Hypokalemia is a biochemical signal of poor prognosis for acute paraquat poisoning within 4 hours

The significance of APACHE II as a predictor of mortality in paraquat poisoning: A systematic review and meta-analysis

The Acute Physiology and Chronic Health Evaluation II (APACHE II) scoring system is utilised as a prognostic method in paraquat poisoning; however, current evidence shows ambiguity. Although some studies have shown APACHE II to be a superior tool, others have reported it inferior to other prognostic markers, such as lactate, severity index of paraquat poisoning and urine paraquat concentration. Hence, to address this ambiguity, we conducted a systematic review and meta-analysis to analyse prognostic accuracy of APACHE II score in predicting mortality in paraquat poisoning. We included twenty studies with 2524 paraquat poisoned patients in the systematic review, after a comprehensive literature search in databases PubMed, Embase, Web of Science, Scopus and Cochrane Library, from which 16 studies were included in the meta-analysis. The survivors of paraquat poisoning were found to have significantly lower APACHE II scores (Mean Difference (MD): -5.76; 95% CI: -7.93 to -3.60 p < 0.0001; n = 16 studies) compared to non-survivors. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) for APACHE II score <9 was found to be 74%, 68%, 2.58, 0.38 and 7.10, respectively (n = 5 studies). The area under the curve (AUC) of the bivariate summary receiver operating characteristic (SROC) curve was found to be 0.80. The pooled sensitivity, specificity, PLR, NLR and DOR for APACHE II score ≥9 was found to be 73%, 86%, 4.69, 0.33 and 16.42, respectively (n = 9 studies). The AUC of the SROC curve was found to be 0.89. Pairwise AUC comparison of APACHE II with other prognostic markers showed serum presepsin to have a significantly better discriminatory ability than APACHE II. Through the findings of this study, we conclude that APACHE II was found to be a good indicator of death in paraquat poisoning patients. However, higher APACHE II scores (≥9) depicted greater specificity in predicting mortality in paraquat poisoning. Thus, APACHE II can be used as a practical tool in the hand of physicians to prognose patients with paraquat poisoning to aid clinical decisions.

Risk factors and optimal predictive scoring system of mortality for children with acute paraquat poisoning

BACKGROUND

There is no suitable scoring system that can be used to predict mortality in children with acute paraquat intoxication (APP).

AIM

To optimize a predictive scoring system for mortality in children with APP.

METHODS

A total of 113 children with APP from January 1, 2010 to January 1, 2020 were enrolled in this study. These patients were divided into survivors and non-survivors. We compared the clinical characteristics between the two groups and analyzed the independent prognostic risk factors. The survival rates of patients with different values of the pediatric critical illness score (PCIS) were assessed using kaplan-meier survival analysis. The best scoring system was established by using the area under the receiver operating characteristic curve analysis.

RESULTS

The overall mortality rate was 23.4%. All non-survivors died within 20 days; 48.1% (13/27) died within 3 days, and 70.3% (19/27) died within 7 days. Compared to survivors, the non-survivors were older, had higher white blood cell count, alanine aminotransferase (ALT), aspartate aminotransferase, serum creatinine, blood urea nitrogen, glucose, and pediatric early warning score, and had lower platelet count, albumin, Serum sodium (Na⁺) and PCIS. ALT and PCIS were the independent prognostic risk factors for children with APP. The survival rate of children classified as extremely critical patients (100%) was lower than that of children classified as critical (60%) or noncritical (6.7%) patients. The specificity of ALT was high (96.51%), but the sensitivity was low (59.26%). The sensitivity and specificity of ALT combined with PCIS were high, 92.59% and 87.21%, respectively. The difference in mortality was significantly higher for ALT combined with PCIS (area under the receiver operating characteristic: 0.937; 95%CI: 0.875-0.974; P < 0.05).

CONCLUSION

In our study, ALT and PCIS were independent prognostic risk factors for children with APP. ALT combined with PCIS is an optimal predictive mortality scoring system for children with APP.

