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Data mining for identifying novel associations and temporal relationships with Charcot foot.

Munson ME, Wrobel JS, Holmes CM, Hanauer DA - J Diabetes Res (2014)

Bottom Line: 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.CONCLUSION.Future work should focus on confirmatory analyses.

View Article: PubMed Central - PubMed

Affiliation: Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, 24 Frank Lloyd Wright Drive, Lobby C, Suite 1300, Ann Arbor, MI 48106, USA.

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.

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Association diagram showing the clinical milieu in which Charcot foot (pink node in center of square) often exists. Each node represents an ICD-9 code, with the size of the node proportional to its frequency in the overall dataset and node colors representing high-level clinical categories (see legend). Edges between nodes represent highly significant associations. Arrowheads show temporality with preceding nodes pointing to subsequent nodes. This figure was made using the following criteria: association P value < 1.0 × 10−176; association odds ratio > 200; temporal P value < 1.0 × 10−6. The two red nodes directly pointing to Charcot foot are related to type 2 diabetes (ICD-9 codes 250.60 and 250.90).
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fig1: Association diagram showing the clinical milieu in which Charcot foot (pink node in center of square) often exists. Each node represents an ICD-9 code, with the size of the node proportional to its frequency in the overall dataset and node colors representing high-level clinical categories (see legend). Edges between nodes represent highly significant associations. Arrowheads show temporality with preceding nodes pointing to subsequent nodes. This figure was made using the following criteria: association P value < 1.0 × 10−176; association odds ratio > 200; temporal P value < 1.0 × 10−6. The two red nodes directly pointing to Charcot foot are related to type 2 diabetes (ICD-9 codes 250.60 and 250.90).

Mentions: Our data mining approach revealed 710 pairs of associations between Charcot foot and other disorders, 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%) pairs that had a significant temporal relationship with a P value of less than 1.0 × 10−3. A full list of all 710 associations with Charcot foot can be found in the Supplementary Table. Figure 1 provides a high-level overview of some of the diagnoses associated with Charcot foot or associated with other closely related diagnoses. This figure also shows the strongest temporal relationships, using arrows between two diagnoses to represent the temporality.


Data mining for identifying novel associations and temporal relationships with Charcot foot.

Munson ME, Wrobel JS, Holmes CM, Hanauer DA - J Diabetes Res (2014)

Association diagram showing the clinical milieu in which Charcot foot (pink node in center of square) often exists. Each node represents an ICD-9 code, with the size of the node proportional to its frequency in the overall dataset and node colors representing high-level clinical categories (see legend). Edges between nodes represent highly significant associations. Arrowheads show temporality with preceding nodes pointing to subsequent nodes. This figure was made using the following criteria: association P value < 1.0 × 10−176; association odds ratio > 200; temporal P value < 1.0 × 10−6. The two red nodes directly pointing to Charcot foot are related to type 2 diabetes (ICD-9 codes 250.60 and 250.90).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4020407&req=5

fig1: Association diagram showing the clinical milieu in which Charcot foot (pink node in center of square) often exists. Each node represents an ICD-9 code, with the size of the node proportional to its frequency in the overall dataset and node colors representing high-level clinical categories (see legend). Edges between nodes represent highly significant associations. Arrowheads show temporality with preceding nodes pointing to subsequent nodes. This figure was made using the following criteria: association P value < 1.0 × 10−176; association odds ratio > 200; temporal P value < 1.0 × 10−6. The two red nodes directly pointing to Charcot foot are related to type 2 diabetes (ICD-9 codes 250.60 and 250.90).
Mentions: Our data mining approach revealed 710 pairs of associations between Charcot foot and other disorders, 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%) pairs that had a significant temporal relationship with a P value of less than 1.0 × 10−3. A full list of all 710 associations with Charcot foot can be found in the Supplementary Table. Figure 1 provides a high-level overview of some of the diagnoses associated with Charcot foot or associated with other closely related diagnoses. This figure also shows the strongest temporal relationships, using arrows between two diagnoses to represent the temporality.

Bottom Line: 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.CONCLUSION.Future work should focus on confirmatory analyses.

View Article: PubMed Central - PubMed

Affiliation: Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, 24 Frank Lloyd Wright Drive, Lobby C, Suite 1300, Ann Arbor, MI 48106, USA.

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.

Show MeSH
Related in: MedlinePlus