Background Patient matching in intensive care databases yields sample sizes too small for individualised outcome analysis. Current AI systems provide population-level guideline summaries but omit stratification variables that may invert therapy signals at the individual level.

Methods We developed the Therapeutic Distance framework, which computes the z-standardised distance between a patient’s clinical parameters and the centroid of MIMIC-IV patients who received each therapy: d(P,T) = Σ wi(T) · |(Li − μi(T)) / σi|. We hypothesise that patients at the same distance to a therapy (same orbit) have comparable outcomes. Six validation experiments were performed on 11,627 sepsis patients (SAPS-II 30–80) from MIMIC-IV v3.1.

Results Echo-stratified vasopressin recipients showed mortality of 30.1% (n=146, 95% CI 22.6–37.7%) versus 53.9% without echo (n=2,426, 95% CI 51.9–55.9%). Confidence intervals did not overlap (bootstrap, 1,000 resamples). However, echo-stratified patients had lower general severity (SAPS-II 49.2 vs 53.9) but higher cardiac biomarkers (troponin 1.0 vs 0.51 ng/mL), indicating that the observed difference is compatible with both severity confounding and a possible cardiac-specific vasopressin effect. Leave-one-out prediction with uniform weights achieved AUC 0.61 as a structural baseline.

Conclusions Therapeutic Distance replaces patient matching with orbit matching, substantially increasing usable sample sizes. The echo-vasopressin finding is hypothesis-generating and mechanistically plausible but not causally proven. The framework is intended as a clinical decision support signal under uncertainty, not as a causal inference method.

The author is the developer of chicxulub.ai, which hosts the MAHLER retrieval engine and the KeplerTwin system described in this paper.

This study did not receive any funding. All computational resources were self-funded by the author.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study used the MIMIC-IV v3.1 database, a de-identified publicly available critical care dataset. The institutional review board of Beth Israel Deaconess Medical Center (Boston, MA) approved the creation of the database (protocol 2001P001699). Individual investigator IRB approval is waived for analyses of MIMIC-IV as the dataset contains only de-identified data. Access was obtained through PhysioNet after completion of the Collaborative Institutional Training Initiative (CITI) program in human subjects research.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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MIMIC-IV v3.1 is available through PhysioNet. Validation scripts are available at https://chicxulub.ai.