80岁以上患者的手术:全国性队列研究中的死亡率和康复率
Jesper Eriksson1,2, Cornelia Sandberg2, Naima Kilhamn1,2
1Section of Anesthesiology and Intensive Care Medicine, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
Anaesthesia
|March 12, 2025
概括
经过急性手术的80岁及以上的老年人面临高死亡率和恢复挑战. 选择性手术显示死亡率较低,这表明年龄不应该阻止与量身定制的护理进行干预.
科学领域:
- 老年人手术是一门老年手术.
- 在外科手术期间的医学.
- 患者研究成果研究结果
背景情况:
- 在全球人口老龄化中,对外科手术的需求日益增加.
- 老年人 (≥80岁) 面临由于生理变化和并发症而增加的手术风险.
- 需要对老年人群的手术结果进行全面评估.
研究的目的:
- 评估80岁及以上接受手术的患者的短期和长期死亡率.
- 评估以患者为中心的结果,包括活着和在家的日子 (手术后的30天和90天).
- 为了比较老年人选择性和急性外科手术程序之间的结果.
主要方法:
- 全国范围的队列研究,使用瑞典定期手术注册表 (2019年1月至2023年3月).
- 包括接受手术的80岁以上的患者.
- 与国家患者登记 (并发病) 和国家死亡原因登记的联系.
- 主要结局:30天全因死亡率;次要结局:365天死亡率,活着的日子和在家.
主要成果:
- 包括118,359名患者:54,320名选择性,64,039名急性手术.
- 30天死亡率:1.2% (选择性) 与9.9% (急性) 相比.
- 随着年龄的增长,死亡率显著增加,特别是在90岁以上的人群中.
- 对于急性手术患者来说,观察到活着和在家的日数较少,这表明恢复和并发症的时间较长.
结论:
- 经过急性手术的90岁以上的患者死亡率高,恢复困难.
- 选择性手术显示短期死亡率较低,这表明仅仅年龄并不是一个禁忌.
- 个性化的术后护理和共享决策对于优化老年手术患者的治疗结果至关重要.
相关概念视频
01:20Actuarial Approach
50
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
50
01:21Cancer Survival Analysis
315
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
315
01:20Comparing the Survival Analysis of Two or More Groups
113
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
113
01:15Assumptions of Survival Analysis
81
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
81