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Decompression illness medically reported by hyperbaric treatment facilities: cluster analysis of 1929 cases
Tamer Ozyigit1, Salih Murat Egi, Petar Denoble
1Galatasaray University, Industrial Engineering Department, Istanbul, Turkey. tozyigit@gsu.edu.tr
Objective classification of decompression illness (DCI) using cluster analysis identified four distinct patient groups. This method offers an objective approach to understanding DCI manifestations, independent of clinical judgment.
Area of Science:
- Diving Medicine
- Hyperbaric Medicine
- Biostatistics
Background:
- Decompression illness (DCI) lacks consensus on clinically useful subclasses.
- Objective classification of DCI manifestations is needed.
Purpose of the Study:
- To explore an objective DCI classification using multivariate statistics.
- To assess naturally associated clusters of DCI manifestations.
- To evaluate mapping onto other DCI classifications and therapeutic outcomes.
Main Methods:
- Utilized two-step cluster analysis and Bayesian information criterion.
- Confirmed with hierarchical clustering (squared Euclidean distances, Ward's method).
- Analyzed 1929 DCI cases from Divers Alert Network (DAN America) (1999-2003).
Main Results:
- Identified four robust and significant clusters of DCI manifestations.
- Cluster 1: Pain only.
- Cluster 2: Numbness, paresthesia, decreased skin sensitivity.
- Cluster 3: Malaise, paralysis, muscular weakness, bladder-bowel dysfunction.
- Cluster 4: Diverse symptoms including hearing loss, skin mottling, confusion, dyspnea, vision problems, altered consciousness, and vertigo.
Conclusions:
- Clusters mapped poorly to traditional DCI categories (AGE, Type I/II DCS) but better to the Perceived Severity Index (PSI).
- All classification methods predicted complete relief equally well.
- Cluster analysis provides an objective method for classifying DCI manifestations.
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