Vasilopoulos, Terrie

Background: When missing data are present in clinical outcomes studies, complete-case analysis (CCA) is often performed, whereby patients with missing data are excluded. While simple, CCA analysis may impart selection bias and reduce statistical power, leading to erroneous statistical results in some cases. However, there exist more rigorous statistical approaches, such as single and multiple imputation, which approximate the associations that would have been present in a full dataset and preserve the study’s power. The purpose of this study is to evaluate how statistical results differ when performed after CCA analysis versus imputation methods. Methods: This simulation study analyzed a sample dataset consisting of 2204 shoulders, with complete datapoints from a larger multicenter total shoulder arthroplasty database. From the sampled dataset of demographics, surgical characteristics, and clinical outcomes, we created five test datasets, ranging from 100 to 2000 shoulders, and simulated 10–50% missingness in the postoperative American Shoulder and Elbow Surgeons (ASES) score and range of motion in four planes in missing completely at random (MCAR), missing at random (MAR), and not missing at random (NMAR) patterns. Missingness in outcomes was remedied using CCA, three single imputation techniques, and two multiple imputation techniques. The imputation performance was evaluated relative to the native complete dataset using the root mean squared error (RMSE) and the mean absolute percentage error (MAPE). We also compared the mean and standard deviation (SD) of the postoperative ASES score and the results of multivariable linear and logistic regression to understand the effects of imputation on the study results. Results: The average overall RMSE and MAPE were similar for MCAR (22.6 and 27.2%) and MAR (19.2 and 17.7%) missingness patterns, but were substantially poorer for NMAR (37.5 and 79.2%); the sample size and the percentage of data missingness minimally affected RMSE and MAPE. Aggregated mean postoperative ASES scores were within 5% of the true value when missing data were remedied with CCA, and all candidate imputation methods for nearly all ranges of sample size and data missingness when data were MCAR or MAR, but not when data were NMAR. When data were MAR, CCA resulted in overestimates of the SD. When data were MCAR or MAR, the accuracy of the regression estimate (β or OR) and its corresponding 95% CI varied substantially based on the sample size and proportion of missing data for multivariable linear regression, but not logistic regression. When data were MAR, the width of the 95% CI was up to 300% larger when CCA was used, whereas most imputation methods maintained the width of the 95% CI within 50% of the true value. Single imputation with k-nearest neighbor (kNN) method and multiple imputation with predictive mean matching (MICE-PMM) best-reproduced point estimates and intervariable relationships resembling the native dataset. Availability of correlated outcome scores improved the RMSE, MAPE, accuracy of the mean postoperative ASES score, and multivariable linear regression model estimates. Conclusions: Complete-case analysis can introduce selection bias when data are MAR, and it results in loss of statistical power, resulting in loss of precision (i.e., expansion of the 95% CI) and predisposition to false-negative findings. Our data demonstrate that imputation can reliably reproduce missing clinical data and generate accurate population estimates that closely resemble results derived from native primary shoulder arthroplasty datasets (i.e., prior to simulated data missingness). Further study of the use of imputation in clinical database research is critical, as the use of CCA may lead to different conclusions in comparison to more rigorous imputation approaches.

ABSTRACTIntroductionLung transplantation has been evolving since its inception in 1963. Over recent years, literature has suggested a shift in the perioperative strategy of mechanical support toward extracorporeal membrane oxygenation (ECMO) as the preferred modality of extracorporeal life support (ECLS) in lung transplantation. The Survey of ECLS Application in Lung transplantation (SEAL) was designed to elucidate the current practice patterns of perioperative ECLS within the United States.MethodsIn this cross‐sectional study, a physician from 62 adult lung transplantation centers across the United States of America (USA) was surveyed on their institutional practices regarding the perioperative management of lung transplantation patients, with a focus on mechanical support.ResultsThe survey completion rate was 74% (46/62 eligible institutions). Most transplant centers utilize venoarterial (VA) ECMO (78%, 36/46) and/or venovenous (VV) ECMO (93%, 29/43) as a bridge to lung transplantation. When ECLS is used intraoperatively, 61% of (28/46) responding programs use VA ECMO as their preferred support. All programs use transesophageal echocardiography (TEE) intraoperatively, 85% (33/39) cannulate for ECMO centrally, and 74% (29/39) use a combination of inhaled and intravenous anesthesia while using ECMO intraoperatively. Most programs do not use antifibrinolytic during VA ECMO (62%, 28/45). Anticoagulation management and VA ECMO flows throughout the procedure showed considerable variation.ConclusionData from SEAL illustrates that though there are some practice commonalities within the United States, there is also quite a bit of variability in practice. Multiple dominant practices within the USA are consistent with a recently published International Society of Heart and Lung Transplantation consensus.

