Mild traumatic brain injury (mTBI) is commonly encountered in the emergency department (ED), but there is wide variation in diagnosis, specialist referral, and follow-up. Our goal was to measure how frequently ED clinicians diagnosed mTBI during head injury evaluation at ED discharge and compare this to 1) mTBI diagnosis at outpatient follow-up and 2) mTBI diagnosis based on consensus diagnostic criteria via retrospectively reviewed clinical signs & symptoms. We further sought to assess how these frequencies vary with age and rurality. We performed a retrospective cohort study of adults treated and discharged from the ED with a diagnosis of closed head injury or mTBI for three months in one health system through electronic medical record data abstraction. We compared clinician diagnosis to 2023 American College of Rehabilitation Medicine (ACRM) consensus diagnostic criteria for mTBI and suspected mTBI. 314 patients were included and were predominantly urban (76%), age 65 years or older (42%) and female (62%). Forty patients (13%) had an ED diagnosis of mTBI, and 27 (9%) had suspected mTBI. ACRM-defined mTBI or suspected mTBI comprised 129 patients (41%), compared to 67 (21%) of clinician-documented mTBI or suspected mTBI. Eighty-four patients (27%) had a follow-up visit; 23 (8%) received mTBI diagnosis at follow-up. Young and urban adults were most frequently diagnosed with mTBI while rural and older adults were least frequently diagnosed. In conclusion, less than half of patients likely to have mTBI based on consensus criteria were diagnosed with mTBI at ED discharge, suggesting opportunities for improvement in ED management.

Routine semen analysis provides limited diagnostic and prognostic insight into male reproductive potential, contributing to the increasing use of sperm DNA fragmentation (SDF) testing in fertility evaluation. However, the clinical application of SDF testing appears to outpace the strength and consistency of the supporting evidence. This opinion paper critically appraises SDF testing through established screening, diagnostic, and prognostic test-performance frameworks, drawing on published observational studies, meta-analyses, and international guideline statements across natural conception and ART. The available evidence indicates that SDF testing does not meet the criteria for population-level screening or for routine diagnostic or prognostic use in unselected infertile populations and is frequently applied beyond its validated scope. Interpretation is further limited by assay heterogeneity, lack of standardization, variable thresholds, reliance on surrogate outcomes, and the limited effectiveness of available interventions. Routine implementation therefore risks overdiagnosis, unnecessary interventions, and premature escalation to assisted reproduction without proven benefit. When applied selectively within an aetiology-driven framework, particularly in defined subgroups, SDF testing may provide adjunctive risk stratification rather than deterministic clinical guidance. All stakeholders must be made aware of these limitations before the test is offered, interpreted, or used to modify treatment.

This study aimed to assess the knowledge, attitudes, and practices (KAP) of anesthesiology healthcare professionals concerning crisis resource management (CRM). A cross-sectional survey was conducted in Shanghai between November 20, 2024, and December 31, 2024. Data were collected using a self-developed questionnaire in Chinese based on published CRM/ACRM evidence summaries and educational resources. A total of 407 valid responses were obtained, yielding a valid response rate of 93.14%. Among the respondents, 281 (69.04%) were affiliated with public tertiary hospitals, 174 (42.75%) were primarily based in the operating room (OR) versus other anesthesiology work settings, and 223 (54.79%) were physicians. The mean self-perceived familiarity (knowledge), attitude, and practice scores were 12.39 ± 3.47 (possible range: 0-20), 30.85 ± 4.74 (possible range: 8-40), and 36.18 ± 6.95 (possible range: 10-50), respectively. In the prespecified path analysis (SEM) using summed KAP scores, knowledge was significantly associated with attitude and practice in the prespecified path model, and attitude was significantly associated with practice; knowledge was also indirectly associated with practice through attitude within the theoretical model (all P < 0.001). Anesthesiology healthcare professionals demonstrated moderate levels of self-perceived knowledge, generally positive attitudes, and frequent CRM-related practices, with significant associations among these components. These findings suggest that CRM-related knowledge, attitudes, and practices are statistically associated within this cross-sectional framework, although causal relationships cannot be inferred.

