Investigation of simple, objective, and effective indicators for predicting acute paraquat poisoning outcomes

Yiwei Su, Weiwei Liu, Guanghui Dong, Zhengmin Qian, Namratha Gurram, Echu Liu, Lenise A. Cummings-Vaughn, Steven W. Howard, Michael G. Vaughn, Daire R. Jansson, Chen Zhang, Jianyu Wang, Yimin Liu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Initial symptoms of paraquat (PQ) toxicity are often not obvious, and the lack of advanced testing equipment and medical conditions in the primary hospital make it difficult to provide early diagnosis and timely treatment. To explore simple, objective, and effective indicators of prognosis for primary clinicians, we retrospectively analyzed acute PQ poisoning in 190 patients admitted to our hospital from 2008 to 2017. Based on their condition at the time of discharge, patients were categorized into either the survival group (n = 71) or the mortality group (n = 119). Age, PQ ingested amount, urinary PQ, urinary protein, white blood cell (WBC), and serum creatinine (Cr) were the key factors associated with the prognosis for PQ poisoning. We identified specific diagnostic thresholds for these key indicators of PQ poisoning: PQ ingested amount (36.50 mL), urinary PQ (semiquantitative result “++”), urinary protein (semiquantitative result “±”), WBC (16.50 × 109/L), and serum Cr (102.10 µmol/L). Combining these five indicators to identify poisoning outcomes was considered objective, accurate, and convenient. When the combined score was <1, the predicted probability of patient death was 6%. When the combined score was ≥3, the predicted probability of patient death was 96%. These findings provide metrics to assist primary clinicians in predicting outcomes of acute PQ poisoning at earlier stages, a basis for administering treatment.

Original languageEnglish
Pages (from-to)417-426
Number of pages10
JournalToxicology and Industrial Health
Volume36
Issue number6
DOIs
StatePublished - Jun 1 2020

Keywords

  • Paraquat
  • acute poisoning
  • biological indicators
  • predictive indicator

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