Comparative effect of nonpharmacological interventions on emergence delirium prevention in children following sevoflurane general anesthesia: A systematic review and network meta-analysis of randomized controlled trials

BACKGROUND

Children receiving general anesthesia while undergoing surgery have a significantly high incidence of emergence delirium (ED). Nonpharmacological interventions yield beneficial effects on preventing pediatric ED. However, the relative effects of nonpharmacological interventions on pediatric ED prevention based on various perioperative phases remain unknown.

OBJECTIVE

To compare the effects of nonpharmacological interventions on pediatric ED prevention at different surgical phases.

DESIGN

A systematic review and network meta-analysis.

DATA SOURCES

A comprehensive search of five electronic databases (PubMed, CINAHL via EBSCOhost, Embase via Elsevier, Cochrane Trials, and ProQuest Dissertations and theses) for identifying randomized control trials published from inception to October 15, 2023.

METHODS

Two reviewers independently screened, assessed, and extracted data from the eligible studies. A random-effects network meta-analysis was used to determine the comparative effect of nonpharmacological interventions on preventing pediatric ED.

RESULTS

A total of 19 studies involving 2522 children were included in this network meta-analysis. Thirteen studies reported on the prevention of pediatric ED in the preoperative phase, and six studies reported on the prevention of pediatric ED in the intraoperative phases. Multimedia devices (OR 0.39, 95 % CIs 0.20-0.74), a multicomponent program (OR 0.20, 95 % CI 0.14-0.28) significantly reduced the incidence of pediatric ED during the preoperative phase compared with usual care. During the intraoperative phase, listening to regular heartbeat sounds significantly reduced the risk of pediatric ED compared with usual care (OR 0.06, 95 % CI 0.02-0.22), placebo (OR 0.11, 95 % CI 0.03-0.36), acupuncture (OR 0.17, 95 % CI 0.03-0.88), acupuncture with electrical stimulus (OR 0.16, 95 % CI 0.04-0.68), and acupuncture with midazolam (OR 0.04, 95 % CI 0.00-0.41).

CONCLUSIONS

Our study results suggest that the multicomponent program and listening to heartbeat sounds are relatively effective nonpharmacological interventions for preventing pediatric ED during the perioperative phase. This study compared the effectiveness and ranking of various interventions, and the findings can serve as a guide to assist health professionals in choosing the optimal strategy for preventing ED.

REGISTRATION

The study protocol was registered at PROSPERO (CRD42023459541).

TWEETABLE ABSTRACT

Nonpharmacological interventions can reduce the high incidence of pediatric emergence delirium after surgery. Our systematic review highlights the efficacy of multicomponent programs and listening to heartbeat sounds intraoperatively in reducing ED risk. The findings aid health professionals in selecting optimal strategies for pediatric perioperative care.

Dare 2 Discuss social media campaign: An educational initiative to improve opioid use disorder discussions between the pharmacist and patient

BACKGROUND

Opioid use disorder (OUD) is a chronic substance use disorder that currently results in significant morbidity and mortality within the United States. The Opioid and Naloxone Education program is a pharmacy-centered opioid risk screening process to identify patients at risk for OUD and opioid overdose. Three years after inception, data indicated patients screened as high-risk for OUD were receiving opioid safety interventions; however the evaluation noted a lack of OUD education with patients.

OBJECTIVE

To describe and assess an educational initiative for pharmacists which is delivered via social media for the improvement of pharmacist-patient communication surrounding OUD education.

METHODS

The initiative was named 'Dare 2 Discuss' and video content was developed to align with prior research citing challenges to health care provider-patient OUD education. Data to evaluate pharmacist interventions/education delivered to patients was collected by a pharmacy services documentation platform and social media performance was captured by each respective social media dashboard.

RESULTS

The first video was posted on October 1, 2022 and the last video was posted on April 10, 2023. Each video took approximately 2.5 hours to create and averaged 42 seconds in length (17-168 seconds). On average, videos received 233 Facebook views (55-489 views) and 527 Instagram views (232-1434 views). The postintervention phase indicated that patient receipt of OUD education by the pharmacist increased by 23% and patient receipt of community support services information increased by 68%.

