Diagnostic Accuracy and Operational Efficiency of Point-of-Care Ultrasound (POCUS) in Long Bone Fractures: A Brazilian Multicenter Study

Overview

The purpose of this study is to evaluate the diagnostic accuracy and operational efficiency of Point-of-Care Ultrasound (POCUS) for identifying long bone fractures in the emergency department. Traditionally, suspected long bone fractures are diagnosed using X-rays. While effective, X-rays require transporting patients to a radiology suite, involve exposure to ionizing radiation, and can contribute to longer emergency room wait times. POCUS is a portable, radiation-free imaging tool that physicians perform directly at the patient's bedside. The investigators hypothesize that POCUS can accurately identify or rule out long bone fractures when compared to standard X-rays, and that its use will reduce the time required to make clinical decisions. This is a multicenter, prospective observational study. Participants arriving at the emergency department with a suspected long bone fracture will undergo a bedside ultrasound examination performed by a trained emergency physician. Following the ultrasound, all participants will receive standard-of-care X-ray imaging. Researchers will compare the initial POCUS findings to the final X-ray results (the reference standard) to determine the sensitivity and specificity of the ultrasound. Additionally, the study will measure operational timelines-including time to diagnosis, time to treatment decision, and total length of stay in the emergency department-to assess the impact of POCUS on hospital workflow and patient care efficiency.

\## Background and Rationale Long bone fractures are among the most frequent traumatic injuries managed in emergency departments (EDs) worldwide. The current standard of care for diagnosing these fractures is plain radiography (X-ray). While highly effective and widely available, the standard radiological workflow presents several challenges in crowded ED environments. It requires patient transport to a radiology suite-which can exacerbate pain in trauma patients-involves exposure to ionizing radiation, and often contributes to significant delays in clinical decision-making and overall length of stay (LOS). Point-of-Care Ultrasound (POCUS) has emerged as a rapid, portable, and radiation-free imaging modality that can be performed directly at the patient's bedside. Previous single-center studies have suggested that POCUS has high sensitivity and specificity for detecting fractures. However, there is a lack of robust, multicenter data evaluating its real-world implementation in diverse Brazilian emergency settings. The POCUS-BONE BR study aims to fill this gap by assessing both the diagnostic accuracy and the operational impact of integrating musculoskeletal POCUS into the standard trauma workflow. \## Study Objectives \*\*Primary Objective:\*\* To determine the diagnostic accuracy (sensitivity, specificity, positive predictive value, and negative predictive value) of bedside POCUS performed by emergency physicians for the detection of long bone fractures, using standard plain radiography as the reference standard. \*\*Secondary Objectives:\*\* * To evaluate operational efficiency by comparing time-to-diagnosis and time-to-disposition between the POCUS evaluation and standard radiological workflows. * To assess patient pain levels during the POCUS examination compared to standard X-ray positioning, using the Visual Analog Scale (VAS). * To determine the inter-observer agreement between the emergency physician's POCUS interpretation and the formal radiologist's X-ray report. * Study Design and Methodology POCUS-BONE BR is a prospective, multicenter, observational diagnostic accuracy study. It will be conducted across \[Insert Number\] participating emergency departments in Brazil. Eligible patients presenting to the ED with clinical signs of a suspected long bone fracture (involving the femur, tibia, fibula, humerus, radius, or ulna) will be enrolled consecutively. Written informed consent will be obtained from all participants or their legal representatives prior to enrollment. * Study Procedures 1. \*\*Initial Assessment:\*\* Upon ED arrival and triage, patients with suspected long bone fractures will undergo standard clinical evaluation. 2. \*\*POCUS Examination:\*\* An emergency physician trained in musculoskeletal ultrasound will perform a targeted bedside POCUS examination of the affected limb. The physician will document the presence or absence of a fracture, the fracture type (e.g., cortical disruption), and the time of examination completion. 3. \*\*Reference Standard Imaging:\*\* Following the POCUS exam, all patients will undergo standard plain radiography of the affected extremity as dictated by standard clinical care. 4. \*\*Blinding:\*\* The emergency physician performing the POCUS will be blinded to the subsequent X-ray results. The radiologist or attending orthopedist interpreting the definitive X-ray will be blinded to the POCUS findings. 5. \*\*Clinical Management:\*\* Patient care, analgesia, and orthopedic consultation will proceed according to institutional protocols and will not be delayed by study procedures. * Data Collection and Metrics Trained researchers will collect clinical and operational data using a standardized electronic case report form (eCRF) via \[e.g., REDCap\]. Key time-stamps recorded will include: * Time of ED triage. * Time of POCUS completion. * Time of X-ray completion. * Time to definitive medical decision/orthopedic consultation. * Total ED Length of Stay (LOS). * Statistical Analysis Plan Diagnostic accuracy metrics (sensitivity, specificity, positive predictive value, and negative predictive value) will be calculated with 95% confidence intervals using standard 2x2 contingency tables. The agreement between POCUS and X-ray findings will be evaluated using Cohen's kappa coefficient. Continuous variables (such as time-to-diagnosis and LOS) will be assessed for normality. Parametric data will be analyzed using Student's t-test, and non-parametric data using the Mann-Whitney U test. A p-value of \<0.05 will be considered statistically significant. The planned sample size of \[Insert Target Sample Size\] patients was calculated to achieve a \[Insert Power, e.g., 90%\] power to detect a sensitivity of at least \[Insert Percentage, e.g., 90%\] with a predefined margin of error.