Socioeconomic and racial disparities were associated with patients with severe AS receiving TAVR at a major referral center. This study emphasizes the importance of improving access to standard of care for these subgroups of cardiac patients.

Sepsis is distinguished by an overwhelming uncontrolled inflammatory response to a pathogen (e.g. Escherichia coli, E. coli). The interval from the onset of sepsis to treatment is a critical factor for patient survival. We hypothesize that ventilatory pattern variability (VPV; autocorrelation coefficient (r), Mutual Information, (MI), Sample Entropy (SampEn) and nonlinear complexity index (NLCI)), respiratory frequency (fR), and cardio‐ventilatory coupling (CVC) are biometrics that vary with neural inflammation and may signal the onset of a sepsis. Male, Sprague Dawley rats (n=35) received surgically implanted pressure transducers (DSI telemetry; arterial blood pressure, (BP)), allowed 2wks to recover, then placed unanesthetized in whole‐body plethysmography (Buxco) set on a receiver (EMKA) for baseline (0h) recordings. Then, we implanted them with a thrombin‐fibrinogen pellet, which was either sterile (D0) or contained 25 x 106 CFU E. coli (D25). After inoculation, we recorded ventilation at 3h (D0 n=5, D25 N=5), 6h (D0 n=3, D25 n=5), 15h (D0 n=4, D25 n=4), 24h (D0 n=4, D25 n=5) and analyzed fR, VPV & CRC. We tested for differences with a 2‐way, repeated‐measures ANOVA, both within groups between 0h and each hour and between D0 and D25 at each hour. fR did not differ from 0h or between D0 and D25 by 3, 6 and12h; but increased by 24h (D0 and D25 (p<001)). Similarly, VPV became more predictable by 15h D25 (r at 1 cycle length, D0 0.59 ± 0.08 vs 0.69 ± 0.201, p<0.001; MI, D0 0.37 ± 0.100 vs D25 0.49 ± 0.11 bits, p<.001; and NLCI, D0 0.08 ± 0.05 vs D25 0.15 ± 0.04 p<0.001). CVC changed, in the distribution (χ2) of the intervals between the peak of the R‐wave the transition from expiration‐to‐inspiration phase switch (EIPS) by 15h for D25 (D0, 66.3 ± 53.1 vs D25, 31.2 ± 19.1, p< 0.001). Transformed relative Shannon entropy (tRSE) for the R‐wave‐to‐EIPS intervals did not differ at any time point. Heart rate (HR) changed at 15hr for D25 (D0, 400 ± 47 vs D25, 445 ± 33, p<0.001). These results suggest that fR, VPV and CVC biometrics change as systemic infection progresses and may be useful measures of sepsis progression over time in critically ill patients.

Little is known regarding gender differences in response to systemic infection. Progesterone peaks during proestrus and is associated with increased respiratory frequency and reduced cytokine expression during systemic infection compared to nonproestrus. We hypothesized that hormone fluctuations during the estrus cycle may not only affect respiration, but also the systemic inflammation impact on respiratory pattern. We compared baseline and changes in Ventilatory Pattern Variability (VPV, Autocorrelation coefficient (r at one‐cycle length), Mutual Information (MI), Sample Entropy (SampEn) and Nonlinear Complexity Index (NLCI)) in proestrus and nonproestrus in Sprague Dawley rats (n=44) during peritonitis and compared male (n=24) to females. CWRU IACUC approved all experiments. We tracked estrus cycle stage by characterizing vaginal epithelial cells and recorded ventilatory pattern in conscious unrestrained rats using whole‐body plethysmography. We sacrificed 10 females (n=5 proestrus and 5 nonproestrus) and 8 males (Naïve rats). In the remaining, we implanted clots containing 0 (D0) or 100x106 (D100) Escherichia coli cells. In addition to naïve groups, we studied: 1) D0 proestrus (n=7), 2) D100 proestrus (n=13), 3) D0 non‐proestrus (n=6), 4) D100 non‐proestrus (n=8), 5) D0 males (n=6) and 6) D100 males (n=10). We measured durations of inspiration (Ti), expiration (Te) and cycle (Ttot), r, MI, SampEn and NLCI. At D100, aside from SampEn between proestrus and nonproestrus (1.25±0.12 vs 1.13±0.05, p<0.01), the response to systemic infection was cycle independent. By 12h in infected rats compared to D0, MI increased and SampEn decreased in nonproestrus but not proestrus (0.69±0.09 vs 0.55±0.05, p=0.02; 1.13±0.05 vs 1.28±0.09, p=0.03); NLCI increased in proestrus but not in nonproestrus (0.21±0.12 vs 0.10±0.05 p=0.05). In naïve rats, r at one‐cycle length, CV, and MI varied between male and female (0.65±0.13 vs 0.40±0.15; p=0.006); (0.1±0.03 vs 0.19±0.05; p=0.04); (0.613±0.106 vs 0.45±0.08; p=0.02). Males responded to systemic infection more robustly than females; higher fR (122.4±31.2 vs 79.2±11.3, p<0.001); lower SampEn (1.08±0.15 vs 1.20±0.11, p=0.004); and higher NLCI (0.28±0.10 vs 0.19±0.12, p=0.009). In summary, proestrus effects on VPV are evident when comparing ventilatory patterns within the estrus cycle and against males during the development of peritonitis. SampEn was the variable that was consistently different. SampEn measures predictability of the pattern; a lower value implies more predictability. NLCI is derived from the difference in SampEn of the original dataset from the mean of 19 surrogate datasets. Stochastic variability is preserved in surrogate datasets while deterministic variability is disrupted. Thus, during proestrus lower NLCI indicates decreased deterministic variability in female rats, and perhaps, less sickness.

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