Citations

Abstract Background Poor operating room (OR) ergonomics poses risk of injury to OR staff, worsening patient outcomes and threatening workforce wellness and sustainability. How OR staff navigate ergonomic barriers in the interdisciplinary team environment was examined in this qualitative study. Methods Semi-structured, open-ended interviews of surgeons, anaesthesiologists, and OR nurses were conducted at a single institution using a sociomaterial approach with interview-to-the-double. Transcripts were coded by two independent researchers. Themes in the data were outlined using the System Engineering Initiative for Patient Safety (SEIPS) 2.0 framework. Results Five major themes were identified. First, physical environment issues creating cognitive and physical frictions, such as tripping hazards and poor room layouts. Second, influence of social positionality, with hierarchy by role and experience and social dynamics leading to a differential capacity to adjust. Third, team collaboration, with lack of interdisciplinary work and communication and high staff turnover. Fourth, burden of self-initiated workarounds, outlining conflicts between system/organizational issues and individual solutions. Fifth, institutional support, with lack of leadership engagement. Participants suggested solutions including accommodations to foster a collaborative approach to managing discomfort in the OR and new team communication tools. Conclusion Ergonomic barriers were described within the work system of the SEIPS 2.0 framework. Social positionality and differential levels of agency, as well as lack of team collaboration and misperceptions of others’ roles, were central to ergonomic challenges. Conflicts between problems lying with the system/organization and solutions being left to individuals were also central to challenges to optimal OR ergonomics.

Background: The origin of arthrofibrosis of the knee is multifactorial; however, it is more commonly seen in patients with arthritis, prolonged immobility, or a history of trauma or surgery to the knee. Arthrofibrosis that results in a flexion contracture of the knee is commonly attributable to scarring and shortening of the posterior joint capsule as seen in the setting of operative intervention, such as anterior cruciate ligament reconstruction (ACLR). Indications: Arthroscopic posterior capsular releases of the knee are indicated in patients with recalcitrant arthrofibrosis who have (1) failed nonoperative management and (2) a flexion contracture of ≥10°. Technique Description: This arthroscopic technique utilizes posteromedial and posterolateral portals in addition to the standard anteromedial and anterolateral portals. A transpatellar tendon portal may also be used to create the posterolateral portal. Both a 30° and a 70° arthroscope are used to better visualize the posteromedial and posterolateral inferior and superior releases. In addition to releases of the capsule both inferiorly and posteriorly, the medial and lateral gastrocnemius tendons can be partially released from the femur to allow for a more adequate release. The 70° arthroscope is necessary to access the capsule posterior to the posterior cruciate ligament to ensure complete release. Results: This procedure is typically reserved for patients who have failed conservative management with extension splinting, physical therapy, and the use of corticosteroids. Persistent arthrofibrosis with flexion contracture can occur after ACLR, with an incidence as high as 38% in some series. The specific technique described in this video has documented patient-reported outcomes of achieving full extension in >90% of patients after an arthroscopic posterior capsular release at final follow-up. Discussion/Conclusion: Recalcitrant arthrofibrosis leading to a persisting extension deficit can be devastating for a patient, as it results in increased pain and stiffness, as well as a significant decrease in functionality. Performing a posterior capsular release in addition to the standard manipulation under anesthesia and lysis of adhesions/synovectomy will allow for greater knee range of motion, particularly greater knee extension. Patient Consent Disclosure Statement: The author(s) attests that consent has been obtained from any patient(s) appearing in this publication. If the individual may be identifiable, the author(s) has included a statement of release or other written form of approval from the patient(s) with this submission for publication.

Background: Matching techniques such as direct covariate matching and propensity score matching (PSM) are increasingly used in anterior cruciate ligament reconstruction (ACLR) research to reduce bias in observational study designs. However, the rationale for covariate selection, consistency in methodological reporting, and patterns of matching practices remain unclear. Purpose: To systematically evaluate covariate matching practices in ACLR literature, including the types and number of covariates used, methodological transparency, and trends in matching strategies. Study Design: Systematic review. Methods: A systematic literature search of the PubMed, EMBASE, and Cochrane databases was conducted to evaluate covariate matching practices in the ACLR literature. A comprehensive search identified 798 unique studies, of which 97 met eligibility criteria. Data were extracted on study design, matching technique, covariate inclusion, reporting practices, and matching ratios. Descriptive and comparative statistics were used to summarize trends. Results: The 97 included studies encompassed 91,165 ACLRs. Most studies were retrospective (90.7%) and cohort in design (92.8%). PSM was used in 41 studies (42.3%), while 56 (57.7%) used direct matching. A total of 60 unique covariates were used across 76 different combinations. PSM studies used significantly more covariates than direct matching studies (6.17 ± 2.79 vs 3.75 ± 1.63; P < .0001), and database studies used more covariates than single-center studies (6.33 ± 2.89 vs 4.08 ± 1.96; P < .0001). The most commonly used covariates were age (96.9%), sex (84.5%), and body mass index (41.2%). Only 6 studies (6.2%) provided justification for covariate selection. The most frequent matching ratio was 1:1 (73.2%). While most studies reported descriptive statistics after matching (95.9%), only 10.3% did so before matching, and 13.4% failed to report prematching sample size. Conclusion: Matching practices in ACLR studies remain highly variable, with limited justification provided for covariate selection. PSM and database-based studies tend to incorporate a greater number of covariates, yet reporting of matching methodology is often inconsistent. To enhance the quality, reproducibility, and comparability of ACLR research, future studies should adopt standardized reporting practices for matching, including explicit descriptions of covariate selection, matching algorithms, balance diagnostics, and match ratios. These steps can serve as a foundation for a more unified research framework, enabling future studies to collectively generate higher quality, generalizable evidence for ACLR outcomes.