CONCLUSION

'Dare 2 Discuss' campaign may have improved pharmacist self-efficacy with subsequent adjustment of patient education techniques when addressing OUD conversations. These findings highlight the feasibility of a social media-delivered educational initiative to have a potential impact on factors associated with the opioid crisis and risk-reduction education by pharmacists. Creating relevant and easy-to-digest educational materials for health professionals is an important step in advancing practice and improving patient care. Results from the Dare 2 Discuss campaign suggest that this educational initiative may be an effective method to reach a broad number of pharmacists to improve patient interactions.

Impact of ChatGPT and Large Language Models on Radiology Education: Association of Academic Radiology-Radiology Research Alliance Task Force White Paper

Generative artificial intelligence, including large language models (LLMs), holds immense potential to enhance healthcare, medical education, and health research. Recognizing the transformative opportunities and potential risks afforded by LLMs, the Association of Academic Radiology-Radiology Research Alliance convened a task force to explore the promise and pitfalls of using LLMs such as ChatGPT in radiology. This white paper explores the impact of LLMs on radiology education, highlighting their potential to enrich curriculum development, teaching and learning, and learner assessment. Despite these advantages, the implementation of LLMs presents challenges, including limits on accuracy and transparency, the risk of misinformation, data privacy issues, and potential biases, which must be carefully considered. We provide recommendations for the successful integration of LLMs and LLM-based educational tools into radiology education programs, emphasizing assessment of the technological readiness of LLMs for specific use cases, structured planning, regular evaluation, faculty development, increased training opportunities, academic-industry collaboration, and research on best practices for employing LLMs in education.

German surgeons' perspective on the application of artificial intelligence in clinical decision-making

PURPOSE

Artificial intelligence (AI) is transforming clinical decision-making (CDM). This application of AI should be a conscious choice to avoid technological determinism. The surgeons' perspective is needed to guide further implementation.

METHODS

We conducted an online survey among German surgeons, focusing on digitalization and AI in CDM, specifically for acute abdominal pain (AAP). The survey included Likert items and scales.

RESULTS

We analyzed 263 responses. Seventy-one percentage of participants were male, with a median age of 49 years (IQR 41-57). Seventy-three percentage of participants carried out a senior role, with a median of 22 years of work experience (IQR 13-28). AI in CDM was seen as helpful for workload management (48%) but not for preventing unnecessary treatments (32%). Safety (95%), evidence (94%), and usability (96%) were prioritized over costs (43%) for the implementation. Concerns included the loss of practical CDM skills (81%) and ethical issues like transparency (52%), patient trust (45%), and physician integrity (44%). Traditional CDM for AAP was seen as experience-based (93%) and not standardized (31%), whereas AI was perceived to assist with urgency triage (60%) and resource management (59%). On median, generation Y showed more confidence in AI for CDM (P = 0.001), while participants working in primary care hospitals were less confident (P = 0.021).

CONCLUSION

Participants saw the potential of AI for organizational tasks but are hesitant about its use in CDM. Concerns about trust and performance need to be addressed through education and critical evaluation. In the future, AI might provide sufficient decision support but will not replace the human component.

Recent Advances in Ionic Mechanisms in Pituitary Cells: Implications for Electrophysiological and Electropharmacological Research

Pituitary cells are specialized cells located within the pituitary gland, a small, pea-sized gland situated at the base of the brain. Through the use of cellular electrophysiological techniques, the electrical properties of these cells have been revealed. This review paper aims to introduce the ion currents that are known to be functionally expressed in pituitary cells. These currents include a voltage-gated Na+ current (INa), erg-mediated K+ current (IK(erg)), M-type K+ current (IK(M)), hyperpolarization-activated cation current (Ih), and large-conductance Ca2+-activated K+ (BKCa) channel. The biophysical characteristics of the respective ion current were described. Additionally, we also provide explanations for the effect of various drugs or compounds on each of these currents. GH3-cell exposure to GV-58 can increase the magnitude of INa with a concurrent rise in the inactivation time constant of the current. The presence of esaxerenone, an antagonist of the aldosterone receptor, directly suppresses the magnitude of peak and late INa. Risperidone, an atypical antipsychotic agent, is effective at suppressing the IK(erg) amplitude directly, and di(2-ethylhexyl)-phthalate suppressed IK(erg). Solifenacin and kynurenic acid can interact with the KM channel to stimulate IK(M), while carisbamate and cannabidiol inhibit the Ih amplitude activated by sustained hyperpolarization. Moreover, the presence of either rufinamide or QO-40 can enhance the activity of single BKCa channels. To summarize, alterations in ion currents within native pituitary cells or pituitary tumor cells can influence their functional activity, particularly in processes like stimulus-secretion coupling. The effects of small-molecule modulators, as demonstrated here, bear significance in clinical, therapeutic, and toxicological contexts.

