Computer-Assisted Surgery Enables Beginner Surgeons, Under Expert Guidance, to Achieve Long-Term Clinical Results not Inferior to Those of a Skilled Surgeon in Knee Arthroplasty.

Purpose: The purpose of this study is to determine whether the use of a surgical navigation system in total knee replacement (TKR) enables beginner and intermediate surgeons to achieve clinical PROM outcomes as good as those conducted by expert surgeons in the long term. Methods: We enrolled 100 consecutive patients whose total navigated knee arthroplasty (TKA) was performed in our institution from 2008 to 2010. According to the principal surgeon's surgical experience, the patients were divided into three groups: (1) beginner surgeons, with no more than 30 previous knee replacement performances, (2) intermediate surgeons, with more than 30 but not more than 300, and (3) expert surgeons, with more than 300 knee replacements. Demographic data collected on the cohort included gender, laterality, age, and body mass index (BMI). The outcome measures assessed were Forgotten Joint Score (FJS), implant positioning, limb alignment, and prosthesis survival rate. A margin of equivalence of ± 18.5 points in the FJS scale was prespecified in terms of the minimal clinically important difference (MCID) to compare the FJS results obtained in the long period between the groups of interest. Results: The mean follow-up was 11.10 ± 0.78, 10.86 ± 0.66, and 11.30 ± 0.74 years, respectively, for each of the groups. The long-term FJS mean score was 80.86 ± 21.88, 81.36 ± 23.87, and 90.48 ± 14.65 for each group. The statistical analysis proved noninferiority and equivalence in terms of the FJS results reported in the long term by patients in Groups 1 or 2 compared to those in Group 3. More specifically, it has been proved that the mean difference between groups is within the interval of equivalence defined in terms of the MCID. The overall prostheses survival rate was 93.7%. Conclusion: Navigated assisted TKA, under expert guidance, can be as effective when performed by beginner or intermediate surgeons as performed by senior surgeons regarding the accuracy of implant positioning, limb alignment, and long-term clinical outcome.

Survival analysis and influence of the surgical aggression of a cohort of orthopedic and trauma patients in a non-controlled spread COVID-19 scenario.

BACKGROUND: Determining the infection rate and mortality probability in healthy patients who have undergone orthopedic and trauma surgeries (OTS) during a period of uncontrolled COVID-19 transmission may help to inform preparations for future waves. This study performed a survival analysis in a cohort of non-infected OTS patients and determined the effect of COVID-19 on mortality. METHODS: This observational study included 184 patients who underwent OTS in the month before surgical activities ceased and before the implementation of special measures. Four groups of surgery (GS) were established based on the location of the surgery and the grade of inflammation produced. Crude risk of infection and infection rates were assessed. Survival and failure functions by GS were analyzed. Comparison of the Kaplan-Meier survival curves by GS was assessed. Cox regression and Fine-Gray models were used to determine the effect of different confounders on mortality. RESULTS: The crude risk of COVID-19 diagnosis was 14.13% (95% CI: 9.83-19.90%). The total incidence rate was 2.67 (1000 person-days, 95% CI: 1.74-3.91). At the end of follow-up, there was a 94.42% chance of surviving 76 days or more after OTS. The differences in K-M survivor curves by GS indicated that GS 4 presented a lower survival function (Mantel-Cox test, p = 0.024; Wilcoxon-Breslow test, p = 0.044; Tarone-Ware test, p = 0.032). One of the best models to determine the association with mortality was the age-adjusted model for GS, high blood pressure, and respiratory history, with a hazard ratio of 1.112 in Cox regression analysis (95% CI: 1.005-1.230) and a sub hazard ratio of 1.111 (95% CI: 1.046-1.177) in Fine-Gray regression analysis for competitive risk. CONCLUSIONS: The infection risk after OTS was similar to that of the general population in a community transmission area; the grade of surgical aggression did not influence this rate. The survival probability was extremely high if patients had not previously been infected. With higher grades of surgical aggression, the risk of mortality was higher in OTS patients. Adjusting for age and other confounders (e.g., GS, high blood pressure and respiratory history) was associated with higher mortality rates.