Background/Objectives: Older adults are disproportionately affected by traumatic brain injuries (TBIs), representing a significant portion of TBI-related hospitalizations and deaths. The objective of this study was to evaluate the feasibility and effectiveness of BrainCheck (Braincheck, Inc., Austin, TX, USA), a digital cognitive assessment tool, in detecting acute TBI-related cognitive deficits in the context of dementia-related cognitive impairment in older adult emergency department (ED) patients. Methods: From March 2020 to November 2023, participants aged 65+ with mild TBI, as defined by the American College of Rehabilitation Medicine (ACRM) diagnostic criteria, and individuals with isolated orthopedic injuries were recruited from 14 U.S. type 1 and 2 trauma centers. After informed consent, each subject was assessed by well-validated neurocognitive tests to characterize pre- and postinjury cognitive status. The Clinical Dementia Rating (CDR) and Functional Activities Questionnaire (FAQ) were used to assess cognitive impairment, with the informant sections used to classify preinjury status. The Rivermead Post-Concussion Symptoms Questionnaire (RPQ16) was used to assess injury-related symptoms, and the tablet-based BrainCheck Battery was tested as a diagnostic platform for injury-related deficits across several functional domains. Spearman's correlation was used to assess BrainCheck's internal validity and its relationship with self-reported cognitive symptoms. Technology familiarity was self-reported on a 1 (lowest) to 5 (highest) Likert scale. ROC curves evaluated the tool's accuracy in identifying cognitive impairment associated with TBI in the context of pre-existing cognitive impairment. Results: For the 101 mTBI and 52 orthopedic trauma control patients, BrainCheck demonstrated strong internal validity, with significant correlations among its component tests, indicating its effectiveness in assessing cognitive impairment. However, low correlations with RPQ16 self-reported symptoms suggest that BrainCheck and the self-reported questionnaire assess different aspects of cognitive functions. Conclusions: While BrainCheck effectively identified cognitive impairment, the composite battery and scoring did not differentiate TBI and dementia. Technology familiarity did not affect test outcomes. BrainCheck is a useful tool for evaluating cognitive function in adults aged ≥ 65 years with and without TBI in ED settings.

Neuropsychologists are frequently asked to evaluate individuals following presumed mild traumatic brain injury (mTBI) and to communicate findings across clinical and forensic settings that rely on divergent diagnostic systems. This article provides an analytic review of major mTBI frameworks (American Congress of Rehabilitation Medicine [ACRM], Department of Veterans Affairs/Department of Defense [VA/DoD], Diagnostic and Statistical Manual of Mental Disorders-5-Text Revision [DSM-5-TR], International Classification of Diseases 11th Revision [ICD-11], and Concussion in Sport Group [CISG]), emphasizing their differing evidentiary thresholds and intended uses. Particular attention is given to retrospective determinations, gaps in acute documentation, and medicolegal constraints. Evidence is reviewed regarding diagnostic uncertainty, emergency department under recognition, construct boundaries between injury and sequelae, and reliance on historical markers such as loss of consciousness, posttraumatic amnesia, and altered mental status. Intimate partner violence-related brain injury and non-fatal strangulation illustrate mechanistic complexity that strains current criteria. Emerging blood-based biomarkers (GFAP, UCH-L1, NfL, S100B) are evaluated as adjunctive tools when imaging is normal. The scope of neuropsychological opinion under Daubert, Joiner, and Kumho is clarified, distinguishing functional assessment from retrospective causal inference. Across systems, apparent disagreements between experts often reflect mismatches between framework demands and available data. Recommendations emphasize explicit declaration of framework use, transparent articulation of inferential limits, and cautious integration of adjunctive methods that are time-sensitive and mechanism-aware.

