Related Experiment Video
Updated: Jul 17, 2026

14:31
Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees
Published on: July 15, 2009
13.9K
Evaluation of the SwedeAmp database: Focus on coverage and amputation level rates
A G Johannesson1, R Scheving2, K L Westlund2
1Össur Clinics EMEA, Stockholm, Sweden.
Canadian Prosthetics & Orthotics Journal
|February 24, 2025
Summary
SwedeAmp captured only 48.6% of lower limb amputations (LLA) in Sweden. Improving data completeness is crucial for national standards and research in amputation care.
Area of Science:
- Medical Informatics
- Public Health
- Surgical Outcomes Research
Background:
- National health registers, including the Swedish National Inpatient Register (IPR) and SwedeAmp, are managed by the National Board of Health and Welfare.
- IPR covers all surgical operations, while SwedeAmp focuses on outcomes after lower limb amputations (LLA).
- External analysis of LLA coverage rates between these registers has been lacking.
Purpose of the Study:
- To compare the coverage of SwedeAmp with IPR for LLA cases.
- To assess the accuracy of SwedeAmp in capturing LLA data.
- To identify discrepancies and establish benchmarks for common amputation levels.
Main Methods:
- Comparative analysis of LLA data from SwedeAmp and IPR (2018-2023).
- Calculation of SwedeAmp's coverage rate using IPR as the denominator.
- Assessment of patient demographics and amputation levels.
Main Results:
- IPR recorded 10,788 LLAs; SwedeAmp documented 5,246, indicating 48.6% coverage.
- Significant underrepresentation of individuals over 85 years in SwedeAmp.
- Variable coverage rates across regions and hospitals, with only 13 regions exceeding 40%.
Conclusions:
- SwedeAmp's 48.6% coverage necessitates improved data completeness for LLA records.
- Proposed benchmarks (≥60% overall, ≤36.3% transfemoral, ≤8.4% knee disarticulations, ≥55.3% transtibial) can enhance reporting consistency.
- Expanded coverage will improve SwedeAmp's utility for outcome tracking, standard setting, research, and clinical decision-making.
Keywords:
AmputationAmputation RatesKnee DisarticulationLower Limb AmputationRehabilitationSwedeAmpSwedenTransfemoralTranstibialMore Related Videos
Related Concept Videos
Review and Preview
In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
Percentiles are a type of fractile that partition data into...
Quality Assurance
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
Introduction to Scalers
Many familiar physical quantities can be specified completely by giving a single number and the appropriate unit. For example, "a class period lasts 50 min," or "the gas tank in my car holds 65 L," or "the distance between the two posts is 100 m." A physical quantity that can be specified completely in this manner is called a scalar quantity. The word "scalar" is a synonym for "number." Time, mass, distance, length, volume, temperature, and energy are some examples of scalar quantities.
Scalar...
Scalar...
Statgraphics
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...

