From the Faculty of Health Studies, University of Bradford, Bradford, UK.
Bradford Teaching Hospitals NHS Foundation Trust Bradford Institute for Health Research, Bradford, UK.
QJM. 2017 Jan;110(1):27-31. doi: 10.1093/qjmed/hcw110. Epub 2016 Aug 2.
The Biochemistry and Haematology Outcome Model (BHOM) relies on the results from routine index blood tests to predict the patient risk of death. We aimed to externally validate the BHOM model.
We considered all emergency adult medical patients who were discharged from Northern Lincolnshire and Goole (NLAG) hospital in 2014. We compared patient characteristics between NLAG (the validation sample) and the hospital where BHOM was developed. We evaluated the predictive performance, according to discriminative ability (with a concordance statistic, c), and calibration (agreement between observed and predicted risk).
There were 29 834 emergency discharges of which 24 696 (83%) had complete data. In comparison with the development sample, the NLAG sample was similar in age, blood test results, but experienced a lower mortality (4.7 vs. 8.7%). When applied to NLAG, the BHOM model had good discrimination (c-statistic 0.83 [95% CI 0.823-0.842]). Calibration was good overall, although the BHOM model overpredicted for lowest (<5%, observed = 229, predicted = 286) and highest (≥50%, observed = 31, predicted = 49) risk groups, even after recalibrating for the differences in baseline risk of death.
Differences in patient case-mix profile and baseline risk of death need to be considered before the BHOM model can be used in another hospital. After re-calibrating for the baseline difference in risk the BHOM model had good discrimination but less adequate calibration.
生物化学和血液学结局模型(BHOM)依赖于常规指标血液检测结果来预测患者死亡风险。我们旨在对 BHOM 模型进行外部验证。
我们考虑了 2014 年从北林肯郡和古尔(NLAG)医院出院的所有成年急诊内科患者。我们比较了 NLAG 医院(验证样本)与 BHOM 开发医院之间的患者特征。我们根据判别能力(一致性统计量 c)和校准(观察风险与预测风险之间的一致性)来评估预测性能。
共有 29834 例急诊出院患者,其中 24696 例(83%)有完整的数据。与开发样本相比,NLAG 样本在年龄、血液检测结果方面相似,但死亡率较低(4.7%比 8.7%)。当应用于 NLAG 时,BHOM 模型具有良好的判别能力(c 统计量 0.83[95%CI 0.823-0.842])。整体校准情况良好,但 BHOM 模型对最低(<5%,观察值=229,预测值=286)和最高(≥50%,观察值=31,预测值=49)风险组的预测值过高,即使在校准了死亡率的基线差异后也是如此。
在 BHOM 模型可用于另一家医院之前,需要考虑患者病例组合特征和死亡率的基线差异。在校准了死亡率的基线差异后,BHOM 模型具有良好的判别能力,但校准效果较差。