Development of a multivariable model predicting COVID-19 mortality risk from comorbidities in an Italian cohort of 18,286 confirmed cases aged 40 years or older

Background: large studies on the predictive role of chronic conditions on mortality from COVID‑19 are scarce. We developed a predictive model of death from COVID‑19 in an Italian cohort aged 40 years or older.Methods: we conducted a cohort study on prospectively collected data. The cohort included all (n=18,286) swab positive cases ≥40 year-old in patients registered with the Agency for Health Protection (AHP) of Milan up to 27/04/2020. Data on comorbidities were obtained from the chronic condition administrative database of the AHP. A multivariable logistic regression model, including age and gender and the selected conditions, was fitted to predict 30-day mortality risk and internally validated. External validation and recalibration were performed in a cohort of untested subjects with COVID-19 like symptoms. R software was used for the analysis.Results: chronic conditions having the largest model-adjusted odds ratio (OR) of dying within 30 days from COVID-19 infection were chronic heart failure (OR=1.9, 95%CI 1.5-2.5), tumors (OR=1.8, 95%CI 1.4-2.3), complicated diabetes (OR=1.6, 95%CI 1.1-2.2) and dialysis-dependent chronic kidney disease (OR=1.5, 95%CI 1.0-2.2). Bootstrap-validated c-index was 0.78. The model fitted on the validation cohort had a c-index of 0.93, but required recalibration. With this latter model, at a 10% risk of death threshold, 11% of the AHP population aged 40 years or older is considered at high risk.Conclusion: we identified a selected number of comorbidities predicting early risk of death in a large COVID-19 cohort aged 40 years or older. In a new epidemic wave, our results will help physicians and health systems to identify high-risk subject to target for prevention and therapy in this specific age group.

Should Gamma Knife be Offered as a Primary Treatment for a Resectable Glomus Jugulare Tumor?

ABSTRACT Attempted total resections is the preferred treatment option in the management of glomus jugulare tumors in most subjects. In the elderly patients, it may be advisable to leave a tiny residue over the involved cranial nerve to preserve function. In a medically unfit and anesthetically high-risk subject observation with serial MRI scans is the preferred line of management. If in such a patient there occurs brainstem compression, it is prudent to only operate the intracranial part to relieve the compression explaining the very high-risk in this group. Radiotherapy is not to be offered as a primary treatment for glomus jugulare tumors.

Heart rate control in normal and aborted-SIDS infants

Approximate entropy (ApEn), a mathematical formula quantifying regularity in data, was applied to heart rate data from normal and aborted-sudden infant death syndrome (SIDS) infants. We distinguished quiet from rapid-eye-movement (REM) sleep via the following three criteria, refining the notion of REM as more "variable": 1) REM sleep has greater overall variability (0.0374 +/- 0.0138 vs. 0.0205 +/- 0.0090 s, P < 0.005); 2) REM sleep is less stationary (StatAv = 0.742 +/- 0.110) than quiet sleep (StatAv = 0.599 +/- 0.159, P < 0.03); 3) after normalization to overall variability, REM sleep is more regular (ApEnsub = 1.224 +/- 0.092) than quiet sleep (ApEnsub = 1.448 +/- 0.071, P < 0.0001). Fifty percent of aborted-SIDS infants showed greater ApEn instability across quiet sleep than any normal infant exhibited, suggesting that autonomic regulation of heart rate occasionally becomes abnormal in a high-risk subject. There was an association between low ApEn values and aborted-SIDS events; 5 of 14 aborted-SIDS infants had at least one quiet sleep epoch with an ApEn value below the minimum of 45 normal-infant ApEn values.