Evaluation of Hidden Blood Loss and Clinical Outcomes of Arthroscopy-Assisted Uni-Portal Spinal Surgery for Lumbar Disc Herniation with Lateral Recess Stenosis

OBJECTIVE

This study aims to evaluate hidden blood loss (HBL) and its influencing factors in patients with lumbar disc herniation-related lateral recess stenosis who underwent arthroscopy-assisted uni-portal spinal surgery (AUSS). Additionally, the study assesses clinical outcomes at the 6-month postoperative follow-up.

METHODS

This study included 129 patients with lumbar disc herniation-associated lateral recess stenosis who underwent AUSS during the year 2024. Demographic data and parameters related to blood loss were recorded. HBL was calculated using the Nadler and Gross formulas. Pearson or Spearman correlation analyses were performed to explore the relationships between patient characteristics and HBL. Multiple linear regression analysis was used to identify independent risk factors for HBL. Primary clinical outcomes (visual analog scale scores) and secondary outcomes (Oswestry Disability Index scores and the modified Macnab criteria) were assessed preoperatively and at 3 days, 3 months, and 6 months postoperatively. Longitudinal data were analyzed using generalized mixed linear models.

RESULTS

A total of 129 consecutive patients (66 females and 63 males) were enrolled. The average HBL was 414.34 ± 179.15 ml. Correlation analyses (Pearson and Spearman) revealed significant associations between surgical duration, American Society of Anesthesiologists (ASA) score, muscle thickness, preoperative activated partial thromboplastin time, and preoperative D-dimer with HBL (P < 0.05). Multiple linear regression analysis identified surgical duration and ASA score as independent risk factors for HBL. Postoperative visual analog scale and Oswestry Disability Index scores showed significant improvement compared to preoperative values.

CONCLUSIONS

The amount of HBL in patients undergoing AUSS should not be underestimated. ASA score and surgical duration are independent risk factors for HBL. AUSS, as an improved technique, significantly alleviates postoperative pain and enhances quality of life, demonstrating good short-term clinical efficacy. It is an effective treatment option for lateral recess stenosis caused by lumbar disc herniation.

Mutational status of RAS, SMAD4 and APC predicts survival after resection of colorectal liver metastases in Chinese patients: prognostic stratification based on genetic sequencing data of multiple somatic genes

BACKGROUND

This study aimed to investigate the impact of the mutational status of multiple genes on survival in Chinese patients with colorectal liver metastases (CRLM) undergoing liver resection.

METHODS

This study included 519 Chinese patients undergoing curative liver resection for CRLM between 2011 and 2021 and had genomic sequencing data of 620 genes available for analysis. The genes associated with overall survival (OS) were identified using Cox regression analyses. The patients were stratified according to a novel scoring system based on the number of genes with a deleterious status (mutation or wild type), and OS was compared among the groups. The prognostic capacity of the scoring system was assessed using Harrell's C-index.

RESULTS

Twelve genes were mutated in more than 10% of the patients. RAS mutation, SMAD4 mutation, and APC wild-type status were significantly associated with worse OS. A scoring system was built based on the mutational status of RAS, SMAD4, and APC. Higher scores were significantly associated with worse OS (HR > 1, p < 0.05, for any two groups), and the patients with a score of 3 had poor survival with a median OS of only 17.1 months. The scoring system demonstrated moderate discriminative capacity (Harrell's C-index = 0.627).