Primary care is a language-intensive environment where clinicians frequently synthesize, document, and communicate large amounts of information. Given the amount of information in primary care, large language models (LLMs) have emerged as tools to support primary care clinician workflows, aiming to reduce administrative burden and augment patient care. LLMs are artificial intelligence tools that can generate text and assist with chart summarization, message drafting, and clinical decision support. However, because LLMs are probabilistic, identical inputs may yield inconsistent responses. The LLMs output can be significantly improved through prompt engineering. Prompt engineering is the intentional design of text entered into the LLM to help produce better LLM results. Prompting is best approached as an iterative process where a clinician defines the task, the LLM generates output, and the clinician critically reviews and refines the results. Low-quality prompts are often vague and produce generic or misleading responses. High-quality prompts are specific, context-rich, and well-structured. Using structured prompting frameworks can improve the LLMs response. Including core elements, such as the LLMs role, the clinical context, the requested task, and the desired output formatting, can help improve the LLMs response by providing situational background and framing response formatting. Additional frameworks, such as Ask-Context-Expectation and PICO+O, can be utilized for specific patient circumstances and cases. However, despite their promise, LLMs have important limitations. They may generate inaccurate or hallucinated information and produce inconsistent results. Given these limitations, LLMs should not be viewed as knowledge authorities but rather as cognitive assistants. Thoughtful prompt design can help reduce these limitations and improve response accuracy, always keeping in mind that LLMs should not replace human judgment or clinical reasoning. As LLMs continue to be integrated into primary care, prompt engineering will become an increasingly important clinical skill. Careful prompt design and critical appraisal of LLM responses will be key to maintaining excellent patient care in the AI era.

Abstract How glial cells sense and regulate neuronal hypoactivity remains poorly understood. Using in vivo imaging in anesthetized, sleeping, and behaving mice, we identified a glial purinergic signaling mechanism that converts neuronal hypoactivity into local circuit regulation. Cortical hypoactivity increased spatially confined ATP release through astrocytic pannexin-1 hemichannels, which were structurally enriched near perisomatic parvalbumin-positive boutons. Local ATP release directed microglial process movement and stabilized bulbous endings through microglial P2Y12 signaling, accompanied by localized Ca²⁺ activity in microglial processes. Disruption of astrocytic pannexin-1 or microglial P2Y12 impaired bulbous-ending stabilization and abolished rebound increases in neuronal activity during emergence from anesthesia. Similar ATP release and bulbous-ending formation were observed during chemogenetic neuronal silencing or natural sleep in freely behaving mice. These findings identify astrocyte-to-microglia purinergic signaling as a mechanism that converts neuronal hypoactivity into synapse-selective microglial regulation of circuit activity.

Background/Objectives: To develop and evaluate a deep learning-based quality control system for Lumbar Spinal Digital Radiographs (LSDR), designed to automate and improve their evaluation and reduce reliance on manual reviews. Methods: This retrospective study utilized a deep learning workflow comprising image segmentation, feature extraction, and a classification model. The dataset, including anteroposterior (AP) and lateral (LAT) X-ray images, was expanded through data augmentation techniques. Four U-Net-based models were assessed: standard U-Net, Swin-UNet, Attention U-Net, and Attention U-Net with the weight map, with the latter selected for its superior performance. Extracted features, such as brightness, contrast, and anatomical positioning, were used in an XGBoost classifier, which was evaluated using mean intersection over union (mIoU), accuracy, sensitivity, specificity, and AUC. Results: The Attention U-Net with weighted attention outperformed the other models, achieving high mIoU scores in both AP and LAT views. The XGBoost classifier achieved the best performance in classifying images as “qualified” or “unqualified,” with an AUC of approximately 0.9, high accuracy, and balanced sensitivity and specificity. This approach effectively addressed class imbalances and improved model accuracy compared to traditional machine learning models such as MLP and SVM. Conclusions: The developed automated quality control system demonstrated potential for enhancing image quality, enhancing diagnostic reliability, and optimizing clinical workflow efficiency.

Immune-mediated epilepsies represent an etiologically unique category defined by immune activation within the central nervous system that initiates a pathophysiological cascade resulting in seizures, encephalopathy, and sometimes epileptogenesis with long-term epilepsy. Once considered rare and largely confined to paraneoplastic or postinfectious syndromes, immune-mediated and inflammatory mechanisms are now recognized across a broad spectrum ranging from acute autoimmune encephalitis with reversible seizures, new-onset refractory status epilepticus, or febrile illness-related refractory status epilepticus, to chronic autoimmune-associated epilepsy and drug-refractory structural epilepsies. This review integrates historical perspectives, mechanistic insights from animal and human studies, and contemporary clinical frameworks. It synthesizes advances in neuroimmunology, clinical phenotyping, diagnostics, immunomodulatory and antiseizure therapies, neuromodulation, and patient and family centered outcomes, and outlines future directions focused on biomarker-driven precision medicine, disease-modifying strategies, and interdisciplinary care models.