Informed Consent in Patients Undergoing Primary Hip and Knee Arthroplasty: What Do Patients Want to Know?
Bibliographic record
Abstract
Introduction The consenting process has been surgeon-focussed traditionally, but there is a recent trend towards making the process more patient and procedure-focussed. The primary aims were to identify the risks considered most important and requiring further discussion by the patients undergoing primary total hip arthroplasty (THA) and primary total knee arthroplasty (TKA), as well as to identify the sporting and recreational activities these patients would like to pursue after surgery according to the age group, taking into consideration their values and expectations. The secondary aim is to assess the compliance of the current consenting process with guidelines set out by a governing body in a tertiary referral arthroplasty unit. Material and method A prospective study reviewing the consenting process was carried out on 137 patients undergoing THA or TKA over a 12-month period in a tertiary teaching hospital. Patients unable to complete a questionnaire and undergoing revision or uni-compartment arthroplasty were excluded. A standardized anonymous questionnaire was administered. Patients were asked to fill in the specific activities they considered important to be discussed. The data were tabulated in Microsoft Excel (Microsoft Corporation, Redmond, Washington) and subgroup analysis was performed using the student's t-test. The level of statistical significance was p=0.05. Two-hundred consent forms were reviewed to assess whether the information entered correlated to the guidelines presented in Ortho-Consent. Results One-hundred thirty-seven questionnaires were reviewed. The mean age was 66 (range 45-91), with the majority of patients undergoing TKA (114) versus THA (23). The patients in active employment were more concerned about blood clots, pain, joint failure, limb length discrepancy, and infection. Patients undergoing TKA wanted more information on pain management and joint longevity, which achieved statistical significance. There was a significant difference in the activities patients would like to pursue as well as in expectations amongst different age groups. The quality of documentation in the consent form was quite variable in discussing complications, surgery benefits, and alternative treatments. Conclusion Obtaining consent is a patient-specific process. Patient perception of important points that merit discussion can vary with age and employment status. Return to driving is important for all ages, however, as the population ages, the ability to return to activities of daily living becomes an increasingly important discussion point during the consent process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".