Sickle Cell Disease Subjects Have a Distinct Abnormal Autonomic Phenotype Characterized by Peripheral Vasoconstriction With Blunted Cardiac Response to Head-Up Tilt

In sickle cell disease (SCD), prolonged capillary transit times, resulting from reduced peripheral blood flow, increase the likelihood of rigid red cells entrapment in the microvasculature, predisposing to vaso-occlusive crisis. Since changes in peripheral flow are mediated by the autonomic nervous system (ANS), we tested the hypothesis that the cardiac and peripheral vascular responses to head-up tilt (HUT) are abnormal in SCD. Heart rate, respiration, non-invasive continuous blood pressure and finger photoplethysmogram (PPG) were monitored before, during, and after HUT in SCD, anemic controls and healthy subjects. Percent increase in heart rate from baseline was used to quantify cardiac ANS response, while percent decrease in PPG amplitude represented degree of peripheral vasoconstriction. After employing cluster analysis to determine threshold levels, the HUT responses were classified into four phenotypes: (CP) increased heart rate and peripheral vasoconstriction; (C) increased heart rate only; (P) peripheral vasoconstriction only; and (ST) subthreshold cardiac and peripheral vascular responses. Multinomial logistic regression (MLR) was used to relate these phenotypic responses to various parameters representing blood properties and baseline cardiovascular activity. The most common phenotypic response, CP, was found in 82% of non-SCD subjects, including those with chronic anemia. In contrast, 70% of SCD subjects responded abnormally to HUT: C-phenotype = 22%, P-phenotype = 37%, or ST-phenotype = 11%. MLR revealed that the HUT phenotypes were significantly associated with baseline cardiac parasympathetic activity, baseline peripheral vascular variability, hemoglobin level and SCD diagnosis. Low parasympathetic activity at baseline dramatically increased the probability of belonging to the P-phenotype in SCD subjects, even after adjusting for hemoglobin level, suggesting a characteristic autonomic dysfunction that is independent of anemia. Further analysis using a mathematical model of heart rate variability revealed that the low parasympathetic activity in P-phenotype SCD subjects was due to impaired respiratory-cardiac coupling rather than reduced cardiac baroreflex sensitivity. By having strong peripheral vasoconstriction without compensatory cardiac responses, P-phenotype subjects may be at increased risk for vaso-occlusive crisis. The classification of autonomic phenotypes based on HUT response may have potential use for guiding therapeutic interventions to alleviate the risk of adverse outcomes in SCD

Exploring indoor and outdoor dust as a potential tool for detection and monitoring of COVID-19 transmission

This study investigated the potential of using SARS-CoV-2 viral concentrations in dust as an additional surveillance tool for early detection and monitoring of COVID-19 transmission. Dust samples were collected from 8 public locations in 16 districts of Bangkok, Thailand, from June to August 2021. SARS-CoV-2 RNA concentrations in dust were quantified, and their correlation with community case incidence was assessed. Our findings revealed a positive correlation between viral concentrations detected in dust and the relative risk of COVID-19. The highest risk was observed with no delay (0-day lag), and this risk gradually decreased as the lag time increased. We observed an overall decline in viral concentrations in public places during lockdown, closely associated with reduced human mobility. The effective reproduction number for COVID-19 transmission remained above one throughout the study period, suggesting that transmission may persist in locations beyond public areas even after the lockdown measures were in place

McDAPS: A multi-channel physiological signals display and analysis system for clinical researchers

We introduce McDAPS, an interactive software for assessing autonomic imbalance from non-invasive multi-channel physiological recordings. McDAPS provides a graphical user interface for data visualization, beat-to-beat processing and interactive analyses. The software extracts beat-to-beat RR interval systolic blood pressure, diastolic blood pressure, the pulse amplitude of photoplethysmogram and the pulse-to-pulse interval. The analysis modules include stationary and time-varying power spectral analyses, moving-correlation analysis and univariate analyses. Analyses can also be performed in batch mode if multiple datasets have to be processed in the same way. The program exports results in standard CSV format.McDAPS runs in MATLAB, and is supported on MS Windows and MAC OS systems. The MATLAB source code is available at https://github.com/thuptimd/McDAPS.git