In 2023, the American Congress of Rehabilitation Medicine Brain Injury Interdisciplinary Special Interest Group (ACRM BI-ISIG) Mild Traumatic Brain Injury (TBI) Task Force published updated diagnostic criteria for mild TBI. These criteria were developed in collaboration with a panel of 32 subject matter experts in mild TBI using the Delphi method. The 2023 ACRM diagnostic criteria marked the first update since 1993, incorporating three decades of research advancements in our understanding of mild TBI. To facilitate the consistent use of the new diagnostic criteria, the ACRM BI-ISIG Mild TBI Task Force initiated a special project in September 2023 to develop a structured interview to apply the ACRM diagnostic criteria for mild TBI in clinical and research settings. The purpose of this article is to describe the development of the ACRM Structured TBI Interview and the accompanying documents. The ACRM Structured TBI Interview was developed in four phases: (1) initial development of a draft interview by two project leads, (2) review and revision over three rounds by 17 members of the ACRM BI-ISIG Mild TBI Task Force, (3) external review by 19 subject matter experts in mild TBI, and (4) field testing of the ACRM Structured TBI Interview by 11 interviewers who completed 25 diagnostic interviews. In addition to the ACRM Structured TBI Interview, three other documents were developed to help facilitate the administration of the interview (Administration Guide) and to apply the diagnostic criteria (Diagnostic Coding Form and Diagnostic Flow Diagram). A Short Form was also developed for use in contexts where administering the full structured interview is not feasible due to time constraints.

The new American Congress of Rehabilitation Medicine diagnostic criteria for mild traumatic brain injury (mTBI) were published in 2023. The criteria are designed to be used across clinical settings. This article discusses some medical-legal issues and implications relating to the use of the new ACRM diagnostic criteria. First, the new criteria differ from previously published definitions. Second, the criteria can be applied weeks, months, or years after an injury through a clinical interview and review of records. Third, when there is diagnostic uncertainty, and the "suspected" mTBI classification is used, this is not meant to convey a level of diagnostic certainty, from a medical-legal perspective. Fourth, the diagnostic process could be influenced by subjectivity or biases on the part of the person or the examiner. Finally, the new criteria are diagnostic, not prognostic. They are designed to determine whether a person sustained an mTBI, but they are not designed to determine if a person's health problems months or years after an injury are related to that injury.

Objective.Computed tomography (CT) is a crucial medical imaging technique which uses x-ray radiation to identify cancer tissues. Since radiation poses a significant health risk, low dose acquisition procedures need to be adopted. However, low-dose CT (LDCT) can cause higher noise and artifacts which massively degrade the diagnosis.Approach.To denoise LDCT images more effectively, this paper proposes a deep learning method based on U-Net with multiple lightweight attention-based modules and residual reinforcement (MLAR-UNet). We integrate a U-Net architecture with several advanced modules, including Convolutional Block Attention Module (CBAM), Cross Residual Module (CR), Attention Cross Reinforcement Module (ACRM), and Convolution and Transformer Cross Attention Module (CTCAM). Among these modules, CBAM applies channel and spatial attention mechanisms to enhance local feature representation. However, serious detail loss caused by incorrect embedding of CBAM for LDCT denoising is verified in this study. To relieve this, we introduce CR to reduce information loss in deeper layers, preserving features more effectively. To address the excessive local attention of CBAM, we design ACRM, which incorporates Transformer to adjust the attention weights. Furthermore, we design CTCAM, which leverages a complex combination of Transformer and convolution to capture multi-scale information and compute more accurate attention weights.Results.Experiments verify the embedding rationality and validity of each module and show that the proposed MLAR-UNet denoises LDCT images more effectively and preserves more details than many state-of-the-art methods on clinical chest and abdominal CT datasets.Significance.The proposed MLAR-UNet not only demonstrates superior LDCT image denoising capability but also highlights the strong detail comprehension and negligible overheads of our designed ACRM and CTCAM. These findings provide a novel approach to integrating Transformer more efficiently in image processing.