Diagnostic Accuracy of Leucine-Rich α-2-Glycoprotein 1 as a Non-Invasive Salivary Biomarker in Pediatric Appendicitis Article Swipe
Goran Tintor
,
Miro Jukić
,
Daniela Šupe‐Domić
,
Ana Jerončić
,
Zenon Pogorelić
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/ijms24076043
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/ijms24076043
The aim of this study is to evaluate the diagnostic accuracy of leucine-rich α-2-glycoprotein 1 (LRG1) in saliva as a novel biomarker for acute appendicitis in the pediatric population. From October 2021 to June 2022, 92 children aged 5 to 17 years who presented with acute abdomen and suspected acute appendicitis were enrolled in this prospective study. The parameters documented included demographic and clinical information, as well as operative and postoperative data. Patients were divided into two groups: those with acute appendicitis who underwent laparoscopic appendectomy (n = 46) and those without appendicitis (n = 46). The total white blood cell (WBC) count, percent of neutrophils, C-reactive protein (CRP) level, and salivary LRG1 were compared between groups. A commercially available enzyme-linked immunosorbent assay (ELISA) LRG kit was used to measure the LRG levels. The median salivary LRG1 level was significantly higher in the group of children with pathohistologically confirmed acute appendicitis compared to the control group: 233.45 ng/mL (IQR 114.9, 531.2) vs. 55.95 ng/mL (IQR 51.5, 117.9), p < 0.001. LRG1 had an overall good receiver-operator characteristic area under the curve of 0.85 (95% CI 0.76–0.92; p < 0.001). The optimal LRG1 cutoff with best separation between acute appendicitis and the controls was >352.6 ng/mL (95% CI from >270.7 to >352.6). Although the specificity was 100% at this cutoff, the sensitivity for identifying appendicitis was 36%. In addition, a significant difference was found between groups in the laboratory values of all inflammatory markers tested: WBC, absolute neutrophil count, and CRP (p < 0.001 for all). Although LRG1 in saliva showed a good AUC parameter and significantly higher values in patients with acute appendicitis compared to the controls, its usefulness in the patient population who present at emergency departments with abdominal pain is debatable. Future studies should focus on investigating its diagnostic potential.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/ijms24076043
- https://www.mdpi.com/1422-0067/24/7/6043/pdf?version=1679554848
- OA Status
- gold
- Cited By
- 19
- References
- 54
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4360616096Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/ijms24076043Digital Object Identifier
- Title
-
Diagnostic Accuracy of Leucine-Rich α-2-Glycoprotein 1 as a Non-Invasive Salivary Biomarker in Pediatric AppendicitisWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-03-23Full publication date if available
- Authors
-
Goran Tintor, Miro Jukić, Daniela Šupe‐Domić, Ana Jerončić, Zenon PogorelićList of authors in order
- Landing page
-
https://doi.org/10.3390/ijms24076043Publisher landing page
- PDF URL
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https://www.mdpi.com/1422-0067/24/7/6043/pdf?version=1679554848Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/1422-0067/24/7/6043/pdf?version=1679554848Direct OA link when available
- Concepts
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Medicine, Biomarker, Appendicitis, Gastroenterology, Internal medicine, Saliva, Prospective cohort study, Receiver operating characteristic, White blood cell, Acute appendicitis, Acute abdomen, Surgery, Biochemistry, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
19Total citation count in OpenAlex
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2025: 9, 2024: 4, 2023: 6Per-year citation counts (last 5 years)
- References (count)
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54Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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