CONCLUSIONS

In Chinese patients, the mutational status of RAS, SMAD4, and APC was significantly associated with survival after CRLM resection. The three-gene scoring system provided information on prognostic stratification for survival, which can be used to improve precision surgery for CRLM.

Risk Factors and Prevention of Cancer and CVDs: A Chicken and Egg Situation

Cardiovascular diseases and cancer are the two primary causes of mortality worldwide. Although traditionally regarded as distinct pathologies, they share numerous pathophysiological mechanisms and risk factors, including chronic inflammation, insulin resistance, obesity, and metabolic dysregulation. Notably, several cancers have been identified as closely linked to cardiovascular diseases, including lung, breast, prostate, and colorectal cancers, as well as hematological malignancies, such as leukemia and lymphoma. Additionally, renal and pancreatic cancers exhibit a significant association with cardiovascular complications, partly due to shared risk factors and the cardiotoxic effects of cancer therapies. Addressing the overlapping risk factors through lifestyle modifications-such as regular physical activity, a balanced diet, and cessation of smoking and alcohol-has proven effective in reducing both CV and oncological morbidity and mortality. Furthermore, even in patients with established cancer, structured interventions targeting physical activity, nutritional optimization, and smoking cessation have been associated with improved outcomes. Beyond lifestyle modifications, pharmacological strategies play a crucial role in the prevention of both diseases. Several cardiovascular medications, including statins, aspirin, beta-blockers, and metformin, exhibit pleiotropic effects that extend beyond their primary indications, demonstrating potential anti-neoplastic properties in preclinical and observational studies. Recently, novel therapeutic agents have garnered attention for their possible cardioprotective and metabolic benefits. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT2is), initially developed for managing type 2 diabetes, have shown CV and renal protective effects, alongside emerging evidence of their role in modulating cancer-related metabolic pathways. Inclisiran, a small interfering RNA targeting PCSK9, effectively lowers LDL cholesterol and may contribute to reducing CV risk, with potential implications for tumor biology. Additionally, sacubitril/valsartan, an angiotensin receptor-neprilysin inhibitor, has revolutionized heart failure management by improving hemodynamic parameters and exerting anti-inflammatory effects that may have broader implications for chronic disease prevention. Given the intricate interplay between CVD and cancer, further research is essential to clarify the exact mechanisms linking these conditions and assessing the potential of CV therapies in cancer prevention. This review aims to examine shared risk factors, consider the role of pharmacological and lifestyle interventions, and emphasize crucial epidemiological and mechanistic insights into the intersection of CV and oncological health.

Neuro-Nutritional Approach to Neuropathic Pain Management: A Critical Review

Pain is a significant global public health issue that can interfere with daily activities, sleep, and interpersonal relationships when it becomes chronic or worsens, ultimately impairing quality of life. Despite ongoing efforts, the efficacy of pain treatments in improving outcomes for patients remains limited. At present, the challenge lies in developing a personalized care and management plan that helps to maintain patient activity levels and effectively manages pain. Neuropathic pain is a chronic condition resulting from damage to the somatosensory nervous system, significantly impacting quality of life. It is partly thought to be caused by inflammation and oxidative stress, and clinical research has suggested a link between this condition and diet. However, these links are not yet well understood and require further investigation to evaluate the pathways involved in neuropathic pain. Specifically, the question remains whether supplementation with dietary antioxidants, such as melatonin, could serve as a potential adjunctive treatment for neuropathic pain modulation. Melatonin, primarily secreted by the pineal gland but also produced by other systems such as the digestive system, is known for its anti-inflammatory, antioxidant, and anti-aging properties. It is found in various fruits and vegetables, and its presence alongside other polyphenols in these foods may enhance melatonin intake and contribute to improved health. The aim of this review is to provide an overview of neuropathic pain and examine the potential role of melatonin as an adjunctive treatment in a neuro-nutritional approach to pain management.