Biophysical markers of the peripheral vasoconstriction response to pain in sickle cell disease

<div><p>Painful vaso-occlusive crisis (VOC), a complication of sickle cell disease (SCD), occurs when sickled red blood cells obstruct flow in the microvasculature. We postulated that exaggerated sympathetically mediated vasoconstriction, endothelial dysfunction and the synergistic interaction between these two factors act together to reduce microvascular flow, promoting regional vaso-occlusions, setting the stage for VOC. We previously found that SCD subjects had stronger vasoconstriction response to pulses of heat-induced pain compared to controls but the relative degrees to which autonomic dysregulation, peripheral vascular dysfunction and their interaction are present in SCD remain unknown. In the present study, we employed a mathematical model to decompose the total vasoconstriction response to pain into: 1) the neurogenic component, 2) the vascular response to blood pressure, 3) respiratory coupling and 4) neurogenic-vascular interaction. The model allowed us to quantify the contribution of each component to the total vasoconstriction response. The most salient features of the components were extracted to represent biophysical markers of autonomic and vascular impairment in SCD and controls. These markers provide a means of phenotyping severity of disease in sickle-cell anemia that is based more on underlying physiology than on genotype. The marker of the vascular component (BM_v) showed stronger contribution to vasoconstriction in SCD than controls (p = 0.0409), suggesting a dominant myogenic response in the SCD subjects as a consequence of endothelial dysfunction. The marker of neurogenic-vascular interaction (BM_n-v) revealed that the interaction reinforced vasoconstriction in SCD but produced vasodilatory response in controls (p = 0.0167). This marked difference in BM_n-v suggests that it is the most sensitive marker for quantifying combined alterations in autonomic and vascular function in SCD in response to heat-induced pain.</p></div

List of abbreviations.

<p>List of abbreviations.</p

FBV response partitioned into contributions from each model component.

<p>Predicted ΔFBV by each model component (thick lines) plotted on top of the measured ΔFBV (thin lines) during a test procedure in (a) a non-SCD subject and (b) a SCD subject, showing the relative contribution from each component on the total ΔFBV. The bottom row shows the sum of the predicted ΔFBV by all model components (thick line).</p

FBV responses of the interaction between pain and blood pressure and derived biophysical marker BM_n-v.

<p>(a) <i>FBV</i>_{<i>BPCTHM</i>}, responses of the interaction between the simulated Temp and MAP pulses (mean ± SEM) in SCD (N = 22, thick line) and non-SCD (N = 23, thin line); (b) biophysical marker BM_n-v reflecting total change in FBV as a result of the interaction between the two inputs. Error bars show mean ± SEM. SCD vasoconstricted while non-SCD vasodilated (p = 0.0167).</p

Standardized FBV responses to a pain pulse and derived biophysical marker BM_n.

<p>(a) <i>h</i>_<i>THM</i>, standardized FBV responses to a pain pulse (mean ± SEM) in SCD (N = 22, thick line) and non-SCD (N = 23, thin line); (b) biophysical marker BM_n capturing the initial neurogenic vasoconstriction caused by the direct effect of pain. Error bars show mean ± SEM. SCD had slightly stronger vasoconstriction than non-SCD (not statistically significant).</p

Schematic diagram of the model of peripheral vasoconstriction response to heat-induced pain.

<p>Functional relationships between changes in temperature (ΔTemp), blood pressure (ΔMAP) and respiration (ΔV_T) as inputs and changes in finger blood volume (ΔFBV) as the output. ε_FBV denotes extraneous fluctuations on FBV that are not captured by the model.</p