Data Mining for Identifying Novel Associations and Temporal Relationships with Charcot Foot

Abstract

Introduction. Charcot foot is a rare and devastating complication of diabetes. While some risk factors are known, debate continues regarding etiology. Elucidating other associated disorders and their temporal occurrence could lead to a better understanding of its pathogenesis. We applied a large data mining approach to Charcot foot for elucidating novel associations. Methods. We conducted an association analysis using ICD-9 diagnosis codes for every patient in our health system (n = 1.6 million with 41.2 million time-stamped ICD-9 codes). For the current analysis, we focused on the 388 patients with Charcot foot (ICD-9 713.5). Results. We found 710 associations, 676 (95.2%) of which had a P value for the association less than 1.0 × 10−5 and 603 (84.9%) of which had an odds ratio > 5.0. There were 111 (15.6%) associations with a significant temporal relationship (P < 1.0 × 10−3). The three novel associations with the strongest temporal component were cardiac dysrhythmia, pulmonary eosinophilia, and volume depletion disorder. Conclusion. We identified novel associations with Charcot foot in the context of pathogenesis models that include neurotrophic, neurovascular, and microtraumatic factors mediated through inflammatory cytokines. Future work should focus on confirmatory analyses. These novel areas of investigation could lead to prevention or earlier diagnosis.

Charcot foot syndrome

“…A recent study of a large population has also reported some novel statistical associations with conditions not previously linked with the Charcot foot: cardiac dysrhythmia, pulmonary eosinophilia and volume depletion . The significance of these findings will require further study.…”

Precision Medicine for Managing Diabetes

“…Greater individualization of medical care will become possible when traditional sources medical information (the history, physical examination, and laboratory panel) can be augmented by 2 new powerful sources of information. These sources are (1) data mining for multidimensional phenotypic data 6 and (2) improved genomic and omics analyses for structural and functional genotypic data, including pharmacogenomic data. 7 This is now the right time to reclassify the use of genomic information in medicine because of newly available sources of phenotypic and genotypic big data.…”

“…By the time of the taxonomy report in 2011 the cost was $21 000. 6 In 2014 Illumina launched its HiSeq X Ten Sequencer, which delivers the first $1000 genome. 11 The greater availability of such genetic information combined with new databases have both led to renewed hopes that specific descriptions of patients at the molecular level and individualized predictions of responses to treatments will soon become powerful tools for precision medicine.…”

Charcot Neuropathic Arthropathy of the Foot: A Literature Review and Single-Center Experience

“…Bilateral disability has been observed in numbers ranging from 9 to 39% of patients. When MRI is used as a diagnostic method, the detection rate rises to 75% of documented cases [ 2 , 3 ]. Sohn et al [ 4 ] state that the mortality rate is 28.3% within five years in patients with CN.…”