Quantum leap in medical mentorship: exploring ChatGPT's transition from textbooks to terabytes

ChatGPT, an advanced AI language model, presents a transformative opportunity in several fields including the medical education. This article examines the integration of ChatGPT into healthcare learning environments, exploring its potential to revolutionize knowledge acquisition, personalize education, support curriculum development, and enhance clinical reasoning. The AI's ability to swiftly access and synthesize medical information across various specialties offers significant value to students and professionals alike. It provides rapid answers to queries on medical theories, treatment guidelines, and diagnostic methods, potentially accelerating the learning curve. The paper emphasizes the necessity of verifying ChatGPT's outputs against authoritative medical sources. A key advantage highlighted is the AI's capacity to tailor learning experiences by assessing individual needs, accommodating diverse learning styles, and offering personalized feedback. The article also considers ChatGPT's role in shaping curricula and assessment techniques, suggesting that educators may need to adapt their methods to incorporate AI-driven learning tools. Additionally, it explores how ChatGPT could bolster clinical problem-solving through AI-powered simulations, fostering critical thinking and diagnostic acumen among students. While recognizing ChatGPT's transformative potential in medical education, the article stresses the importance of thoughtful implementation, continuous validation, and the establishment of protocols to ensure its responsible and effective application in healthcare education settings.

Propofol Dexmedetomidine Total Intravenous Anesthesia with Tumescent Anesthesia in Aesthetic surgery

BACKGROUND

Total intravenous anesthesia (TIVA) is commonly performed in ambulatory aesthetic surgery centers. The authors compared combination of TIVA and tumescent anesthesia for safety and efficacy in prolonged and successive multiple aesthetic procedures.

METHODS

A retrospective review of patients who underwent aesthetic surgery procedures under TIVA from 2016 through 2024 at the authors' aesthetic surgery center was conducted. Patients were included if they fulfilled ASA 1 or 2 staging, BMI < 45 and were of age between 12 and 80 years. Perioperative drug dosages, time under anesthesia and patient vitals were recorded.

RESULTS

Of the 307 patients assessed, 301 completed surgery under TIVA and 6 were converted to GA. No major morbidity was recorded and all 307 cases were discharged from Anesthesia Recovery at 6 hours post-surgery. Average duration of anesthesia time was highest for lipoabdominoplasty (278 min, range 170-360 min). Average dose of tumescent anesthesia was highest in excisional body contouring (2967 ml). No surgical morbidity, e.g., skin necrosis, hematoma and blood transfusion, was reported. No anesthetic morbidity, e.g., deep vein thrombosis, fat embolism and lignocaine toxicity, was reported. Mean arterial pressure and SpO2 were maintained in safe normal range (70-100 mm Hg and > 95%, respectively) up to 6 hours postoperative. Aldrete score for postoperative recovery was > =9 at 10 min for 80% cases (n= 245).

CONCLUSIONS

The analysis of 307 total intravenous anesthesia with tumescent anesthesia cases demonstrated the overall safety and efficacy of the propofol-dexmedetomidine protocol under deep sedation. The study underscores the importance of complete preoperative assessments, vigilant anesthetist-guided drug infusions and monitoring for complications.

LEVEL OF EVIDENCE III

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

A Retrospective Study of Intraoperative Awareness in Patients Undergoing Electroconvulsive Therapy at Dartmouth Hitchcock Medical Center Over a 3-Year Period

OBJECTIVE

At our academic institution, in a collaborative effort between the departments of anesthesiology, psychiatry, and nursing, we aimed to collect data about the incidence, nature, and predictive factors of intraoperative awareness in patients undergoing electroconvulsive therapy (ECT). Eligible patients were given modified Brice interviews, and the compliance rate of the interviews was analyzed and the effect of the educational initiatives put in place reviewed.

METHODS

Brice interviews were given to patients after ECT over a 3-year period, which included the education of staff. Data points were collected over this 3-year period via the electronic medical record for patients receiving ECT and those who were eligible to complete a Brice interview after procedure. Statistical analysis was conducted to meet our objectives.

RESULTS

The incidence of intraoperative awareness in our patients undergoing ECT was 4.7% (44 out of 936 interviews) and baseline characteristics were recorded. No predictors of intraoperative awareness were discovered. The nature of each positive interview was reviewed and put into categories, and anesthesia modification was reviewed for the positive interviews. Mental health after procedure was shown to be, by our measures, the same between patients with positive Brice interviews and patients with negative Brice interviews. The overall compliance rates of the modified Brice interview were analyzed, and to measure the impact of such initiatives, the compliance rates were compared before and after particular educational initiatives.