Abstract: Today, well-designed randomized clinical trials (RCTs) are considered the pinnacle of clinical research, and they inform many practices in orthopaedics. When designing these studies, researchers conduct a power analysis, which allows researchers to strike a balance between (1) enrolling enough patients to detect a clinically important treatment effect (i.e., researchers can be confident that the effect is unlikely due to chance) and (2) cost, time, and risk to patients, which come with enrolling an excessive number of patients. Because researchers will have a desire to conduct resource-efficient RCTs and protect patients from harm, many studies report a p value that is close to the threshold for significance. The concept of the fragility index (FI) was introduced as a simple way to interpret RCT findings, but it does not account for RCT design. The adoption of the FI conflicts with researchers’ goals of designing efficient RCTs that conserve resources and limit ineffective or harmful treatments to patients. The use of the FI may reflect many clinicians’ lack of familiarity with interpreting p values beyond “significant” or “nonsignificant.” Instead of inventing new metrics to convey the same information provided by the p value, greater emphasis should be placed on educating clinicians on how to interpret p values and, more broadly, statistics, when reading scientific studies.

Aims Both anatomical and reverse total shoulder arthroplasty (aTSA and rTSA) provide functional improvements. A reported benefit of aTSA is better range of motion (ROM). However, it is not clear which procedure provides better outcomes in patients with limited foward elevation (FE). The aim of this study was to compare the outcome of aTSA and rTSA in patients with glenohumeral osteoarthritis (OA), an intact rotator cuff, and limited FE. Methods This was a retrospective review of a single institution’s prospectively collected shoulder arthroplasty database for TSAs undertaken between 2007 and 2020. A total of 344 aTSAs and 163 rTSAs, which were performed in patients with OA and an intact rotator cuff with a minimum follow-up of two years, were included. Using the definition of preoperative stiffness as passive FE ≤ 105°, three cohorts were matched 1:1 by age, sex, and follow-up: stiff aTSAs (85) to non-stiff aTSAs (85); stiff rTSAs (74) to non-stiff rTSAs (74); and stiff rTSAs (64) to stiff aTSAs (64). We the compared ROMs, outcome scores, and complication and revision rates. Results Compared with non-stiff aTSAs, stiff aTSAs had poorer passive FE and active external rotation (ER), whereas there were no significant postoperative differences between stiff rTSAs and non-stiff rTSAs. There were no significant differences in preoperative function when comparing stiff aTSAs with stiff rTSAs. However, stiff rTSAs had significantly greater postoperative active and passive FE (p = 0.001 and 0.004, respectively), and active abduction (p = 0.001) compared with stiff aTSAs. The outcome scores were significantly more favourable in stiff rTSAs for the Shoulder Pain and Disability Index, Simple Shoulder Test, American Shoulder and Elbow Surgeons score, University of California, Los Angeles score, and the Constant score, compared with stiff aTSAs. When comparing the proportion of stiff aTSAs versus stiff rTSAs that exceeded the minimal clinically important difference and substantial clinical benefit, stiff rTSAs achieved both at greater rates for all measurements except active ER. The complication rate did not significantly differ between stiff aTSAs and stiff rTSAs, but there was a significantly higher rate of revision surgery in stiff aTSAs (p = 0.007). Conclusion Postoperative overhead ROM, outcome scores, and rates of revision surgery favour the use of a rTSA rather than aTSA in patients with glenohumeral OA, an intact rotator cuff and limited FE, with similar rotational ROM in these two groups. Cite this article: Bone Joint J 2023;105-B(12):1303–1313.