Attention is a core function in cognition and also the most prevalent cognitive deficit in mild traumatic brain injury (mTBI). Predictive timing is an essential element of attention functioning because sensory processing and execution of goal-oriented behavior are facilitated by temporally accurate prediction. It is hypothesized that impaired synchronization between prediction and external events accounts for the attention deficit in mTBI. Other cognitive and somatic or affective symptoms associated with mTBI may be explained as secondary consequences of impaired predictive timing. Eye-Tracking Rapid Attention Computation (EYE-TRAC) is the quantification of predictive timing with indices of dynamic visuo-motor synchronization (DVS) between the gaze and the target during continuous predictive visual tracking. Such quantification allows for cognitive performance monitoring in comparison to the overall population as well as within individuals over time. We report preliminary results of normative data and data collected from subjects with a history of mTBI within 2 weeks of injury and post-concussive symptoms at the time of recruitment. A substantial proportion of mTBI subjects demonstrated DVS scores worse than 95% of normal subjects. In addition, longitudinal monitoring of acute mTBI subjects showed that initially abnormal DVS scores were followed by improvement toward the normal range. In summary, EYE-TRAC provides fast and objective indices of DVS that allow comparison of attention performance to a normative standard and monitoring of within-individual changes.
Recent epidemiological studies have demonstrated that common cardiovascular risk factors are strongly associated with adverse outcomes in COVID-19. Coronary artery calcium (CAC) and epicardial fat (EAT) have shown to outperform traditional risk factors in predicting cardiovascular events in the general population. We aim to determine if CAC and EAT determined by Computed Tomographic (CT) scanning can predict all-cause mortality in patients admitted with COVID-19 disease. We performed a retrospective, post-hoc analysis of all patients admitted to Montefiore Medical Center with a confirmed COVID-19 diagnosis from March 1st, 2020 to May 2nd, 2020 who had a non-contrast CT of the chest within 5 years prior to admission. We determined ordinal CAC scores and quantified the epicardial (EAT) and thoracic (TAT) fat volume and examined their relationship with inpatient mortality. A total of 493 patients were analyzed. There were 197 deaths (39.95%). Patients who died during the index admission had higher age (72, [64–80] vs 68, [57–76]; p < 0.001), CAC score (3, [0–6] vs 1, [0–4]; p < 0.001) and EAT (107, [70–152] vs 94, [64–129]; p = 0.023). On a competing risk analysis regression model, CAC ≥ 4 and EAT ≥ median (98 ml) were independent predictors of mortality with increased mortality of 63% (p = 0.003) and 43% (p = 0.032), respectively. As a composite, the group with a combination of CAC ≥ 4 and EAT ≥ 98 ml had the highest mortality. CAC and EAT measured from chest CT are strong independent predictors of inpatient mortality from COVID-19 in this high-risk cohort.
Purpose
Coronary artery calcium (CAC) and epicardial adipose tissue (EAT) can predict AF in the general population. We aimed to determine if CAC and EAT measured by computed tomographic (CT) scanning can predict new-onset AF in patients admitted with COVID-19 disease.
Methods
We performed a retrospective, post hoc analysis of all patients admitted to Montefiore Medical Center with a confirmed COVID-19 diagnosis from March 1st to June 23rd, 2020, who had a non-contrast CT of the chest within 5 years prior to admission. We determined ordinal CAC scores and quantified the EAT volume and examined their relationship with inpatient mortality.
Results
A total of 379 patients were analyzed. There were 16 events of new-onset AF (4.22%). Patients who developed AF during the index admission were more likely to be male (75 vs 47%,
p
< 0.001) and had higher EAT (129.5 [76.3–197.3] vs 91.0 [60.0–129.0] ml,
p
= 0.049). There were no differences on age (68 [56–71] vs 68 [58–76] years;
p
= 0.712), BMI (28.5 [25.3–30.8] vs 26.9 [23.1–31.8] kg/m
2
;
p
= 0.283), ordinal CAC score (3 [1–6] vs 2 [0–4];
p
= 0.482), or prevalence of diabetes (56.3 vs 60.1%;
p
= 0.761), hypertension (75.0 vs 87.3%,
p
= 0.153), or coronary artery disease (50.0 vs 39.4%,
p
= 0.396). Patients with new-onset AF had worse clinical outcomes (death/intubation/vasopressors) (87.5 vs 44.1%;
p
= 0.001).
Conclusion
Increased EAT measured by non-contrast chest CT identifies patients hospitalized with COVID-19 at higher risk of developing new-onset AF. Patients with new-onset AF have worse clinical outcomes.
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