CONCLUSIONS

Our study underscores the importance of tracking intraoperative awareness in patients receiving ECT, using Brice interviews in this population, and executing quality initiatives in the departments involved.

Updated Review on Natural Polyphenols: Molecular Mechanisms, Biological Effects, and Clinical Applications for Cancer Management

Polyphenols, naturally occurring compounds found exclusively in plants, have gained significant attention for their potential in cancer prevention and treatment. These compounds are known for their antioxidant properties and are abundant in various plant-based foods, such as vegetables, fruits, grains, and beverages. Recent studies have highlighted the broad spectrum of health benefits of polyphenols, including their antiviral, anti-inflammatory, and anticancer properties. In addition, these naturally derived compounds are increasingly important for drug discovery due to their high molecular diversity and novel biofunctionalities. This review provides an in-depth analysis of the current research and knowledge on the potential use of dietary polyphenols as bioactive compounds for the prevention and treatment of various cancers. This review aims to provide valuable insights into the mechanisms underlying the anticancer properties of phenolic compounds in both laboratory and clinical settings. Furthermore, this review highlights the positive clinical outcomes associated with the use of polyphenols as anticancer agents and offers guidance for future research to advance this promising field.

Changes in cortical delta power during chronic invasive epilepsy monitoring

OBJECTIVE

Cortical delta band (1-4 Hz) activity is considered a biomarker for states of altered consciousness, with increased delta power observed during anesthesia, sleep, coma, and delirium. The current study sought to characterize delta power following electrode implantation with respect to patient demographics and clinical characteristics as well as type and duration of surgery.

METHODS

Participants were 25 adult neurosurgical patients implanted with intracranial electrodes for clinical monitoring of their epilepsy. Resting state cortical activity was recorded at multiple occasions over the course of the monitoring period. The initial time point was defined as the first recording within 72 h following surgery. Analyses of cortical activity were conducted using a linear mixed effects modeling approach to account for within-participant correlations and between-participant heterogeneity.

RESULTS

Throughout the monitoring period, delta power decreased in frontal, occipital, parietal, and temporal regions, indicating a global phenomenon. By contrast, beta (14-30 Hz) power remained stable. Delta power was higher following surgical cases that required craniotomy compared to stereoelectroencephalography cases. Surgery duration and anesthesia emergence duration were associated with higher delta power. Recordings from depth electrodes showed higher delta power compared to subdural electrodes. No significant effects of patients' age, sex, white blood cell count, antiseizure medication, and opioid medication dosage on postoperative delta power were found.

SIGNIFICANCE

The results are consistent with a postoperative elevation in delta power that resolves over the course of the monitoring period and indicate an association between increased delta power and craniotomy surgery, as well as longer surgery and emergence durations. The current work provides a comprehensive analysis of surgical, clinical, and physiological factors, suggests risk factors, and lays fundamental groundwork for future studies.

Therapeutic Effects of GLP-1 Receptor Agonists and DPP-4 Inhibitors in Neuropathic Pain: Mechanisms and Clinical Implications

Glucagon-like peptide-1 (GLP-1) is a peptide hormone secreted by the small intestine upon food intake. GLP-1 enhances insulin secretion, suppresses glucagon release, and promotes satiety, resulting in reduced food consumption and subsequent weight loss. Endogenous GLP-1 has a very short half-life and is rapidly degraded by the enzyme dipeptidyl-peptidase-IV (DPP-4). To address this limitation, GLP-1 receptor agonists (GLP-1RAs) and DPP-4 inhibitors (DPP-4is) were developed and have demonstrated potency in clinical practice. In recent years, GLP-1RA and DPP4-i therapies are known to have pleiotropic effects, such as a reduction in oxidative stress, autophagy regulation, metabolic reprogramming, enhancement of anti-inflammatory signaling, regulation of gene expression, and being neuroprotective. These effects imply a therapeutic perspective for GLP-1RA and DPP-4i therapies in neuropathic pain treatment. Preclinical and clinical studies increasingly support the hypothesis that these therapies may alleviate neuropathic pain by targeting multiple mechanisms that induce neuropathic pain, such as inflammation, oxidative stress, and mitochondrial dysfunction. This review explores the mechanisms by which GLP-1RAs and DPP-4is alleviate neuropathic pain. It also highlights current advancements in incretin research, focusing on the therapeutic effects of GLP-1RAs and DPP-4-is for neuropathic pain.

