Concussion Screening Evaluation: BESS vs Sway

Introduction: Rapid evaluation of concussion is important in the pre-hospital setting as an easy test. It is also useful in the ED, as too often little is done for concussed patients. The Balance Error Scoring System (BESS) is the current gold standard for evaluating balance, one of the best predictors of concussion. SWAY, a new gyroscope based iPhone application, is being proposed as a more sensitive and more objective test than BESS. This study will compare Sway to BESS to determine if there is equal efficacy.Method: 74 scholastic and collegiate athletes were administered baseline balance evaluations using Sway. Sway is scored out of 100 points and uses the iPhone’s gyroscope to measure balance while the device is clutched to the tester’s chest with both hands and eyes remain closed. In conjunction with their evaluations, we scored each athlete using BESS. Subjects are assessed one point for the following errors using BESS: Removing hands from the mobile device clutched to their chest; opening the eyes; stepping, stumbling, or falling; remaining out of the test position for five seconds; moving the hip into more than 30° of hip flexion or abduction; or lifting the forefoot or heel. No foam pad was used and subjects used their hands to clutch mobile device to chest instead of keeping hands on hips.Results: The average score of 4.1 on BESS correlates to an average score of 77.1 on Sway. There is moderate to strong correlation between Sway and BESS results that is statistically significant (P\u3c.05). The Sway average score has a STDev of 14.2. The BESS average score has a STDev of 2.9. According to “Normative data for the balance error scoring system: Implications for brain injury evaluation” (G.L. Iverson, M.L. Kaarto, and M.S. Koehle), the 76-90th percentile of individuals ages 20-39 scored 4-6 on BESS.Conclusion: Sway is equally, if not more, sensitive than BESS. While BESS is judged by humans and creates the possibility of human error to occur while evaluating subjects, Sway is completely automated so to minimize human error and give a completely objective score. Sway can replace BESS for rapid balance screening and still maintain clinical accuracy. 1) References “Normative data for the balance error scoring system: Implications for brain injury evaluation” (G.L. Iverson, M.L. Kaarto, and M.S. Koehle

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society