BACKGROUND The Gompertz-Makeham law describes a characteristic pattern of mortality in human populations where the death rate is near constant between ages 18 and 30 yr (Makeham law) and rises exponentially thereafter (Gompertz law). This pattern has not been described in surgical populations, but if true, it would have important implications for understanding surgical risk and design and interpretation of surgical risk models. The aim of this study was to determine whether the Gompertz-Makeham law applies to perioperative mortality risk and the conditions under which it may apply. METHODS This study examined the relationship between age and 1-month postoperative all-cause mortality risk in a 10-yr New Zealand administrative dataset comprising 5,615,100 surgical procedures from 2007 to 2016. The dataset includes patient and surgical factors including procedures, American Society of Anesthesiologists (ASA; Schaumburg, Illinois) Physical Status score, diagnoses, and other relevant details. Semilogarithmic graphs of mortality risk and age were plotted. Linear regression models were fitted, with regression line slope and Pearson correlation coefficient calculated. RESULTS The primary outcome occurred in 114,782 (2.0%) of 5,615,100 included participants. The Gompertz-Makeham law seems to apply to the national surgical population as a whole (slope = 0.0241; R2 = 0.971). The law applies in all subgroups studied including sex, ASA Physical Status, surgical acuity, surgical severity category, cancer status, and ethnicity (slopes, 0.0066 to 0.0307; R2, 0.771 to 0.990). Important interactions were found between age, mortality risk, and three high-risk groups (cancer diagnosis, ASA Physical Status IV to V, and high surgical severity). CONCLUSIONS The Gompertz-Makeham law seems to apply in a national cohort of surgical patients. The inflection point for increased 1-month risk is apparent at age 30 yr. A strict exponential rise in mortality risk occurs thereafter. This finding improves the understanding of surgical risk and suggests a concept-driven approach to improve modeling of age and important interactions in future surgical risk models. EDITOR’S PERSPECTIVE

中文翻译：

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应用于手术死亡率建模的人类衰老生物人口学 （Gompertz-Makeham Law）：一项回顾性全国队列研究。


背景 Gompertz-Makeham 定律描述了人类人群中一种典型的死亡率模式，其中死亡率在 18 至 30 岁之间几乎保持不变（Makeham 定律），此后呈指数级上升（Gompertz 定律）。这种模式尚未在手术人群中描述，但如果属实，它将对理解手术风险以及手术风险模型的设计和解释具有重要意义。本研究的目的是确定 Gompertz-Makeham 定律是否适用于围手术期死亡风险及其可能适用的条件。方法 本研究在一个为期 10 年的新西兰行政数据集中检查了年龄与术后 2016 个月全因死亡风险之间的关系，该数据集包括 2007 年至 2016 年的 5,615,100 例外科手术。该数据集包括患者和手术因素，包括手术、美国麻醉医师协会 （ASA;伊利诺伊州绍姆堡）身体状况评分、诊断和其他相关详细信息。绘制了死亡风险和年龄的半对数图。拟合线性回归模型，计算回归线斜率和 Pearson 相关系数。结果 主要结局发生在 5,615,100 名参与者中的 114,782 名 （2.0%）。Gompertz-Makeham 定律似乎适用于整个全国外科手术人群（斜率 = 0.0241;R2 = 0.971）。该法律适用于研究的所有亚组，包括性别、ASA 身体状况、手术敏锐度、手术严重程度类别、癌症状况和种族（斜率，0.0066 至 0.0307;R2,0.771 至 0.990）。发现年龄、死亡风险和 3 个高危组 （癌症诊断、ASA 身体状况 IV 至 V 和手术严重程度高） 之间存在重要交互作用。 结论 Gompertz-Makeham 定律似乎适用于全国手术患者队列。1 个月风险增加的拐点在 30 岁时很明显。此后死亡风险呈严格指数级上升。这一发现提高了对手术风险的理解，并提出了一种概念驱动的方法来改进未来手术风险模型中的年龄和重要相互作用的建模。编辑观点