Kudo Masataka, Takada Toshihiko, Fujii Kotaro, Sasaki Sho, Yagi Yu, Yano Tetsuhiro, Tsuchido Yasuhiro, Ito Hideyuki, Sada Ken-Ei, Fukuhara Shunichi
Department of General Internal Medicine, Iizuka Hospital, Fukuoka, Japan.
Department of Clinical Epidemiology, Kochi Medical School, Nankoku, Japan.
J Gen Intern Med. 2025 Mar;40(4):796-802. doi: 10.1007/s11606-024-09291-8. Epub 2024 Dec 20.
Detailed grading of chills is more useful for diagnosing bacteremia than simply classifying the presence or absence of chills. However, its value added to other clinical information has not been evaluated.
To evaluate the value of adding chills grading to other clinical information compared to simply noting the presence or absence of chills for predicting bacteremia in patients with suspected infection.
Prospective observational study.
Adult patients admitted to two acute-care hospitals with suspected infection from April 2018 to March 2019.
Two types of categorization for chills were applied: "presence" or "absence" (dichotomized chills); and "no chills", "mild/moderate chills", and "shaking chills" (trichotomized chills). Three multivariable logistic regression models incorporating each of dichotomized chills, trichotomized chills, and C-reactive protein (CRP) with other clinical information were developed and compared. To assess the potential consequences of using each model to identify patients with high risk of bacteremia (i.e., requiring prompt intervention), we applied a cut-off point of an estimated probability of 60%. The number of patients with bacteremia correctly identified by each model was compared.
Among the 2,013 patients, 327 (16.2%) were diagnosed with bacteremia. The three models showed comparable discrimination and calibration performance. At the 60% cut-off, the dichotomized chills model correctly identified 11 patients (3.4% [95% confidence interval (CI) 1.9-3.4] of patients with bacteremia). The trichotomized chills model and CRP model correctly identified an additional 15 patients (4.6% [95% CI 2.8-7.4]) and 2 patients (0.6% [95% CI 0.1-2.3]) with bacteremia, respectively.
Differentiating shaking chills in comparison with dichotomized chills for predicting bacteremia allowed the correct identification of an additional 4.6% of patients with bacteremia. Detailed grading of chills can be assessed without additional time, cost, or burden on patients and can be recommended in the routine history taking.
寒战的详细分级对于菌血症的诊断比单纯区分有无寒战更有用。然而，其相对于其他临床信息的附加价值尚未得到评估。
评估与仅记录有无寒战相比，将寒战分级添加到其他临床信息中对预测疑似感染患者菌血症的价值。
前瞻性观察性研究。
2018年4月至2019年3月入住两家急症医院的疑似感染成年患者。
应用两种寒战分类方法：“有”或“无”（二分法寒战）；以及“无寒战”、“轻度/中度寒战”和“寒战”（三分法寒战）。建立并比较了三个多变量逻辑回归模型，分别纳入二分法寒战、三分法寒战和C反应蛋白（CRP）以及其他临床信息。为了评估使用每个模型识别菌血症高危患者（即需要及时干预）的潜在后果，我们应用了估计概率为60%的截断点。比较每个模型正确识别的菌血症患者数量。
在2013例患者中，327例（16.2%）被诊断为菌血症。这三个模型显示出相当的区分度和校准性能。在60%的截断点，二分法寒战模型正确识别了11例菌血症患者（占菌血症患者的3.4%[95%置信区间（CI）1.9 - 3.4]）。三分法寒战模型和CRP模型分别正确识别了另外15例（4.6%[95%CI 2.8 - 7.4]）和2例（0.6%[95%CI 0.1 - 2.3]）菌血症患者。
与二分法寒战相比，区分寒战对预测菌血症可使另外4.