The acute paraquat poisoning mortality (APPM) score to predict the risk of death in paraquat-poisoned patients

CONTEXT

Mortality prediction in paraquat poisoning is a major issue since most prediction rules are inapplicable if the exact ingestion time cannot be determined and/or the serum paraquat concentration is not readily available, as in most countries. Therefore, we aimed to develop and validate a new prediction rule not requiring these two parameters.

METHODS

We designed a 10-year observational cohort study including all consecutive paraquat-poisoned patients managed in two Taiwanese hospitals. We built one cohort to define and one cohort to validate this prediction rule. Parameters independently related to mortality determined using a multivariate analysis were used to formulate the Acute Paraquat Poisoning Mortality (APPM) score.

RESULTS

Overall, 321 paraquat-poisoned patients were included, 156 in the derivation and 165 in the validation cohort. Mortality rates in the derivation and validation cohorts were 73% and 81%, respectively (p = 0.20). The three parameters chosen of 28-day mortality at presentation were urine paraquat level >10 ppm (using a colorimetric sodium dithionite-based test; odds ratio (OR), 12.70; 95% confidence interval (CI), 2.64-61.24), white blood cells >13.0 G/L (OR, 5.50; CI, 1.41-21.48) and blood glucose >140 mg/dL [7.8 mmol/L] (OR, 7.45; CI, 1.70-32.86). In the derivation cohort, the area under the ROC curve (AUC-ROC) of the APPM score did not significantly differ from AUC-ROCs of serum paraquat (0.95, p = 0.25) and the Severity Index of Paraquat Poisoning (0.95, p = 0.33). AUC-ROCs of the APPM score in the derivation and validation cohorts were 0.91 and 0.94, respectively.

CONCLUSION

We built and validated a reliable score to predict 28-day mortality in paraquat-poisoned patients at presentation, independently from the ingestion time and serum paraquat measurement.

A novel flowchart to predict mortality and analyse effectiveness of routinely used pharmacological regimens in paraquat poisoning

Paraquat is responsible for an extremely high case-fatality rate poisoning. Mortality prediction remains a major issue since evidence to support benefits of routinely used treatments is lacking. We aimed to develop an easy-to-use prediction flowchart not requiring the ingestion time, for which accuracy is frequently questionable, and to evaluate the effectiveness of routinely used pharmacological therapies on mortality. We designed a two-centre cohort study including consecutive paraquat-poisoned adults with confirmed diagnosis based on serum/urine paraquat measurement. We built a flowchart using a multivariate analysis of death predictors and analysed the outcome according to the administered therapies. Overall, 256 patients were enrolled. Mortality rate was 75%. Independent death predictors on admission were serum creatinine (odds ratio [OR], 5.07; 95% confidence interval [CI], 1.97-13.05) and serum paraquat concentration (OR, 2.26; CI, 1.66-3.09). The area-under-the flowchart curve was 0.91. Overall sensitivity and specificity were 81.5% and 94.8%, respectively. More survivors than non-survivors of severe poisoning received methylprednisolone (P = 0.04). While not significantly differing in severity, methylprednisolone-treated patients had better survival (P = 0.04). To conclude, we defined an efficient flowchart to predict mortality in paraquat poisoning at presentation, even if ingestion time is undetermined. Methylprednisolone seems effective to improve the outcome, especially in the most severe cases.

Development and Validation of a Radiomics Nomogram for Prognosis Prediction of Patients with Acute Paraquat Poisoning: A Retrospective Cohort Study

Objective

To evaluate the efficiency of a radiomics model in predicting the prognosis of patients with acute paraquat poisoning (APP).

Materials and Methods

Chest computed tomography images and clinical data of 80 patients with APP were obtained from November 2014 to October 2017, which were randomly assigned to a primary group and a validation group by a ratio of 7 : 3, and then the radiomics features were extracted from the whole lung. Principal component analysis (PCA) and least absolute shrinkage and selection operator (LASSO) regression were used to select the features and establish the radiomics signature (Rad-score). Multivariate logistic regression analysis was used to establish a radiomics prediction model incorporating the Rad-score and clinical risk factors; the model was represented by nomogram. The performance of the nomogram was confirmed by its discrimination and calibration.

