Reported Adverse Events for Hip Prostheses and Knee Prostheses Before, During, and After the COVID-19 Pandemic
Bibliographic record
Abstract
The SARS-CoV-2 (COVID-19) pandemic had a profound impact on surgical practices in the United States due to the limited medical resources and cancellation of inpatient treatments, including elective surgeries.As two of the most frequently performed surgical procedures, total knee arthroplasty (TKA) and total hip arthroplasty (THA) can provide insights into the impact of the COVID-19 pandemic on healthcare outcomes.This study investigates the number of reported adverse events for TKA and THA based on United States Food and Drug Administration (FDA) data in the Manufacturer and User Facility Device Experience (MAUDE) database.The MAUDE database was searched using the NJL product code for TKA devices, and the NXT product code for THA devices, and the study compares the number of reported adverse events before, during, and after the COVID-19 pandemic.The findings indicate that knee prostheses and hip prostheses exhibited distinct trends for reported adverse events from 2018 to 2023.Reported injuries for knee prostheses peaked during the pandemic period, as the number of reported injuries increased significantly by 43% from 1709 to 2443 cases (p<0.003)from 2020 to 2021.However, reported injuries for hip prostheses peaked before the pandemic, with a significant 77% decrease in reported injuries, from 573 to 133 (p<0.0007)from 2018 to 2023.Possible explanations for the differences in reported injury trends between TKA and THA include differences in the patient population receiving knee prostheses compared to those receiving hip prostheses, for instance, differences in the underlying health status of patients.Also, differences in the level of difficulty between the two types of prostheses can be a possible explanation.Future research should investigate the underlying causes for trends in reported adverse events, and expand the investigation to include other orthopaedic devices such as ankle-foot prostheses and spinal implants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".