Single-Nucleotide Polymorphisms of BRCA1 and BRCA2 and Risk of Papillary Thyroid Carcinoma

Background/Objectives: We sought to evaluate the association between the risk of papillary thyroid carcinoma (PTC) and single-nucleotide polymorphisms (SNPs) of breast cancer genes 1 (BRCA1) and 2 (BRCA2). Methods: We prospectively recruited 515 cases with PTC and 296 controls without cancer. The genotypes of five BRCA1 SNPs (rs8176318, rs1799966, rs799917, rs16940, rs1799949) and three BRCA2 SNPs (rs15869, rs1799943, rs1799955) were determined using the TaqMan assay. We evaluated the association of haplotypes with the risk of PTC due to linkage disequilibrium (LD). Results: The five BRCA1 SNPs were significantly associated with the risk of PTC. The AC genotype of rs8176318 (OR = 0.69, p = 0.02) and the CT and CC genotypes of rs1799966 (OR = 0.70, p = 0.02 and OR = 0.67, p = 0.01, respectively) were associated with a decreased risk of PTC. The AG genotype of rs16940 (OR = 0.67, p = 0.01) and the AG genotypes of rs799917 and rs1799949 (both OR = 0.70, p = 0.02) decreased the risk of PTC. Haplotype 1 [rs8176318(C)-rs1799966(T)-rs799917(G)-rs16940(A)-rs1799949(G)] ± (OR = 0.69, p = 0.02) and haplotype 2 [rs8176318(A)-rs1799966(C)-rs799917(A)-rs16940(G)-rs1799949(A)] ± (OR = 0.71, p = 0.03) of BRCA1 reduced the risk of PTC. Conclusions: Our findings suggest that the polymorphisms of BRCA1 may contribute to the susceptibility to PTC in the Korean population.

Assessing artificial intelligence-generated patient discharge information for the emergency department: a pilot study

BACKGROUND

Effective patient discharge information (PDI) in emergency departments (EDs) is vital and often more crucial than the diagnosis itself. Patients who are well informed at discharge tend to be more satisfied and experience better health outcomes. The combination of written and verbal instructions tends to improve patient recall. However, creating written discharge materials is both time-consuming and costly. With the emergence of generative artificial intelligence (AI) and large language models (LMMs), there is potential for the efficient production of patient discharge documents. This study aimed to investigate several predefined key performance indicators (KPIs) of AI-generated patient discharge information.

METHODS

This study focused on three significant patients' complaints in the ED: nonspecific abdominal pain, nonspecific low back pain, and fever in children. To generate the brochures, we used an English query for ChatGPT using the GPT-4 LLM and DeepL software to translate the brochures to Dutch. Five KPIs were defined to assess these PDI brochures: quality, accessibility, clarity, correctness and usability. The brochures were evaluated for each KPI by 8 experienced emergency physicians using a rating scale from 1 (very poor) to 10 (excellent). To quantify the readability of the brochures, frequently used indices were employed: the Flesch Reading Ease, Flesch-Kincaid Grade Level, Simple Measure of Gobbledygook, and Coleman-Liau Index on the translated text.

RESULTS

The brochures generated by ChatGPT/GPT-4 were well received, scoring an average of 7 to 8 out of 10 across all evaluated aspects. However, the results also indicated a need for some revisions to perfect these documents. Readability analysis indicated that brochures require high school- to college-level comprehension, but this is likely an overestimation due to context-specific reasons as well as features inherent to the Dutch language.

