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ArticleDigestive diseases and sciences2018

Plasma mtDNA Analysis Aids in Predicting Pancreatic Necrosis in Acute Pancreatitis Patients: A Pilot Study.

Lin Wu, Wujian Xu, Fangyu Wang, Tangfeng Lv, Zhiqiang Yin, Yong Song

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Article in Digestive diseases and sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03788928 (Study of Plasma mitDNA in Predicting Pancreatic Necrosis in Acute Pancreatitis), which is not on this map. Cited by 12 papers, 2 of them syntheses that pooled it.

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12citing papers in PubMed, 2 pooled it
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03788928 unknown statusnot on this mapstarted 2019, after this paper: background citation

Study of Plasma mitDNA in Predicting Pancreatic Necrosis in Acute Pancreatitis

TypeobservationalSponsorAssiut UniversityRan2019 to 2020Enrolled25ConditionsPancreatic NecrosisArmsserum mitochondrial DNA
3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lin WuDepartment of Gastrointestinal Disease, Jinling Hospital, Nanjing, China.
Wujian XuDepartment of Respiratory Medicine, Jinling Hospital, 305 Zhongshan Road, Nanjing, China.
Fangyu WangDepartment of Gastrointestinal Disease, Jinling Hospital, Nanjing, China.
Tangfeng LvDepartment of Respiratory Medicine, Jinling Hospital, 305 Zhongshan Road, Nanjing, China.
Zhiqiang YinChinese PLA 359 Hospital, 8 Zhongshan Road, Zhenjiang, China. yinzhiqiang359@163.com.
Yong SongDepartment of Respiratory Medicine, Jinling Hospital, 305 Zhongshan Road, Nanjing, China. yong_song6310@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpecific plasma biomarkers in predicting pancreatic necrosis (PNec) are needed in treating acute pancreatitis (AP).

aimsTo investigate the prognostic value of plasma mitochondrial DNA fragments (mtDNA) in patient with AP for PNec.

methodsAP patients with symptoms onset within 72 h were prospectively enrolled from June 2015 through June 2017 and were assessed for PNec using contrast-enhanced CT scan. Plasma mtDNA concentration (specific mitochondrial gene ND1) was measured using qRT-PCR.

resultsOf the 74 AP patients included, significant higher median level of plasma mtDNA was found in severe AP patients than in mild AP patients and healthy controls, but not in moderately severe AP patients. Patients with PNec had higher level of plasma mtDNA than those without PNec (774.2 [IQR 397.6-2205.0] vs. 169.5 [IQR 73.6-683.4] pg/ml, P < 0.05). The area under the receiver operator characteristic curve (ROC-AUC) of mtDNA for predicting PNec was higher than that of CRP (0.813 [95% CI 0.705-0.895] vs. 0.678 [95% CI 0.558-0.783]). Using a cutoff value of 302.5 pg/ml, the sensitivity and specificity for diagnosing PNec were 90.9 and 68.3%, respectively. Finally, plasma mtDNA levels decreased significantly after continuous renal replacement therapy (717.7 [IQR 307.00-1370.00] vs. 237.5 [IQR 117.20-464.80] pg/ml, P < 0.01).

conclusionsElevated plasma mtDNA content in AP patients may be used as a more accurate early predictor of PNec in contrast to traditional CRP.

Indexed as

AdultAgedBiomarkersCase-Control StudiesDNA, MitochondrialFemaleHumansMaleMiddle AgedPancreatitis, Acute NecrotizingPilot ProjectsBiomarkersDNA, MitochondrialAcute pancreatic necrosisAcute pancreatitisC-reactive proteinMitochondrial DNA

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.