相关实验视频

Updated: Jun 17, 2025

Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running

Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running

Published on: September 14, 2017

一个批判性的文献综述,突出了流行病学研究中的方法差异:英格兰的脚踏截肢

Frank L Bowling¹, Lauren Burdett², Keeley Foley³

¹University of Manchester, Consultant Podiatric Surgeon, Manchester Foundation Trust, England.

Foot (Edinburgh, Scotland)

|August 10, 2024

概括

关于下肢截肢 (LEA) 率的不一致报告妨碍了趋势分析. 标准化定义和数据报告对于准确的LEA流行病学研究至关重要.

科学领域:

流行病学流行病学
公共卫生公共卫生
血管外科血管外科

背景情况:

在报告下肢截肢 (LEA) 率时,标准化的流行病学原则被不一致地应用.
现有的LEA率数据显示出广泛的差异,特别是在糖尿病人和非糖尿病人群之间,这阻碍了比较.
方法上的不一致性阻碍了在不同人群和时间段中比较LEA率的能力.

研究的目的:

系统地审查和比较英格兰轻微下肢截肢的方法和率.
识别不同地区和不同人口群体的mLEA报告的变化.
评估不一致的报告对确定流行病学趋势的能力的影响.

主要方法:

根据PRISMA指南进行了系统的文献搜索,以研究英格兰的mLEA率 (1988-2018).
搜索包括电子数据库,灰色文献和参考列表搜索.
确定了11项符合条件的研究,并纳入了审查.

主要成果:

在英格兰,在各区域和性别群体中观察到mLEA率的显著变化.
报告的发病率差异很大:糖尿病人群每10万人中1.2-362.9人,非糖尿病人群每10万人中0.9-109.4人.
差异主要源于定义不良的分数/分母群和对轻微截肢的多样化定义,阻止了自信的趋势分析.

结论:

对mLEAs的不一致报告使时间和人口变化的解释变得复杂.
未来的研究必须清楚地定义mLEAs的数和分母 (数量,年龄,性别) 种群.
建议采用对轻微截肢 (脚或脚以下) 的标准定义,以提高数据的一致性.

关键词:

截肢是一种截肢.流行病学流行病学影响影响影响影响下肢截肢是一个截肢.这是一个轻微的截肢.流行程度流行程度

更多相关视频

Lower Limb Biomechanical Analysis of Healthy Participants

Lower Limb Biomechanical Analysis of Healthy Participants

Published on: April 15, 2020

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication

Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication

Published on: December 11, 2013

相关概念视频

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

Comparing the Survival Analysis of Two or More Groups

Comparing the Survival Analysis of Two or More Groups

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...