Result

The area under the ROC curve of operation was 0.942 and 0.865, respectively, in the primary and validation datasets. The sensitivity and specificity were 0.864 and 0.914 and 0.778 and 0.929, and the prediction accuracy rates were 89.5% and 87%, respectively. Predictors included in the individualized predictive nomograms include the Rad-score, blood paraquat concentration, creatine kinase, and serum creatinine. The AUC of the nomogram was 0.973 and 0.944 in the primary and validation datasets, and the sensitivity and specificity were 0.943 and 0.955, respectively, in the primary dataset and 0.889 and 0.929 in the validation dataset, and the prediction accuracy was 94.7% and 91.3%, respectively.

Conclusion

The radiomics nomogram incorporates the radiomics signature and hematological laboratory data, which can be conveniently used to facilitate the individualized prediction of the prognosis of APP patients.

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

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.

A retrospective analysis of leucocyte count as a strong predictor of survival for patients with acute paraquat poisoning

The aim of this study is the identification of a reliable predictor of prognosis to optimize the treatment of acute paraquat (PQ) poisoning patients. We performed a retrospective analysis on 96 patients with acute PQ poisoning to evaluate leucocyte count as a predictor of 90-day survival. These patients were admitted to the emergency department from May 2012 to February 2017. Kaplan–Meier method was used to compare the 90-day survival. Cox proportional hazard models were utilized to estimate the hazard ratios (HR) and 95% confidence intervals (CI). Receiver operating characteristic (ROC) analysis was conducted to analyze the discriminatory potential of leucocyte with respect to 90-day survival. Result showed that leucocyte was significantly higher among nonsurvivors than that among survivors (p<0.001). Leukocyte was also an independent predictor of survival according to the multivariate Cox analysis (HR 1.103; 95%CI: 1.062–1.146; p<0.001). The area under the curve (AUC) for leucocyte (AUC 0.911; 95%CI: 0.855–0.966; p<0.001) showed a discriminatory potential similar to that of the plasma PQ concentration (AUC 0.961; 95%CI: 0.926–0.997; p<0.001) in predicting 90-day survival. The leucocyte count is a strong predictor of survival in patients with acute PQ poisoning.

The value of APACHE II in predicting mortality after paraquat poisoning in Chinese and Korean population: A systematic review and meta-analysis

BACKGROUND

The Acute Physiology and Chronic Health Evaluation II (APACHE II) score is used to determine disease severity and predict outcomes in critically ill patients. However, the prognostic significance of APACHE after acute paraquat (PQ) poisoning remains unclear. The meta-analysis was aimed to study the value of APACHE II in predicting mortality in PQ-exposed Chinese and Korean patients.

METHODS

Databases that included PubMed, Embase, Cochrane Library, and the Chinese National Knowledge Infrastructure were searched through August 2016. Studies using APACHE II to predict mortality in PQ-poisoned patients were selected. The odds ratio and weighted mean difference (WMD) were used to pool binary and continuous data. Additionally, we aggregated sensitivity, specificity, and other measures of accuracy. Statistical analyses were made using the Stata V.13.0 software.

RESULTS

This study included 29 studies, and 25 studies evaluated APACHE II scores on admission. Pooled data showed that survivors had significantly lower total scores than nonsurvivors (WMD = -7.29, and I = 98.2%, both P <.05). The pooled sensitivity of an APACHE II score ≥5 for predicting mortality was 75% and the pooled specificity was 86%. The positive likelihood ratio (PLR) was 5.3 and the negative likelihood ratio (NLR) was 0.29. The pooled sensitivity of an APACHE II score ≥10 for predicting mortality was 88% and the pooled specificity was 84%. The pooled PLR and NLR was 5.5 and 0.15, respectively.

CONCLUSION

This study showed PQ-poisoned nonsurvivors had significantly higher APACHE II score than did survivors. APACHE II scores satisfactorily predicted mortality.