Prediction of outcome after paraquat poisoning by measurement of the plasma paraquat concentration.
Prediction of outcome after paraquat poisoning by measurement of the plasma paraquat concentration.
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DOI：
10.1093/qjmed/hcp006
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发表时间：
2009-04
期刊：
影响因子：
--
通讯作者：
Buckley NA
中科院分区：
文献类型：
--
作者：
Senarathna L;Eddleston M;Wilks MF;Woollen BH;Tomenson JA;Roberts DM;Buckley NA
背景资料：百草枯是一种具有良好职业安全记录的除草剂，但在有意摄入后死亡率很高，已证明难以治疗。近三十年来，百草枯浓度-时间数据一直用于预测摄入后的结果。然而，没有一种已发表的方法得到独立或前瞻性验证。我们的目的是使用前瞻性收集的数据来测试已发表的预测方法，并确定是否有任何上级。研究方法：作为大型前瞻性队列研究的一部分，对斯里兰卡10家医院的451名患者入院时的血浆百草枯浓度进行了测量。记录所有住院死亡; 3个月后随访存活至出院的患者，以检测延迟死亡。然后在所有符合条件的患者中评估了基于百草枯浓度-时间数据的五种预测方法。结果：所有方法在其应用范围内表现出相当的性能。例如，Sawada和Proudfoot方法对4- 24小时预后的预测差异最大，但这些差异相对较小[特异性0.96（95% CI：0.90-0.99）与0.89（0.82-0.95）;灵敏度0.57对0.79，阳性和阴性似然比分别为14.8对7.40和0.44对0.23，阳性预测值分别为0.96对0.92]。结论：所有五种已发表的方法在预测死亡方面都优于预测生存。这些预测也可以作为工具来识别需要治疗的患者，并对在没有对照组的情况下进行试验的新疗法进行评估。
Background: Paraquat is a herbicide with a good occupational safety record, but a high mortality after intentional ingestion that has proved refractory to treatment. For nearly three decades paraquat concentration–time data have been used to predict the outcome following ingestion. However, none of the published methods has been independently or prospectively validated. We aimed to use prospectively collected data to test the published predictive methods and to determine if any is superior. Methods: Plasma paraquat concentrations were measured on admission for 451 patients in 10 hospitals in Sri Lanka as part of large prospective cohort study. All deaths in hospital were recorded; patients surviving to hospital discharge were followed up after 3 months to detect delayed deaths. Five prediction methods that are based on paraquat concentration–time data were then evaluated in all eligible patients. Results: All methods showed comparable performance within their range of application. For example, between 4- and 24-h prediction of prognosis was most variable between Sawada and Proudfoot methods but these differences were relatively small [specificity 0.96 (95% CI: 0.90–0.99) vs. 0.89 (0.82–0.95); sensitivity 0.57 vs. 0.79, positive and negative likelihood ratios 14.8 vs. 7.40 and 0.44 vs. 0.23 and positive predictive values 0.96 vs. 0.92, respectively]. Conclusions: All five published methods were better at predicting death than survival. These predictions may also serve as tools to identify patients who need treatment and for some assessment to be made of new treatments that are trialled without a control group.
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通过免疫抑制药物治疗帕拉奎特诱导的肺纤维化的前景，并且需要更好地预测结果：系统评价。
DOI：
10.1093/qjmed/hcg137
发表时间：
2003-11
期刊：
QJM : monthly journal of the Association of Physicians
影响因子：
--
作者：
Eddleston M;Wilks MF;Buckley NA
通讯作者：
Buckley NA
影响因子：
168.9
作者：
Eddleston, Michael;Juszczak, Edmund;Buckley, Nick A.;Senarathna, Lalith;Mohamed, Fahim;Dissanayake, Wasantha;Hittarage, Ariyasena;Azher, Shifa;Jeganathan, K.;Jayamanne, Shaluka;Sheriff, M. H. Rezvi;Warrell, David A.
通讯作者：
Warrell, David A.
影响因子：
3.3
作者：
Gil, Hyo-Wook;Kang, Mun-Soo;Hong, Sae-Yong
通讯作者：
Hong, Sae-Yong
影响因子：
4.5
作者：
Heylings, J. R.;Farnworth, M. J.;Elliott, B. M.
通讯作者：
Elliott, B. M.
影响因子：
3.3
作者：
Eddleston, Michael;Haggalla, Sapumal;Buckley, Nick A.
通讯作者：
Buckley, Nick A.