Klompas Michael, Kleinman Ken, Platt Richard
Department of Ambulatory Care and Prevention, Harvard Medical School, Boston, Massachusetts, USA.
Infect Control Hosp Epidemiol. 2008 Jan;29(1):31-7. doi: 10.1086/524332.
Surveillance for ventilator-associated pneumonia (VAP) using standard Centers for Disease Control and Prevention (CDC) criteria is labor intensive and involves many subjective assessments. We sought to improve the efficiency and objectivity of VAP surveillance by adapting the CDC criteria to make them amenable to evaluation with electronic data.
Prospective comparison of the accuracy of VAP surveillance by use of an algorithm with responses to prospective queries made to intensive care physicians. CDC criteria for VAP were used as a reference standard to evaluate the algorithm and clinicians' reports.
Three surgical intensive care units and 2 medical intensive care units at an academic hospital.
A total of 459 consecutive patients who received mechanical ventilation for a total of 2,540 days underwent surveillance by both methods during consecutive 3-month periods. Electronic surveillance criteria were chosen to mirror the CDC definition. Quantitative thresholds were substituted for qualitative criteria. Purely subjective criteria were eliminated. Increases in ventilator-control settings were taken to indicate worsening oxygenation. Semiquantitative Gram stain of pulmonary secretion samples was used to assess whether there was sputum purulence.
The algorithm applied to electronic data detected 20 patients with possible VAP. All cases of VAP were confirmed in accordance with standard CDC criteria (100% positive predictive value). Prospective survey of clinicians detected 33 patients with possible VAP. Seventeen of the 33 possible cases were confirmed (52% positive predictive value). Overall, 21 cases of confirmed VAP were identified by either method. The algorithm identified 20 (95%) of 21 known cases, whereas the survey of clinicians identified 17 (81%) of 21 cases.
Surveillance for VAP using electronic data is feasible and has high positive predictive value for cases that meet CDC criteria. Further validation of this method is warranted.
使用美国疾病控制与预防中心（CDC）的标准监测呼吸机相关性肺炎（VAP）需要耗费大量人力，且涉及许多主观评估。我们试图通过调整CDC标准，使其适合利用电子数据进行评估，以提高VAP监测的效率和客观性。
采用一种算法对VAP监测的准确性与向重症监护医师进行的前瞻性询问的回答进行前瞻性比较。以CDC的VAP标准作为参考标准来评估该算法和临床医生的报告。
一所学术医院的3个外科重症监护病房和2个内科重症监护病房。
在连续的3个月期间，共有459例接受机械通气总计2540天的连续患者接受了两种方法的监测。选择电子监测标准以反映CDC的定义。用定量阈值替代定性标准，消除了纯粹主观的标准。呼吸机控制设置的增加被视为氧合恶化的指标。使用肺分泌物样本的半定量革兰氏染色来评估痰液是否有脓性。
应用于电子数据的算法检测出20例可能患有VAP的患者。所有VAP病例均符合CDC标准得到确诊（阳性预测值为100%）。对临床医生的前瞻性调查检测出33例可能患有VAP的患者。33例可能病例中有17例得到确诊（阳性预测值为52%）。总体而言，两种方法共识别出21例确诊的VAP病例。该算法识别出了21例已知病例中的20例（95%），而对临床医生的调查识别出了21例中的17例（81%）。
利用电子数据监测VAP是可行的，对于符合CDC标准的病例具有较高的阳性预测值。有必要对该方法进行进一步验证。
