Linear Combination of Leukocyte Count and D-Dimer Levels in the Diagnosis of Patients with Non-traumatic Acute Abdomen
Abstract
Aim: Rapid intervention is required in patients with non-traumatic acute abdominal pain. It is very important to distinguish between surgical and non-surgical pathologies during this intervention. This study aimed to increase the diagnostic accuracy by combining the leukocyte count and D-dimer levels used in this evaluation with linear combination methods.
Materials and Methods: Logistic regression, scoring, min-max, minimax, Su & Liu, Pepe & Thompson, Pepe, Cai & Langton, and Todor & Saplacan methods were used as linear combination methods. The data set was divided into 70% training set and 30% test set. Parameter optimization was performed on the training data by 5 fold cross-validation method using 10 repeats. The area under the ROC curve, sensitivity, selectivity, accuracy, positive and negative predictive value, and positive and negative likelihood ratio statistics were used in the performance evaluation.
Results: The area under the ROC curve statistic for D-dimer level and log-transformed leukocyte count variable were obtained as 0.71 and 0.70, respectively. The accuracy rate was 0.69 for the D-dimer level and 0.73 for log-transformed leukocyte count. For the linear combination methods, the area under the ROC curve was between 0.77 and 0.81, and the accuracy statistics were between 0.72 and 0.79. The best performance was obtained with the min-max method.
Conclusion: In patients with non-traumatic acute abdominal pain, leukocyte count and D-dimer levels can be evaluated together by using linear combination methods in differentiating surgical and non-surgical pathologies. The obtained results showed that the diagnostic performance of the combined results with the min-max procedure was higher than the leukocyte count and D-dimer levels.
Thanks
We would like to thank Prof. Dr. Hızır Yakup Akyıldız for sharing data.
References
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- 13. Liu C, Liu A, Halabi S. A min–max combination of biomarkers to improve diagnostic accuracy. Stat Med. 2011;30:2005–14.
- 14. Todor N, Todor I, Saplacan G. Tools to identify linear combination of prognostic factors which maximizes area under receiver operator curve. J Clin Bioinforma. 2014;4:1–7.
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Abstract
References
- 1. Graff LG, Robinson D. Abdominal pain and emergency department evaluation. Emerg Med Clin North Am. 2001;19:123-36.
- 2. Yeniocak S, Turkmen S, Uzun O, et al. Analysis of Patients Presenting to the Emergency Department with Acute Abdominal Pain. J Acad Emerg Med. 2012;11:212-5.
- 3. Akyıldız HY, Sozuer E, Akcan A, et al. The value of D-dimer test in the diagnosis of patients with non-traumatic acute abdomen. Ulus Travma Acil Cer. 2010;16:22-26.
- 4. Zararsiz G, Akyildiz HY, Goksuluk D, et al. Statistical learning approaches in diagnosing patients with nontraumatic acute abdomen. Turk J Electr Eng Comput Sci. 2016;24: 3685-97.
- 5. Gohel P, Singh P, Mohanty M. Explainable AI: current status and future directions. arXiv: 2107.07045v1.
- 6. Kang L, Liu A, Tian L. Linear combination methods to improve diagnostic/prognostic accuracy on future observations. Stat Methods Med Res. 2016;25:1359–80.
- 7. Yin J, Tian L. Optimal linear combinations of multiple diagnostic biomarkers based on Youden index. Stat Med. 2014;33:1426-40.
- 8. Coolen-Maturi T. Predictive inference for best linear combination of biomarkers subject to limits of detection. Stat Med. 2017;36:2844-74.
- 9. Pepe MS, Thompson ML. Combining diagnostic test results to increase accuracy. Biostatistics. 2000;1:123–40.
- 10. Pepe MS, Cai T, Longton G. Combining predictors for classification using the area under the receiver operating characteristic curve. Biometrics. 2006;62:221–9.
- 11. Su JQ, Liu. Linear combinations of multiple diagnostic markers. Journal of the American Statistical Association. 1993;88:1350–5.
- 12. Sameera G, Vardhan RV, Sarma KVS. Binary classification using multivariate receiver operating characteristic curve for continuous data. JJ Biopharm Stat. 2016;26:421–31.
- 13. Liu C, Liu A, Halabi S. A min–max combination of biomarkers to improve diagnostic accuracy. Stat Med. 2011;30:2005–14.
- 14. Todor N, Todor I, Saplacan G. Tools to identify linear combination of prognostic factors which maximizes area under receiver operator curve. J Clin Bioinforma. 2014;4:1–7.
- 15. Kyurkchiyan SG, Popov TM, Shakola F, et al. A Pilot Study Reveals the Potential of miR-31-3p and miR-196a-5p as Non-Invasive Biomarkers in Advanced Laryngeal Cancer. Folia Med. 2021;63: 355-64.
- 16. Huang K, Li Q, Zeng W et al. Ultrasound score combined with liver stiffness measurement by sound touch elastography for staging liver fibrosis in patients with chronic hepatitis B: a clinical prospective study. Ann Transl Med. 2022;10:271.
- 17. Zhang G, Yang C, Kang X, et al. The combination of cerebrospinal fluid procalcitonin, lactate, interleukin-8 and interleukin-10 concentrations for the diagnosis of postneurosurgical bacterial meningitis: A prospective study. Ann Clin Biochem. 2019; 56:133-40.
- 18. Han WK, Waikar SS, Johnson A, et al. Urinary biomarkers in the early diagnosis of acute kidney injury. Kidney Int. 2008;73:863-9.
Details
| Primary Language | English |
|---|---|
| Subjects | Clinical Sciences |
| Journal Section | Original Articles |
| Authors | |
| Early Pub Date | January 15, 2023 |
| Publication Date | January 15, 2023 |
| Acceptance Date | December 2, 2022 |
| Published in Issue | Year 2023 Volume: 5 Issue: 1 |
Chief Editors
Assoc. Prof. Zülal Öner
Address: İzmir Bakırçay University, Department of Anatomy, İzmir, Türkiye
Assoc. Prof. Deniz Şenol
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