Applying Sequential Pattern Mining to Investigate the Temporal Relationships between Commonly Occurring Internal Medicine Diseases and Intervals for the Risk of Concurrent Disease in Canine Patients
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Canine Patients
2.2. Identification of Internal Medicine Diseases
2.3. SPM
2.4. Statistical Analysis
3. Results
3.1. Canine Patient Population
3.2. Comorbidity Association Rules and Intervals for Internal Medicine Diseases
3.2.1. Hyperadrenocorticism
3.2.2. Myxomatous Mitral Valve Disease
3.2.3. Chronic Pancreatitis
3.2.4. Chronic Kidney Disease
3.2.5. CAD
3.3. Risk of Progression of the Five Most Common Veterinary Internal Medicine Diseases
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Dx | Gender | Frequency | Size † | Frequency | Analogy ‡ | Frequency | Total |
---|---|---|---|---|---|---|---|
HAC | Female | 15 | Small | 132 | Pediatric | 11 | 152 |
Spayed female | 53 | Medium | 19 | Adult | 91 | ||
Male | 10 | Large | 1 | Senior | 21 | ||
Castrated male | 74 | Extra Large | 0 | Geriatric | 29 | ||
MMVD | Female | 10 | Small | 130 | Pediatric | 23 | 140 |
Spayed female | 51 | Medium | 10 | Adult | 84 | ||
Male | 14 | Large | 0 | Senior | 11 | ||
Castrated male | 65 | Extra Large | 0 | Geriatric | 22 | ||
CAD | Female | 7 | Small | 68 | Pediatric | 6 | 85 |
Spayed female | 29 | Medium | 14 | Adult | 52 | ||
Male | 4 | Large | 3 | Senior | 10 | ||
Castrated male | 45 | Extra Large | 0 | Geriatric | 17 | ||
CKD | Female | 19 | Small | 123 | Pediatric | 26 | 137 |
Spayed female | 52 | Medium | 12 | Adult | 79 | ||
Male | 8 | Large | 2 | Senior | 13 | ||
Castrated male | 58 | Extra Large | 0 | Geriatric | 19 | ||
Chronic pancreatitis | Female | 8 | Small | 62 | Pediatric | 13 | 68 |
Spayed female | 25 | Medium | 5 | Adult | 40 | ||
Male | 5 | Large | 1 | Senior | 7 | ||
Castrated male | 30 | Extra Large | 0 | Geriatric | 8 |
Risk of Disease | OR (95% CI) | p | Risk of Disease | OR (95% CI) | p | ||
---|---|---|---|---|---|---|---|
HAC ≥ MMVD | CAD ≥ CKD | ||||||
Controls | 0.237 (94/396) | Reference | Controls | 0.178 (15/84) | Reference | ||
HAC | 0.286 (42/147) | 1.285 (0.839–1.968) | 0.249 | CAD | 0.262 (121/462) | 0.613 (0.338–1.111) | 0.107 |
HAC ≥ CAD | CAD ≥ Chronic pancreatitis | ||||||
Controls | 0.134 (53/396) | Reference | Controls | 0.118 (10/85) | Reference | ||
HAC | 0.201 (30/149) | 1.632 (0.996–2.667) | 1.632 | CAD | 0.123 (57/462) | 0.947 (0.463–1.938) | 0.882 |
HAC ≥ CKD | CKD ≥ HAC | ||||||
Controls | 0.096 (38/396) | Reference | Controls | 0.246 (101/410) | Reference | ||
HAC | 0.095 (14/148) | 1.653 (1.086–2.515) | 0.019 * | CKD | 0.341 (45/132) | 1.582 (1.035–2.419) | 0.034 * |
HAC ≥ Chronic pancreatitis | CKD ≥ MMVD | ||||||
Controls | 0.096 (38/396) | Reference | Controls | 0.219 (90/410) | Reference | ||
HAC | 0.187 (28/150) | 2.162 (1.273–3.672) | 0.004 * | MMVD | 0.360 (49/136) | 2.003 (1.314–3.051) | <0.001 * |
MMVD ≥ CAD | CKD ≥ CAD | ||||||
Controls | 0.093 (13/140) | Reference | Controls | 0.110 (15/136) | Reference | ||
MMVD | 0.177 (72/407) | 0.476 (0.255–0.890) | 0.02 * | CKD | 0.168 (69/410) | 0.613 (0.338–1.111) | 0.107 |
MMVD ≥ CKD | CKD ≥ Chronic pancreatitis | ||||||
Controls | 0.214 (87/407) | Reference | Controls | 0.078 (32/410) | Reference | ||
CKD | 0.352 (49/139) | 2.003 (1.314–3.051) | <0.001 * | CKD | 0.250 (34/136) | 3.937 (2.318–6.689) | <0.0001 * |
MMVD ≥ Chronic pancreatitis | Chronic pancreatitis ≥ HAC | ||||||
Controls | 0.115 (16/139) | Reference | Controls | 0.254 (122/480) | Reference | ||
MMVD | 0.123 (50/407) | 0.929 (0.510–1.691) | 0.809 | Chronic pancreatitis | 0.406 (26/64) | 2.008 (1.171–3.444) | 0.011 * |
MMVD ≥ HAC | Chronic pancreatitis ≥ MMVD | ||||||
Controls | 0.258 (105/407) | Reference | Controls | 0.231 (15/65) | Reference | ||
MMVD | 0.314 (43/137) | 1.316 (0.861–2.010) | 0.204 | Chronic pancreatitis | 0.256 (123/480) | 0.871 (0.472–1.606) | 0.658 |
CAD ≥ HAC | Chronic pancreatitis ≥ CAD | ||||||
Controls | 0.257 (119/462) | Reference | Controls | 0.149 (10/67) | Reference | ||
CAD | 0.354 (29/82) | 1.577 (0.958–2.596) | 0.073 | Chronic pancreatitis | 0.156 (75/480) | 0.947 (0.463–1.938) | 0.882 |
CAD ≥ MMVD | Chronic pancreatitis ≥ CKD | ||||||
Controls | 0.143 (12/84) | Reference | Controls | 0.212 (102/480) | Reference | ||
CAD | 0.275 (127/462) | 0.440 (0.231–0.837) | 0.012 * | Chronic pancreatitis | 0.508 (33/65) | 3.822 (2.242–6.513) | <0.0001 * |
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Lee, S.-J.; Kim, J.-H. Applying Sequential Pattern Mining to Investigate the Temporal Relationships between Commonly Occurring Internal Medicine Diseases and Intervals for the Risk of Concurrent Disease in Canine Patients. Animals 2023, 13, 3359. https://doi.org/10.3390/ani13213359
Lee S-J, Kim J-H. Applying Sequential Pattern Mining to Investigate the Temporal Relationships between Commonly Occurring Internal Medicine Diseases and Intervals for the Risk of Concurrent Disease in Canine Patients. Animals. 2023; 13(21):3359. https://doi.org/10.3390/ani13213359
Chicago/Turabian StyleLee, Suk-Jun, and Jung-Hyun Kim. 2023. "Applying Sequential Pattern Mining to Investigate the Temporal Relationships between Commonly Occurring Internal Medicine Diseases and Intervals for the Risk of Concurrent Disease in Canine Patients" Animals 13, no. 21: 3359. https://doi.org/10.3390/ani13213359
APA StyleLee, S.-J., & Kim, J.-H. (2023). Applying Sequential Pattern Mining to Investigate the Temporal Relationships between Commonly Occurring Internal Medicine Diseases and Intervals for the Risk of Concurrent Disease in Canine Patients. Animals, 13(21), 3359. https://doi.org/10.3390/ani13213359