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Research ArticleOpen Access

Is it Possible to Mathematically Predict the outcomes of Treatment of Abdominal Inflammation?

Volume 5 - Issue 5

Sławomir Jabłoński*1, Sylwia Kustalik1sup>, Magdalena Drzewiecka-Jędrzejczyk2, Piotr Misiak1, Szymon Wcisło1 and Marcin Kozakiewicz3

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    • 1Department of Thoracic Surgery, General and Oncological Surgery, Medical University of Lodz, Poland
    • 2Department of Endocrine, General and Oncological Surgery, Medical University of Lodz, Poland
    • 3Department of Maxillofacial Surgery, Medical University of Lodz, Poland

    *Corresponding author: Sławomir Jabłoński, Department of Thoracic Surgery, General and Oncological Surgery, Medical University of Lodz, 90-549 Łódź, 113 Żeromskiego St., 17 Daleka St., 93-348 Łódź, Poland

Received: June 04, 2018;   Published: June 20, 2018

DOI: 10.26717/BJSTR.2018.05.001256

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Abstract

Aim:

The aim of this study was to assess whether the statistical determination of the outcomes of treatment of abdominal inflammation is possible.

Materials and Methods: The sample size in this study consisted of 49 patients who underwent surgery due to abdominal inflammatory states. Data for six biochemical and two clinical parameters were collected for the purpose of constructing a prognostic scale designed by the authors.

Results:

The multi-dimensional space that resulted from the data collected was reduced to a three-dimensional model by analysis of 3 factors: inflammation, proteinic status and general risk. Firstly, all cases were categorized based on their respective composite Recovery Prediction Factor (SNC=62%, SPC=55%). Secondly, it was determined that two cases could not be categorized due to their dichotomic division based on factors 1, 2 and 3 (SNC=79%, SPC=95%). Lastly, based on its median origin dichotomic division (SNC=72%, SPC=84%), one case could not be categorized.

Conclusion: It is possible to predict the outcomes of the treatment of abdominal inflammation, based on statistical factor analysis and a factor average prediction engine. However, some degree of uncertainty must be taken into account with respect to the probability that a given outcome may unfold in a given patient.

Keywords: Intra-Abdominal Infections; Prediction Method; Inflammatory Status; Proteinic Status; Recovery Prediction Factor; Sepsis

Abbreviations: HGB: Hemoglobin Level; HCT: Hematocrit; WBC: White Blood Cell Count; Na: Serum Sodium; K: Potassium Level; CRP-C: Reactive Protein; PCT: Procalcitonin; AM Risk Calculator: Acute Mediastinitis Risk Calculator; SNC: Sensitivity Coefficient; SPC: Specifity Coefficient; ICED: Index of Coexistent Diseases; NRI - Nutritional Risk Index; GNRI: Geriatric Nutritional Risk Index; PINI: Prognostic Inflammatory and Nutritional Index; ASA: American Society of Anesthesiologists Physical Status; LOD: Logistic Organ Dysfunction system; RPF: Recovery Prediction Factor

Abstract| Background| Material and Methods| Results| Discussion| Conclusion| Acknowledgement| References|