Characterizing Negative Online Reviews of Pediatric Orthopaedic Surgeons.

BACKGROUND: The growing focus on subjective patient experiences has created an increase in popularity for physician rating websites. The purpose of this study was to characterize extremely negative reviews of pediatric orthopaedic surgeons. METHODS: Pediatric orthopaedic surgeons were randomly selected using the Pediatric Orthopaedic Society of North America comprehensive list of surgeons. A search was then performed on Healthgrades.com, Vitals.com, and Yelp.com for 1-star reviews. Reviews were classified into clinical and nonclinical categories. Statistical analyses were performed regarding the frequency of reviews and complaints for each respective category. RESULTS: Of the 279 one-star reviews categorized, 248 reviews (88.9% of reviews) included nonclinical complaints, and 182 reviews (65.2% of reviews) included clinical complaints. Nonsurgical patients were associated with 255 reviews, and the remaining 24 were related to surgical patients. Of the 430 comments within reviews, 248 referenced nonclinical aspects of care, and 182 referenced clinical care. Clinical factors most frequently noted included clinical disagreement (37%), unclear treatment plan (25%), complication (17%), misdiagnosis (15%), uncontrolled pain (13%), and delay in care (8%). The most addressed nonclinical factors included physician bedside manner (68%), time spent with provider (21%), wait time (18%), unprofessional staff (17%), scheduling issues (9%), cost (8%), and billing (8%). Compared with surgical reviews, nonsurgical reviews were more likely to contain nonclinical complaints (rate ratio: 1.5; P<0.05) and less likely to contain clinical complaints (rate ratio: 0.7; P<0.05). The most common complaint by surgical patients was complications (91.7%). CONCLUSIONS: To our knowledge, this is the first study to examine the factors associated with negative reviews of pediatric orthopaedic surgeons. The majority of reviews of pediatric orthopaedic surgeons were left by nonsurgical patients and were related to nonclinical aspects of care. We also found surgeon-dependent factors such as poor physician bedside manner, unclear treatment plan, or parents' disagreement with treatment plan were the most common reasons for negative reviews. LEVEL OF EVIDENCE: Level IV.

Body Composition Assessment in Male and Female Bodybuilders: A 4-Compartment Model Comparison of Dual-Energy X-Ray Absorptiometry and Impedance-Based Devices.

Graybeal, AJ, Moore, ML, Cruz, MR, and Tinsley, GM. Body composition assessment in male and female bodybuilders: a 4-compartment model comparison of dual-energy x-ray absorptiometry and impedance-based devices. J Strength Cond Res 34(6): 1676-1689, 2020-The purpose of this study was to examine the group and individual accuracy of body composition estimates obtained from multicompartment models, dual-energy x-ray absorptiometry (DXA), and several impedance-based devices in male and female bodybuilders. Twenty-seven male (n = 17; 4-compartment [4C] model fat-free mass index [FFMI]: 25.1 ± 1.8 kg·m; 4C body fat: 11.8 ± 4.4%) and female (n = 10; 4C FFMI: 18.3 ± 1.4 kg·m; 4C body fat: 19.7 ± 4.9%) bodybuilders underwent duplicate assessments using DXA, bioimpedance spectroscopy (BIS), electrical impedance myography (EIM), and 3 bioelectrical impedance analysis (BIA) devices. In addition to utilizing standard output, multicompartment models were generated. For each method, body fat %, FFM, and fat mass were compared with the reference 4C model for the evaluation of group and individual errors. The 3-compartment model with a BIS body water estimate produced the lowest standard error of the estimate, total error (TE), and 95% limits of agreement (LOA) for all variables, although some alternative methods had lower constant error (CE). In general, multicompartment models with BIS or multifrequency BIA body water estimates produced more accurate body composition estimates than single assessment techniques (i.e., DXA, BIS, EIM, and BIA). Single assessment techniques produced low CE and TE for some body composition variables. However, proportional bias was observed for DXA and BIS. All single assessment techniques produced LOA large enough to make the utility of these methods questionable in individual athletes. Appropriate caution should be used when interpreting and utilizing body composition estimates in muscular physique athletes, particularly at the individual level.

Precision of Dual-Energy X-Ray Absorptiometry Reflection Scans in Muscular Athletes.

BACKGROUND: Offset scanning procedures, such as reflection scanning, allow for dual-energy x-ray absorptiometry (DXA) body composition assessment of individuals who are too broad for standard scanning dimensions. However, limited information is available concerning the precision of this procedure, particularly in athletes. METHODOLOGY: Twenty-seven muscular athletes (n = 17 males, BMI: 28.8 ± 2.0 kg/m2, DXA body fat: 12.5 ± 2.7%; n = 10 females, BMI: 22.8 ± 1.6 kg/m2, DXA body fat: 19.2 ± 3.4%) underwent consecutive DXA scans on a GE Lunar Prodigy scanner using the reflection scanning technique. The fully automated output was obtained for each scan, and an additional version of each scan's output was saved after manual adjustment of regions of interest (ROI). Metrics of reliability and precision were calculated for total and regional body mass (BM), lean mass (LM), fat mass (FM) and bone mineral content (BMC). These metrics included the precision error (PE), least significant change, ΔMean, technical error of measurement, intraclass correlation coefficient, smallest worthwhile effect and minimum difference considered real. RESULTS: Reflection scanning produced small errors for BM (PE: ∼0.5%), LM (PE < 1%) and BMC (PE: ∼1.2%), with larger errors observed for total FM (PE: ∼3%). Manual ROI adjustment produced lower errors for total BM, LM, FM, and BMC, as well as lower errors for most regional estimates. The utilization of automated ROI revealed concerns unique to reflection scanning, including unnecessary estimation of trunk composition, which appreciably increased error in this region. Regional estimates produced higher errors for all variables as compared to whole-body estimates, although which regions produced the highest errors differed between BM, LM, FM, and BMC. CONCLUSIONS: Reflection scanning allows DXA body composition assessment in individuals exceeding traditional scanning dimensions, including broad athletes. Although this procedure introduces error, it may be minimized through manual adjustment of ROIs and consistency of analysis methods.