Reporting errors in plain radiographs for lower limb trauma-a systematic review and meta-analysis.

INTRODUCTION: Plain radiographs are a globally ubiquitous means of investigation for injuries to the musculoskeletal system. Despite this, initial interpretation remains a challenge and inaccuracies give rise to adverse sequelae for patients and healthcare providers alike. This study sought to address the limited, existing meta-analytic research on the initial reporting of radiographs for skeletal trauma, with specific regard to diagnostic accuracy of the most commonly injured region of the appendicular skeleton, the lower limb. METHOD: A prospectively registered, systematic review and meta-analysis was performed using published research from the major clinical-science databases. Studies identified as appropriate for inclusion underwent methodological quality and risk of bias analysis. Meta-analysis was then performed to establish summary rates for specificity and sensitivity of diagnostic accuracy, including covariates by anatomical site, using HSROC and bivariate models. RESULTS: A total of 3887 articles were screened, with 10 identified as suitable for analysis based on the eligibility criteria. Sensitivity and specificity across the studies were 93.5% and 89.7% respectively. Compared with other anatomical subdivisions, interpretation of ankle radiographs yielded the highest sensitivity and specificity, with values of 98.1% and 94.6% respectively, and a diagnostic odds ratio of 929.97. CONCLUSION: Interpretation of lower limb skeletal radiographs operates at a reasonably high degree of sensitivity and specificity. However, one in twenty true positives is missed on initial radiographic interpretation and safety netting systems need to be established to address this. Virtual fracture clinic reviews and teleradiology services in conjunction with novel technology will likely be crucial in these circumstances.

Waiting lists for symptomatic joint arthritis are not benign: prioritizing patients for surgery in the setting of COVID-19.

AIM: Restarting elective services presents a challenge to restore and improve many of the planned patient care pathways which have been suspended during the response to the COVID-19 pandemic. A significant backlog of planned elective work has built up representing a considerable volume of patient need. We aimed to investigate the health status, quality of life, and the impact of delay for patients whose referrals and treatment for symptomatic joint arthritis had been delayed as a result of the response to COVID-19. METHODS: We interviewed 111 patients referred to our elective outpatient service and whose first appointments had been cancelled as a result of the response to the COVID-19 pandemic. RESULTS: Patients reported significant impacts on their health status and quality of life. Overall, 79 (71.2%) patients reported a further deterioration in their condition while waiting, with seven (6.3%) evaluating their health status as 'worse than death'. CONCLUSIONS: Waiting lists are clearly not benign and how to prioritize patients, their level of need, and access to assessment and treatment must be more sophisticated than simply relying on the length of time a patient has been waiting. This paper supports the contention that patients awaiting elective joint arthroplasty report significant impacts on their quality of life and health status. This should be given appropriate weight when patients are prioritized for surgery as part of the recovery of services following the COVID-19 pandemic. Elective surgery should not be seen as optional surgery-patients do not see it in this way.

Clinical Characteristics and Predictors of Mortality in Patients with COVID-19 Infection Outside Intensive Care.

BACKGROUND/INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic has affected all aspects of inpatient hospital medicine with patients admitted from level 1 (general medical wards) to level 3 (intensive care). Often, there are subtle physiological differences in these cohorts of patients. In particular, in intensive care, patients tend to be younger and have increased disease severity. Data, to date, has combined outcomes from medical and intensive care cohorts, or looked exclusively at intensive care. We looked solely at the level 1 (medical) cohort to identify their clinical characteristics and predictors of outcome. PATIENTS AND METHODS: This was a retrospective study of adult patients admitted to a central London teaching hospital with a diagnosis of COVID-19 from 23rd March to 7th April 2020 identified from the hospital electronic database. Any patients who required level 2 or 3 care were excluded. RESULTS: A total of 229 patients were included for analysis. Increased age and frailty scores were associated with increased 30-day mortality. Reduced renal function and elevated troponin blood levels are also associated with poor outcome. Baseline observations showed that increased oxygen requirement was predictive for mortality. A trend of increased mortality with lower diastolic blood pressure was noted. Lymphopenia was not shown to be related to mortality. CONCLUSION: Urea and creatinine are the best predictors of mortality in the level 1 cohort. Unlike previous intensive care data, lymphopenia is not predictive of mortality. We suggest that these factors be considered when prognosticating and for resource allocation for the treatment and escalation of care for patients with COVID-19 infection.