Comparison of conventional versus robotic-assisted total hip arthroplasty using the Mako system: An Italian retrospective study
Bibliographic record
Abstract
Introduction: Our research aimed to evaluate differences in terms of length of hospital stay and clinical outcomes between robotic-arm assisted using MAKO system and standard manual implantation in a group of patients who underwent primary total hip arthroplasty (THA). Methods: Our retrospective, cohort study was conducted between August 2014 and March 2016. From our target population of 376 patients from three hospitals of Tuscany Region, Italy, we randomly selected a sample of 220 patients, who was subdivided in two groups (MAKO system n = 100; Standard technique n = 120). Our evaluation was carried out before and after surgery at 24 months follow-up. Western Ontario and McMaster (WOMAC) Osteoarthritis Index, Harris Hip Modified Score (HHS), and Numeric Pain Rating Score (NPRS) scales were administered. One sample and independent sample T Student tests were used to assess eventual differences within and between groups for the continuous variables. The significance threshold was set up at P < 0.05. Results: Rate of respondents was 48.6% (MAKO system n = 56, 56%; Standard technique n = 51, 42.5%). There was a significant difference in the length of hospital stay, expressed as number of days hospitalized, between the MAKO group (M = 5.14, SD = 1.98) and the standard group (M = 8.11, SD = 1.64) (t(105) = 15.30, P < 0.001). There were no significant differences in preoperative and post-operative scores between robotic-assisted and standard groups in all of the patient-reported outcome measures (PROMs), but we reported a statistically and clinically significant improvement in all of the post-operative PROMs scores for both surgical procedures (P < 0.001). Discussion and Conclusion: Our findings showed that the MAKO™ robotic is a valuable technology that may innovate THA. However, further long-term studies are needed to justify additional costs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".