Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model

Crit Care. 2023 May 2;27(1):167. doi: 10.1186/s13054-023-04437-2.


BACKGROUND: Identifying patterns within ICU medication regimens may help artificial intelligence algorithms to better predict patient outcomes; however, machine learning methods incorporating medications require further development, including standardized terminology. The Common Data Model for Intensive Care Unit (ICU) Medications (CDM-ICURx) may provide important infrastructure to clinicians and researchers to support artificial intelligence analysis of medication-related outcomes and healthcare costs. Using an unsupervised cluster analysis approach in combination with this common data model, the objective of this evaluation was to identify novel patterns of medication clusters (termed ‘pharmacophenotypes’) correlated with ICU adverse events (e.g., fluid overload) and patient-centered outcomes (e.g., mortality).

METHODS: This was a retrospective, observational cohort study of 991 critically ill adults. To identify pharmacophenotypes, unsupervised machine learning analysis with automated feature learning using restricted Boltzmann machine and hierarchical clustering was performed on the medication administration records of each patient during the first 24 h of their ICU stay. Hierarchical agglomerative clustering was applied to identify unique patient clusters. Distributions of medications across pharmacophenotypes were described, and differences among patient clusters were compared using signed rank tests and Fisher’s exact tests, as appropriate.

RESULTS: A total of 30,550 medication orders for the 991 patients were analyzed; five unique patient clusters and six unique pharmacophenotypes were identified. For patient outcomes, compared to patients in Clusters 1 and 3, patients in Cluster 5 had a significantly shorter duration of mechanical ventilation and ICU length of stay (p < 0.05); for medications, Cluster 5 had a higher distribution of Pharmacophenotype 1 and a smaller distribution of Pharmacophenotype 2, compared to Clusters 1 and 3. For outcomes, patients in Cluster 2, despite having the highest severity of illness and greatest medication regimen complexity, had the lowest overall mortality; for medications, Cluster 2 also had a comparably higher distribution of Pharmacophenotype 6.

CONCLUSION: The results of this evaluation suggest that patterns among patient clusters and medication regimens may be observed using empiric methods of unsupervised machine learning in combination with a common data model. These results have potential because while phenotyping approaches have been used to classify heterogenous syndromes in critical illness to better define treatment response, the entire medication administration record has not been incorporated in those analyses. Applying knowledge of these patterns at the bedside requires further algorithm development and clinical application but may have the future potential to be leveraged in guiding medication-related decision making to improve treatment outcomes.

PMID:37131200 | PMC:PMC10155304 | DOI:10.1186/s13054-023-04437-2


Free CME credits

Both our subscription plans include Free CME/CPD AMA PRA Category 1 credits.

Digital Certificate PDF

On course completion, you will receive a full-sized presentation quality digital certificate.

medtigo Simulation

A dynamic medical simulation platform designed to train healthcare professionals and students to effectively run code situations through an immersive hands-on experience in a live, interactive 3D environment.

medtigo Points

medtigo points is our unique point redemption system created to award users for interacting on our site. These points can be redeemed for special discounts on the medtigo marketplace as well as towards the membership cost itself.
  • Registration with medtigo = 10 points
  • 1 visit to medtigo’s website = 1 point
  • Interacting with medtigo posts (through comments/clinical cases etc.) = 5 points
  • Attempting a game = 1 point
  • Community Forum post/reply = 5 points

    *Redemption of points can occur only through the medtigo marketplace, courses, or simulation system. Money will not be credited to your bank account. 10 points = $1.

All Your Certificates in One Place

When you have your licenses, certificates and CMEs in one place, it's easier to track your career growth. You can easily share these with hospitals as well, using your medtigo app.

Our Certificate Courses