Rocktaeschel Jens, Morimatsu Hiroshi, Uchino Shigehiko, Bellomo Rinaldo
Department of Intensive Care, Austin and Repatriation Medical Centre, Melbourne, Australia.
Crit Care Med. 2003 Aug;31(8):2131-6. doi: 10.1097/01.CCM.0000079819.27515.8E.
To determine whether base excess, base excess caused by unmeasured anions, and anion gap can predict lactate in adult critically ill patients, and also to determine whether acid-base variables can predict mortality in these patients.
Retrospective study.
Adult intensive care unit of tertiary hospital.
Three hundred adult critically ill patients admitted to the intensive care unit.
Retrieval of admission biochemical data from computerized records, quantitative biophysical analysis of data with the Stewart-Figge methodology, and statistical analysis.
We measured plasma Na+, K+, Mg2+, Cl-, HCO3-, phosphate, ionized Ca2+, albumin, lactate, and arterial pH and Paco2. All three variables (base excess, base excess caused by unmeasured anions, anion gap) were significantly correlated with lactate (r2 =.21, p <.0001; r2 =.30, p <.0001; and r2 =.31. p <.0001, respectively). Logistic regression analysis showed that the area under the receiver operating characteristic (AUROC) curves had moderate to high accuracy for the prediction of a lactate concentration >5 mmol/L: AUROC curves, 0.86 (95% confidence interval [CI], 0.78-0.94), 0.86 (95% CI, 0.78-0.93), and 0.85 (95% CI, 0.77-0.92), respectively. Logistic regression analysis showed that hospital mortality rate correlated significantly with Acute Physiology and Chronic Health Evaluation (APACHE) II score, anion gap corrected (anion gap corrected by albumin), age, lactate, anion gap, chloride, base excess caused by unmeasured anions, strong ion gap, sodium, bicarbonate, strong ion difference effective, and base excess. However, except for APACHE II score, AUROC curves for mortality prediction were relatively small: 0.78 (95% CI, 0.72-0.84) for APACHE II, 0.66 (95% CI, 0.59-0.73) for lactate, 0.64 (95% CI, 0.57-0.71) for base excess caused by unmeasured anions, and 0.63 (95% CI, 0.56-0.70) for strong ion gap.
Base excess, base excess caused by unmeasured anions, and anion gap are good predictors of hyperlactatemia (>5 mmol/L). Acid-base variables and, specifically, "unmeasured anions" (anion gap, anion gap corrected, base excess caused by unmeasured anions, strong ion gap), irrespective of the methods used to calculate them, are not accurate predictors of hospital mortality rate in critically ill patients.
确定碱剩余、未测定阴离子引起的碱剩余和阴离子间隙能否预测成年危重症患者的乳酸水平，同时确定酸碱变量能否预测这些患者的死亡率。
回顾性研究。
三级医院的成人重症监护病房。
300例入住重症监护病房的成年危重症患者。
从计算机记录中检索入院时的生化数据，采用Stewart-Figge方法对数据进行定量生物物理分析，并进行统计分析。
我们测定了血浆钠、钾、镁、氯、碳酸氢根、磷酸盐、离子钙、白蛋白、乳酸以及动脉血pH值和二氧化碳分压。所有三个变量（碱剩余、未测定阴离子引起的碱剩余、阴离子间隙）均与乳酸显著相关（r²分别为0.21，p<0.0001；r²为0.30，p<0.0001；r²为0.31，p<0.0001）。逻辑回归分析显示，受试者工作特征（AUROC）曲线下面积对于预测乳酸浓度>5 mmol/L具有中等至高的准确性：AUROC曲线分别为0.86（95%置信区间[CI]，0.78 - 0.94）、0.86（95%CI，0.78 - 0.93）和0.85（95%CI，0.77 - 0.92）。逻辑回归分析显示，医院死亡率与急性生理与慢性健康状况评价（APACHE）II评分、校正后的阴离子间隙（经白蛋白校正的阴离子间隙）、年龄、乳酸、阴离子间隙、氯、未测定阴离子引起的碱剩余、强离子间隙、钠、碳酸氢根、有效强离子差和碱剩余显著相关。然而，除APACHE II评分外，用于死亡率预测的AUROC曲线相对较小：APACHE II为0.78（95%CI，0.72 - 0.84），乳酸为0.66（95%CI，0.59 - 0.73），未测定阴离子引起的碱剩余为0.64（95%CI，0.57 - 0.71），强离子间隙为0.63（95%CI，0.56 - 0.70）。
碱剩余、未测定阴离子引起的碱剩余和阴离子间隙是高乳酸血症（>5 mmol/L）的良好预测指标。酸碱变量，特别是“未测定阴离子”（阴离子间隙、校正后的阴离子间隙、未测定阴离子引起的碱剩余、强离子间隙），无论用于计算它们的方法如何，都不是危重症患者医院死亡率的准确预测指标。
