Combating heart attacks with knowledge

BACKGROUND Despite worldwide efforts to develop an effective COVID vaccine, it is quite evident that initial supplies will be limited. Therefore, it is important to develop methods that will ensure that the COVID vaccine is allocated to the people who are at major risk until there is a sufficient global supply. OBJECTIVE The purpose of this study was to develop a machine-learning tool that could be applied to assess the risk in Massachusetts towns based on community-wide social, medical, and lifestyle risk factors. METHODS I compiled Massachusetts town data for 29 potential risk factors, such as the prevalence of preexisting comorbid conditions like COPD and social factors such as racial composition, and implemented logistic regression to predict the amount of COVID cases in each town. RESULTS Of the 29 factors, 14 were found to be significant (p < 0.1) indicators: poverty, food insecurity, lack of high school education, lack of health insurance coverage, premature mortality, population, population density, recent population growth, Asian percentage, high-occupancy housing, and preexisting prevalence of cancer, COPD, overweightness, and heart attacks. The machine-learning approach is 80% accurate in the state of Massachusetts and finds the 9 highest risk communities: Lynn, Brockton, Revere, Randolph, Lowell, New Bedford, Everett, Waltham, and Fitchburg. The 5 most at-risk counties are Suffolk, Middlesex, Bristol, Norfolk, and Plymouth. CONCLUSIONS With appropriate data, the tool could evaluate risk in other communities, or even enumerate individual patient susceptibility. A ranking of communities by risk may help policymakers ensure equitable allocation of limited doses of the COVID vaccine.

Download Full-text

Effects of omega-3 acid ethyl esters and aspirin, alone and in combination, on platelet function in healthy subjects

Thrombosis and Haemostasis ◽

10.1160/th08-02-0084 ◽

2008 ◽

Vol 100 (10) ◽

pp. 634-641 ◽

Cited By ~ 47

Author(s):

Mark K. Larson ◽

Joseph H. Ashmore ◽

Kristina A. Harris ◽

Jessica L. Vogelaar ◽

James V. Pottala ◽

...

Keyword(s):

Platelet Aggregation ◽

Platelet Function ◽

Combined Therapy ◽

Significant Risk ◽

Ethyl Esters ◽

Omega 3 ◽

Heart Attacks ◽

Impedance Aggregometry ◽

Patients At Risk ◽

Clinically Significant

SummaryOmega-3 fatty acids (n-3 FA) from oily fish are clinically useful for lowering triglycerides and reducing risk of heart attacks. Accordingly, patients at risk are often advised to take both aspirin and n-3 FA. However, both of these agents can increase bleeding times, and the extent to which the combination inhibits platelet function is unknown. The purpose of this pilot study was to determine the effects of a prescription omega-3 FA product (P-OM3) and aspirin, alone and in combination, on platelet aggregation assessed by whole blood impedance aggregometry (WBA). Ten healthy volunteers provided blood samples on four separate occasions: Day 1, baseline; Day 2, one day after taking aspirin (2 x 325 mg tablets); Day 29, after 28 days of P-OM3 (4 capsules/day); and Day 30, after one day of combined P-OM3 and aspirin. WBA was tested with two concentrations of collagen, with ADP and with a thrombin receptor activating peptide (TRAP). Compared to baseline, aspirin alone inhibited aggregation only with low-dose collagen stimulation;P-OM3 alone did not inhibit aggregation with any agonist; and combined therapy inhibited aggregation with all agonists butTRAP. Significant interactions between interventions were not observed in response to any agonist. In conclusion, P-OM3 alone did not inhibit platelet aggregation, but did (with two agonists) when combined with aspirin. Since previous studies have not reported a clinically significant risk for bleeding in subjects on combined therapy, P-OM3 may safely enhance the anti-platelet effect of aspirin.

Download Full-text