Heart Rate Variability Measurement Through a Smart Wearable Device in Congenital Central Hypoventilation Syndrome (CCHS): Influence of PHOX2B Genotype
Bibliographic record
Abstract
Abstract Rationale: CCHS is a rare genetic disorder associated with awide array of autonomic nervous system (ANS)-related abnormalities, including cardiovascular dysfunction. CCHS is caused by PHOX2B mutations including polyalanine repeat expansion mutations (PARMs) or non-PARMs (NPARMs). CCHS phenotype severity, including cardiovascular dysfunction, is related to PHOX2B genotype. Heart Rate Variability (HRV) is a well-established measurement of ANS cardiovascular function and a key biomarker in CCHS. Given the rarity and geographic dispersion of CCHS, methods of remote HRV monitoring in this population are critical. This study investigated HRV using thesmart wearable Hexoskin® system (Carre Technologies Inc., Montreal, Canada) in CCHS patients compared to healthy controls. Methods: 16 CCHS patients and 21 healthy controls were enrolled. Six CCHS patients had repeated measurements (annual visits, 22 total CCHS recordings). CCHS patients were divided into the following groups: 1) severe PHOX2B genotypes including 20/27 PARMs and severe NPARMs (N=13 recordings) and 2) moderate PHOX2B genotypes including 20/25, 20/26, and non-severe NPARMs (N=9 recordings). For each recording, between 1-34 hours of continuous electrocardiogram (ECG) was captured using Hexoskin® 3-lead ECG. ECG data were processed through Kubios® HRV Premium (Kubios, Kuopio, Finland). Time-domain-based HRV parameters (standard deviation of NN intervals (SDNN) andtheroot mean square of successive differences (RMSSD)), and frequency-domain-based HRV parameters (low-frequency/high-frequency ratio (LF/HF)) were calculated. Short-term (SD1)and long-term (SD2) variations in heart rate and their ratio were obtained using Poincaré plots. Results: Hexoskin®-based HRV assessment in CCHS patients versus healthy controls showed significant alterations in all domains. Comparing all CCHS patients to healthy controls revealed higher levels of time domain parameters SDNN (p=0.0001) and RMSSD (p=0.0136), frequency domain LF/HF (p=0.0237), and non-linear domain SD1/SD2 (p=0.0357). A significant increase in SDNN (p=0.0019) in the CCHS severe genotype group was detected compared to the healthy control group. Significant increases in the levels of SDNN (p=0.02), RMSSD (p=0.0002), andLF/HF ratio (p=0.03) were identified in theCCHS moderate genotype group compared to the healthy control group. Conclusion: This study highlights the feasibility of wearable technology to monitor HRV in CCHS patients. Validation of these results on alarge scale in the home, especially compared to hospital-based, gold-standard systems, would be the logical next step to move toward remote HRV monitoring in CCHS. Collectively this would allow clinical guidance based on in-home recordings in activities of daily living and serve as a reliable biomarker for future therapeutic trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".