Suppr超能文献

癌症患者脑血管病死亡的季节性模式

Seasonal Pattern of Cerebrovascular Fatalities in Cancer Patients.

作者信息

Shivarov Velizar, Shivarov Hristo, Yordanov Angel

机构信息

Department of Experimental Research, Medical University Pleven, 5800 Pleven, Bulgaria.

Singing River Hospital, Pascagoula, MS 39567, USA.

出版信息

Healthcare (Basel). 2023 Feb 4;11(4):456. doi: 10.3390/healthcare11040456.

Abstract

Cancer patients are at increased risk of cerebrovascular events. The incidence of those events and the associated mortality are known to follow a seasonal pattern in the general population. However, it is unclear whether cerebrovascular mortality in cancer patients has seasonal variation. To address this question, we performed a retrospective analysis of the seasonality of deaths due to the fact of cerebrovascular diseases among patients with first primary malignancy registered between 1975 and 2016 in the SEER database. The presence of seasonality in death rates was modeled using the cosinor approach assuming a circa-annual pattern. A significant seasonal pattern with a peak in the first half of November was identified in all patient groups. The same peak was observed in almost all subgroups of patients defined based on demographic characteristics. However, not all entity-defined subgroups showed a seasonal pattern, which might be explained by the different pathologic processes affecting the circulatory system in each cancer type. Based on our findings, one can propose that the active monitoring of cancer patients for cerebrovascular events from the late autumn and during the winter can help in the reduction of mortality in this patient population.

摘要

癌症患者发生脑血管事件的风险增加。在普通人群中,这些事件的发生率及相关死亡率呈现季节性模式。然而,癌症患者的脑血管死亡率是否存在季节性变化尚不清楚。为解决这一问题,我们对1975年至2016年在监测、流行病学和最终结果(SEER)数据库中登记的首发性原发性恶性肿瘤患者因脑血管疾病导致的死亡季节性进行了回顾性分析。采用角余弦分析方法对死亡率的季节性进行建模,假设其为近似年度模式。在所有患者组中均发现了显著的季节性模式,11月上半月出现峰值。在几乎所有根据人口统计学特征定义的患者亚组中都观察到了相同的峰值。然而,并非所有按实体定义的亚组都呈现季节性模式,这可能是由于每种癌症类型中影响循环系统的病理过程不同所致。基于我们的研究结果,可以提出,在深秋和冬季对癌症患者进行脑血管事件的主动监测有助于降低该患者群体的死亡率。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验