急診醫師決定血液培養之病患應用降鈣素原之菌血症預測模式

Abstract

前言：菌血症是急診最嚴重的感染症之一。在沒有給予或使用不適當之經驗性抗生素治療的情況下，可能導致菌血症病患有較差的預後。因此，如何及時辨識出菌血症之可能病患，對於急診醫師來說是一個極大的挑戰。得到血液培養的結果通常需要一兩天的時間，因此急診醫師需要一個可依賴的預測工具，以幫助他們減少不必要的血液培養，並及早偵測到菌血症之高危險病患，以避免菌血症帶來的可能後果。雖然過去已有許多關於菌血症預測模式的研究，但仍未有臨床預測模式使用新的預測工具－降鈣素原。 目的：本研究之研究目標在建構一個使用降鈣素原的菌血症臨床預測模式，幫助急診醫師及早辨識出菌血症高危險病患，以避免延遲使用適當之抗微生物治療，並期能減少急診不必要之血液培養。 材料與方法：自民國九十三年十月一日至十一月三十日期間，於台灣大學醫學院附設醫院急診醫學部前瞻性收集之急診病患族群作分析。於此研究期間，所有15歲以上急診成人病患，經由醫師判斷需施行血液培養者為收錄對象。排除15歲以下孩童、懷孕婦女、以及甲狀腺癌患者。收集之資料包含五大類：(1)病患背景資料；(2)易感因子：如先前疾病、侵襲性程序、及免疫抑制治療等；(3)臨床表現：如症狀、生命徵候等；(4)實驗室檢查結果；以及(5)急診醫師之初步診斷。主要結果為真性菌血症，其定義遵循美國疾病管制局(CDC)臨床指引及MacGregor及Beaty等人之研究。為盡量避免因為模式選擇的標準，而遺漏在其他有意義之因子存在下，可能失去統計差異之陰性干擾因子(negative confounding factors)，吾人應用一個繁複之邏輯回歸 (logistic regression) 過程建立一預測模式。其後使用參考變項係數之整數化給分法(coefficient-based scoring method)，將此臨床預測模式簡化為評分系統預測模式。 結果：共收錄558位病患，其中含84次的真性菌血症事件。經邏輯回歸求得之危險因子及其簡化後之預測模式給分分別為：(1)肝硬化：勝算比0.255(95%信賴區間0.076至0.851)，計-2分；(2)發燒＞38.3℃：勝算比2.94(95%信賴區間1.537至5.625)，計2分；(3)心跳＞120下/分：勝算比3.113(95%信賴區間1.618至5.990)，計2分；(4)淋巴球＜0.5×103/μL：勝算比4.241(95%信賴區間2.144至8.391)，計2分；(5)天門冬胺酸轉胺酶＞40 IU/L：勝算比3.216(95% 信賴區間1.695至6.100)，計2分；(6)C-反應蛋白(CRP)＞10 mg/dL：勝算比1.722(95%信賴區間0.849至3.492)，計1分；(7)降鈣素原(PCT)＞0.5 ng/mL：勝算比3.837(95%信賴區間1.951至7.549)，計2分；以及(8)急診醫師初步診斷為呼吸道感染：勝算比0.205(95% 信賴區間0.077至0.543)，計-3分。Hosmer-Lemeshow測試之整體模式適配度卡方值為8.5813(P=0.3788)，顯示本預測模式有良好之整體模式適配度。原始邏輯回歸模式與簡化後之計分模式之使用者操作特徵曲線圖曲線下面積分別為0.861(95%信賴區間0.825至0.892)及0.859(95%信賴區間0.823至0.890)，兩條曲線相當接近。以1,000次連續隨機抽樣其中一半的資料做模式訓練、另一半作效度確認，交叉效度測試之使用者操作特徵曲線圖曲線下面積下降至0.664 (95%信賴區間0.593至0.734)，其95%信賴區間下限仍在0.50以上。 結論：本研究以台灣本土急診病患為對象，找出菌血症所有相關之危險因子，並據此邏輯回歸預測模式發展出一個簡化之評分預測模式。此預測模式在本研究族群中效度良好，其外推性仍有待其他研究之驗證。

Background: Bloodstream infection or bacteremia is one of the most serious infectious diseases in emergency department (ED). Inappropriate or lacking of empirical antimicrobial therapy may be associated with a poorer outcome in bacteremic patients. How to identify patients with bacteremia timely becomes a great challenge for an emergency physician. A reliable predictive tool for bacteremia is needed to help emergency physicians in reducing the amount of unnecessary blood cultures, and in detecting high risk patients to avoid the sequale as a result of bacteremia. Despite numerous studies on predictive models for bacteremia, there was short of Procalcitonin-incorporated predictive model. Objectives: The objectives of this study are therefore to build up a predictive model for the risk of bacteremia to aid emergency physicians in identifying the high-risk patients earlier in order to reduce the chance of delaying appropriate antimicrobial therapy, and in reducing the unnecessary blood cultures collected at ED. Material and Methods: We conducted a prospective cohort study at the ED of National Taiwan University Hospital (NTUH) from October 1, 2004 to November 30, 2004. All adult patients aged 15 years or older who had at least two sets of blood cultures collected during the study period were recruited. Factors affecting the risk for bacteremia included five categories: demographic characteristics; predisposing conditions such as underlying diseases, invasive procedures, immunosuppressive therapies; clinical presentations; laboratory tests; and presumptive diagnosis by emergency physicians. The primary outcome was true bacteremia adapted from definitions of the Centers for Disease Control and Prevention (CDC) and MacGregor and Beaty guidelines. To minimize all the possible negative confounding factors that are insignificant in the presence of other significant factors based on model selection criteria, we adopted an iterative procedure to build up a predictive model not to miss the possible negative confounding factors, and then simplified the clinical prediction rule into a coefficient-based scoring system. Results: We enrolled 558 patients with 84 episodes of true bacteremia. Predictors identified for bacteremia and their assigned scores were: (1) liver cirrhosis (adjusted odds ratio [aOR] 0.255; 95% confidence interval [CI] 0.076 to 0.851), -2 point; (2)fever＞38.3℃ (aOR 2.94; 95% CI, 1.537 to 5.625), 2 point ; (3) tachycardia (aOR 3.113; 95% CI, 1.618 to 5.990), 2 point; (4) lymphocytopenia (aOR 4.241; 95% CI, 2.144 to 8.391), 2 points; (5) AST＞40 IU/L (aOR 3.216; 95% CI, 1.695 to 6.100), 2 point; (6) C-reactive protein (CRP)＞10 mg/dL (aOR 1.722; 95% CI, 0.849 to 3.492), 1 point; (7) procalcitonin (PCT)＞0.5 ng/mL (aOR 3.837; 95% CI, 1.951to 7.549), 2 points; and (8) presumptive diagnosis of respiratory tract infections (aOR 0.205; 95% CI, 0.077 to 0.543), -3 points. The Hosmer-Lemeshow test revealed a goodness-of-fit of 8.5813 (P=0.3788). The areas under receiver operating characteristic curves (AUC) of original logistic model and the simplified scoring model were 0.861 (95% CI, 0.825 to 0.892) and 0.859 (95% CI, 0.823 to 0.890), respectively. Cross validation with 1,000 bootstraps of half cases for model training and another half for validation revealed a reduction of AUC to 0.664 (95% CI, 0.593 to 0.734). Conclusion: We developed a predictive model with scoring system for bacteremia at ED by application of the risk factors associated with bacteremia. However, its generalizabilty needs further corroboration.