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作 者:刘霖敏[1] 陈金良[1] 徐慧芳[2] 洪广亮[3] 卢中秋[3]
机构地区:[1]浙江省台州市立医院急诊科,浙江台州318000 [2]浙江省台州市中心医院胸外科,浙江台州318000 [3]温州医科大学附属第一医院急诊医学中心,浙江温州325000
出 处:《中国现代医生》2016年第13期1-4,共4页China Modern Doctor
基 金:浙江省自然科学基金项目(LY13H150006)
摘 要:目的探讨脓毒症患者血脂水平与其预后的关系。方法记录分析我院43例脓毒症患者的临床资料。按预后情况将患者分为死亡组和存活组,比较两组患者基线分布情况、血脂水平差异,应用ROC曲线分析血脂水平在预测脓毒症患者预后中的价值,并分析血脂水平与疾病严重程度的关系。结果死亡组HDL-C[(0.95±0.04)mmol/L vs(1.19±0.07)mmol/L]和LDL-C[(1.52±0.26)mmol/L vs(2.49±0.33)mmol/L]水平低于存活组,TC[(3.48±0.64)mmol/L vs(2.62±0.47)mmol/L]水平高于存活组,差异具有统计学意义(P<0.05)。HDL-C预测脓毒症死亡风险AUC为0.994,95%CI(0.878,0.957);LDL-C预测脓毒症死亡风险AUC为0.991,95%CI为(0.856,0.943)。TC、HDL-C和LDL-C与APACHEⅡ评分和24 h内SOFA评分最大值存在明显相关性(P<0.05)。结论脓毒症患者TC、HDL-C、LDL水平与疾病的严重程度呈一定的相关性,TC、HDL-C、LDL-C水平可作为预测脓毒症预后的良好指标。Objective To investigate the value of serum lipid levels for predicting of clinicaloutcomes in patients with sepsis. Methods The clinical date of 43 patients withsepsiswerecollected. All patients were divided to survivor group and non-survivor group. The serum lipid levels were compared. The receiver operator characteristic curve was produced for predicting the hospital motility. To determine the discriminative power of the serum lipid for survival, constructed ROC curves and calculated areas under the curve with 95%CI. The relationship was evaluated by correlation analysis between serum lipid levels and severity of disease. Results The HDL-C[(0.95±0.04)mmol/L vs (1.19±0.07)mmol/L] and LDL-C[(1.52±0.26)mmol/L vs (2.49±0.33)mmol/L] levels in non-survivor group were significantly lower than that in survivor group, but the TC level [(3.48±0.64)mmol/L vs (2.62±0.47)mmol/L] was significant higher, the differences were statistically significant (P〈0.05). The AUCs for predicting hospital motility were 0.994 (95%CI 0.878, 0.957) for the HDL-C and 0.991(95%CI 0.856, 0.943) for the LDL-C. The TC, HDL-C and LDL-C was correlated significantly with the first 24 h SOFA max score and APACHE Ⅱ score(P〈0.05). Conclusion The serum TC, HDL-C and LDL-C levels is related to the severity of disease, and exhibited discriminative power for prediction of mortality in patients with sepsis.
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