背景:类鼻窦炎,一种由假伯克霍尔德菌引起的疾病,在流行的热带地区对健康构成重大威胁。尽管有有效的治疗方法,死亡率仍然显著升高。许多危险因素与死亡率相关。这项研究旨在开发一种评分系统,用于使用易于获得的临床数据来预测由于类骨病导致的院内死亡率。
方法:数据来自苏林医院,苏林,泰国,2014年4月至2017年3月期间。我们纳入了年龄在15岁及以上的患者,这些患者的培养物对假伯克霍尔德菌呈阳性。临床预测规则是使用多变量分析中的重要危险因素制定的。
结果:本研究共纳入282例类鼻窦炎患者。在最终的分析模型中,251例患者被用于确定院内致命性类骨病的重要危险因素。确定了五个因素,并用于制定临床预测规则,影响因素如下:qSOFA≥2(比值比[OR]=2.39,p=0.025),胸部X线检查异常(OR=5.86,p<0.001),肌酐≥1.5mg/dL(OR=2.80,p=0.004),谷草转氨酶≥50U/L(OR=4.032,p<0.001),碳酸氢盐≤20mEq/L(OR=2.96,p=0.002)。预测分数在0到7之间。与低风险组(得分0-3)相比,得分高(4-7)的患者的死亡率显着升高,超过65.0%(似然比[LR]2.18,p<0.001),死亡率较低(LR0.18,p<0.001)。接收器工作特征曲线下面积(AUC)为0.84,表明良好的模型性能。
结论:这项研究提出了一个简单的评分系统,该系统基于容易获得的临床参数来预测类鼻虫病患者的院内死亡率。该工具可能有助于早期识别可能从更积极的治疗策略中受益的高风险患者。有可能改善临床决策和患者预后。
BACKGROUND: Melioidosis, a disease induced by Burkholderia pseudomallei, poses a significant health threat in tropical areas where it is endemic. Despite the availability of effective treatments, mortality rates remain notably elevated. Many risk factors are associated with mortality. This study aims to develop a scoring system for predicting the in-hospital mortality from
melioidosis using readily available clinical data.
METHODS: The data were collected from Surin Hospital, Surin, Thailand, during the period from April 2014 to March 2017. We included patients aged 15 years and above who had cultures that tested positive for Burkholderia pseudomallei. The clinical prediction rules were developed using significant risk factors from the multivariable analysis.
RESULTS: A total of 282 patients with
melioidosis were included in this study. In the final analysis model, 251 patients were used for identifying the significant risk factors of in-hospital fatal
melioidosis. Five factors were identified and used for developing the clinical prediction rules, and the factors were as follows: qSOFA ≥ 2 (odds ratio [OR] = 2.39, p= 0.025), abnormal chest X-ray findings (OR = 5.86, p < 0.001), creatinine ≥ 1.5 mg/dL (OR = 2.80, p = 0.004), aspartate aminotransferase ≥50 U/L (OR = 4.032, p < 0.001), and bicarbonate ≤ 20 mEq/L (OR = 2.96, p = 0.002). The prediction scores ranged from 0 to 7. Patients with high scores (4-7) exhibited a significantly elevated mortality rate exceeding 65.0% (likelihood ratio [LR+] 2.18, p < 0.001) compared to the low-risk group (scores 0-3) with a lower mortality rate (LR + 0.18, p < 0.001). The area under the receiver operating characteristic curve (AUC) was 0.84, indicating good model performance.
CONCLUSIONS: This study presents a simple scoring system based on easily obtainable clinical parameters to predict in-hospital mortality in
melioidosis patients. This tool may facilitate the early identification of high-risk patients who could benefit from more aggressive treatment strategies, potentially improving clinical decision-making and patient outcomes.