Oura Ring Gen 4 sensor data — not clinical measurementsN=1 case study — not validated for clinical decisionsHEV diagnosed Mar 18; interpret findings cautiously in this Day 8 post-ruxolitinib window

Causal Inference: Ruxolitinib

Data period: 2026-01-08 to 2026-03-23 (75 days) | Total runtime: 1.2s
Generated 2026-03-27 07:10 · Post-HSCT Patient
Four complementary causal analysis methods explore whether Oura biometrics shifted after ruxolitinib (10 mg BID, started 2026-03-16) on Oura Ring biometrics. Data period: 2026-01-08 to 2026-03-23 (75 days).
Warning: Post-intervention period is very short (8 days). Results should be interpreted with caution. Minimum 14-21 days of post-intervention data recommended.
Pre-intervention
Info
67days
Post-intervention
Insufficient
8days
Raw p<0.05
Info
0/0
FDR-significant
None
0/0
Lowest raw p
Not significant
p=1.000
N/A | q=1.0000
Methods used
Info
4
CI + PCMCI+ + TE + Mediation
Table of contents:
  1. CausalImpact - Bayesian Structural Time Series
  2. Statistical Power & Interpretation
  3. Placebo tests (falsification)
  4. Granger Causality Network (PCMCI+)
  5. Transfer Entropy
  6. Intervention Response Decomposition
  7. Clinical Interpretation

1. CausalImpact - Bayesian Structural Time Series Analysis

Method: Bayesian Structural Time Series (BSTS) models pre-intervention dynamics and generates a counterfactual prediction for the post-period. The difference between actual and counterfactual estimates the causal effect, with full posterior uncertainty. MCMC: 5,000 iterations, weekly seasonal component (nseasons=7). Benjamini-Hochberg FDR correction for multiple testing.

FAILED CausalImpact package not installed. Install with: pip install pycausalimpact

1a. Statistical Power & Interpretation

Purpose: All 11 metrics sorted by statistical significance, with Benjamini-Hochberg corrected q-values for multiple testing.

No CausalImpact results available for statistical power analysis.

1b. Placebo tests (intervention date falsification)

Method: CausalImpact is run with 3 random placebo dates in the pre-period on the 3 most significant metrics. Placebo dates should NOT show significant effects.

CausalImpact failed, skipping placebo

2. Granger Causality Network (PCMCI+)

Method: PCMCI+ (tigramite) tests for time-lagged causal relationships between biometric variables using partial correlation. Tau_max = 7 days.

Full period (0 days): No significant causal links found.

Pre-ruxolitinib (0 days): No significant causal links found.

3. Transfer Entropy

Method: Transfer entropy quantifies directional information flow between biometric streams. Comparison of TE matrices for pre- and full period reveals changes in information coupling after ruxolitinib start.

Full period (67 days)

SourceTargetTE (bits)Net TE
TotalSleepLowestHR0.5057+0.1814
DeepDurLowestHR0.5057+0.1932
RMSSDmaxLowestHR0.5057+0.2439
SpO2LowestHR0.5057+0.0548
TempDevLowestHR0.5057+0.1932
REMdurRespRate0.5041+0.1875
TotalSleepRespRate0.5041+0.1798
DeepDurRespRate0.5041+0.1916

Pre-ruxolitinib (60 days)

SourceTargetTE (bits)Net TE
REMdurRespRate0.4826+0.1887
REMpctRespRate0.4826+0.2721
TotalSleepRespRate0.4826+0.3072
DeepDurRespRate0.4826+0.1536
RMSSDRespRate0.4826+0.0920
RMSSDmaxRespRate0.4826+0.2721
LowestHRRespRate0.4826+0.0834
AvgHRRespRate0.4826+0.1686

Change in information flow

Largest increase: REMdur -> TotalSleep (+0.1489 bits)

Largest decrease: REMpct -> TempDev (-0.0649 bits)

4. Intervention Response Decomposition

Method: Linear mediation analysis (Baron-Kenny) decomposes total ruxolitinib effect into four mediating pathways. Bootstrap (2000 iterations) for confidence intervals.
+2.9
Total effect (readiness score)
64.8 -> 67.7
Pre -> Post average
p=0.469
Raw p-value Not significant
PathwayMediator (pre->post)a (T->M) b (M->Y)Indirect effect [95% CI] % mediatedp-value
Direct cardiac
Ruxolitinib -> HR change -> Readiness
92.97 -> 92.23-0.109-0.476+0.0520
[-0.2529, +0.3470]
24.9%0.7140 NS
Autonomic
Ruxolitinib -> HRV change -> Readiness
10.03 -> 11.42+0.535+0.620+0.3320
[-0.1788, +1.1762]
95.8%0.3520 NS
Sleep-mediated
Ruxolitinib -> Sleep efficiency -> Readiness
78.62 -> 81.60+0.884+0.134+0.1185
[-0.0977, +0.4055]
18.0%0.3420 NS
Inflammatory
Ruxolitinib -> Temperature deviation -> Readiness
0.06 -> -0.16-0.870-0.357+0.3103
[-0.0269, +0.8368]
89.6%0.1030 NS

5. Clinical Interpretation

Executive summary

N/A
Strongest signal: p=1.000
0/0
Metrics trending in expected direction
8
Post-intervention days (Day 14 target)
  • N/A: strongest hypothesis-generating raw p-value signal (p=1.0000, q=1.0000). It does not survive FDR correction, so confirmation still depends on more post-treatment follow-up.
  • CausalImpact: 0 of 0 biometric streams show significant causal change (p < 0.05). After Benjamini-Hochberg FDR correction: 0 of 0 remain significant (q < 0.05).
  • Placebo validation: N/A - ?/? placebo tests reached significance. This keeps the result vulnerable to false positives rather than establishing a confirmed intervention effect.
  • PCMCI+: 0 significant time-lagged causal links identified in the biometric network
  • Mediation analysis: 0 of 4 mediating pathways show significant indirect effect

Limitations

  • Short post-period (8 days): All results are preliminary. Minimum 14-21 days of post-intervention data recommended for robust causal inference.
  • Confounders: Linear methods cannot capture non-linear interactions. Seasonal variation, activity level, and other medications are not controlled for.
  • Wearable data: Oura Ring is not a medical device. Measurements have inherent noise that can affect causal estimates.
  • Single patient: N=1 study without control group. Causality cannot be definitively established, but Bayesian posterior probability of effect provides a strength measure.
  • HEV diagnosis: HEV was diagnosed 2026-03-18 (2 days after ruxolitinib start). Hepatitis may confound biometric changes.

Recommendations

  1. Repeat analysis after 2-3 weeks of ruxolitinib treatment for robust causal inference
  2. Add HEV-related biomarkers (ALT, bilirubin) as time-varying covariates
  3. Consider synthetic control method when longer time series are available
  4. Combine with clinical endpoints (GVHD scoring, ferritin) for multimodal analysis