The Social Vulnerability Metric (SVM) As A New Tool for Public Health.
Saulsberry Loren et al. Health services research 2022 11
The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018).
The correlation between SVM scores and national age-adjusted county all-cause mortality was r=0.68. This correlation demonstrated the SVM’s robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% versus 12%).
Asthma: From Phenotypes to Personalized Medicine
P Bakakos, J Per Med, November 6, 2022
Asthma is a heterogeneous disease of the airways with a high prevalence worldwide characterized by chronic inflammation. The aim of asthma management is the control of the disease, and the cornerstone of asthma treatment is inhaled corticosteroids. Asthma is no longer recognized as a unique manifestation, and the “one size fits all” approach may apply only in the treatment of mild asthma.
Measurement of Exhaled Volatile Organic Compounds as a Biomarker for Personalised Medicine: Assessment of Short-Term Repeatability in Severe Asthma
A Azim et al, J Per Medicine, September 29, 2022
The intra-subject and between-subject variability of each VOC was calculated across the 70 samples and identified 30.35% of VOCs to be erratic: variable between subjects but also variable in the same subject. Exclusion of these erratic VOCs from machine learning approaches revealed no apparent loss of structure to the underlying data or loss of relationship with salient clinical characteristics. Moreover, cluster evaluation by the silhouette coefficient indicates more distinct clustering.
Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome
C Cervia et al, Nature Comms, January 25, 2022
In a prospective multicentric cohort study of 215 individuals, we study COVID-19 patients during primary infection and up to one year later, compared to healthy subjects. We discover an immunoglobulin (Ig) signature, based on total IgM and IgG3 levels, which – combined with age, history of asthma, and five symptoms during primary infection – is able to predict the risk of PACS independently of timepoint of blood sampling.