: DBS-sampling is a valid and highly reliable tool for large scale serosurveys. We demonstrate feasibility and accuracy with a large validation cohort including unsupervised home sampling. This protocol might be of big importance for surveillance in resource-limited settings, providing low-cost highly accurate serology data. FUNDING: Provided by Bavarian State Ministry of Science and the Arts, LMU University-Hospital; Helmholtz-Centre-Munich, German Ministry for Education and Research (project01KI20271); University of Bonn; University of Bielefeld; the Medical Biodefense Research Program of Bundeswehr-Medical-Service; Euroimmun, RocheDiagnostics provided discounted kits and machines.