迷你HoLEP (MILEP) 与HoLEP:一个倾向得分匹配的分析分析
Tarek Taha1,2, Ziv Savin1,2,3, Karin Lifshitz2,3
1Endourology Unit, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel.
World journal of urology
|August 25, 2023
概括
小型荷激光前列腺核切除术 (MiLEP) 提供了更好的结果. 与标准的HoLEP相比,这种微创的技术减少了灌,保持了体温,并减少了肉体扩张的需要.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 最少侵入性的手术
- 手术技术 手术技术
背景情况:
- 最小的侵入性对于泌尿病学的外科结果至关重要.
- 前列腺的霍尔激光核化 (HoLEP) 是良性前列腺增生的一种标准治疗方法.
- 评估小型化技术对于改善患者护理至关重要.
研究的目的:
- 通过使用22法 (FR) 系统,评估小型化荷激光前列腺疏核 (MiLEP) 的手术内性能和临床结果.
- 为了比较MiLEP (22FR) 与标准的26-FR荷激光前列腺核切除术 (HoLEP).
主要方法:
- 对连续的前列腺激光取核进行了倾向分数匹配的分析.
- 形成了两个匹配的小组:MiLEP (22 FR,n=40) 和HoLEP (26 Fr,n=40).
- 进行了统计分析,以比较两组之间的结果.
主要成果:
- 在MiLEP中,手术期间的灌量显著减少 (15L对比20.5L),身体核心温度下降较小 (0.1°C对比0.6°C).
- 在MiLEP组中,肌肉扩张的需要显著降低 (25%对78%).
- 在MiLEP组中观察到较少早期术后压力失禁的趋势,在有效性,手术时间,住院时间或并发症方面没有显著差异.
结论:
- 小型荷激光前列腺核切除 (MiLEP) 是一种可行的技术.
- 与HoLEP相比,MiLEP在维持身体核心温度,减少灌液,并最大限度地降低肌肉扩张的需要方面具有优势.
- 在不影响疗效的情况下,MiLEP可能会导致早期术后压力失禁的减少和更短的恢复期.
相关概念视频
Sign Test for Matched Pairs
161
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
To conduct the sign test, we first calculate the differences in...
161
Wilcoxon Signed-Ranks Test for Matched Pairs
162
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
162
Comparing the Survival Analysis of Two or More Groups
222
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...
222
Multiple Comparison Tests
3.9K
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
3.9K
Kaplan-Meier Approach
179
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
179
Bonferroni Test
2.8K
The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
2.8K