CONCLUSION

Our findings indicate that AI tools such as LLM could represent a new opportunity to quickly produce patient discharge information brochures. However, human review and editing are essential to ensure accurate and reliable information. A follow-up study with more topics and validation in the intended population is necessary to assess their performance.

Advancing Head and Neck Cancer Therapies: From Conventional Treatments to Emerging Strategies

Head and neck cancers (HNCs), particularly head and neck squamous cell carcinoma (HNSCC), are among the most aggressive and prevalent malignancies of the upper aerodigestive tract. As the incidence of HNCs continues to rise, this cancer type presents a significant public health challenge. Despite conventional treatment options, such as surgery, chemotherapy, and radiotherapy, the five-year survival rates remain relatively low due to resistance to these therapies, local recurrence, local lymph node metastasis, and in some advanced cases also distant metastasis. Consequently, patients with HNCs face a high mortality risk and have reduced quality of life due to the side effects of chemo- and radiotherapy. Furthermore, targeted therapies and immunotherapies have also shown limited effectiveness in many cases, with issues related to resistance and the accessibility of these treatments. Therefore, new strategies, such as those based on combination therapies and nanotechnology, are being explored to improve the treatment of HNC patients. The proteolysis-targeting chimeras (PROTACs) also emerged as a promising therapeutic approach, though research is still ongoing to bring this technology into clinical practice. Here, we aim to highlight the current knowledge of HNC therapies, with a focus on recent advancements, including nanomedicine and PROTAC-based strategies. The development and advancement of novel emerging therapies hold promise for the improvement of patients' survival and quality of life.

Investigating Continuance Intention for Telehealth Visits in Children's Hospitals: Survey-Based Study

BACKGROUND

Telehealth visits are remote health care consultations conducted using digital technologies, such as video calls, phone calls, or web-based platforms. This type of service offers numerous benefits for both health care users and health care providers. Users save time and money by avoiding traveling to health care facilities. At the same time, health care providers can expand access to care for users in remote areas and enhance the continuity of care. These advantages are even more evident in pediatric settings, where attending in-person services must align with the commitments of the patient (eg, school activities) and the caregiver. Although the potential benefits of telehealth visits for users and health care providers were already known before the COVID-19 pandemic, its widespread adoption only occurred during it. Having experienced its benefits, hospitals are now, in the postpandemic phase, determined to maintain and strengthen their remote service offerings. It has, therefore, become crucial for them to understand the factors influencing users' intention to continue using telehealth visits (or "continuance intention"), even now after the access restrictions to health care facilities imposed during the COVID-19 pandemic have been lifted. However, the literature lacks comprehensive, valid, and reliable models explaining users' continuance intention toward telehealth visit services.

OBJECTIVE

This study aims to investigate the variables impacting users' continuance intention toward telehealth visits and identify suggestions for improvement.

METHODS

Two models of variables impacting users' continuance intention toward telehealth visits were developed. The first model applied to all users undergoing telehealth visits, while the second one applied only to patients who received a telehealth visit using videoconferencing tools. The models were created based on the literature and a qualitative study comprising interviews with physicians with extensive experience in telehealth visits. The models were then tested using partial least squares structural equation modeling on 477 responses obtained by administering a survey to guardians of patients who had received at least 1 telehealth visit in a major European children's hospital.

RESULTS

Both models showed that the variable information quality positively influenced the variables continuance intention and perceived usefulness and that perceived usefulness positively influenced continuance intention. The first model was robust to the medical specialty and the channel used to deliver the visit. The second model also showed that systems quality positively influenced information quality.

CONCLUSIONS

This study has identified and tested 2 comprehensive, valid, and reliable models on the variables influencing users' continuance intention toward telehealth visits. Moreover, the study's results provide insights for hospitals to improve telehealth visit services.

A probabilistic model of behavioural emergence from general anaesthesia in mice

BACKGROUND

Time to emergence from general anaesthesia is highly variable between individuals. This variability has been attributed to individual differences in anaesthetic sensitivity. However, this hypothesis has not been verified experimentally. We explicitly test this hypothesis by quantifying emergence from anaesthesia repeatedly in the same individuals over time.

METHODS

Genetically identical adult (12-24 weeks old) male (n=40) and female (n=20) C57BL/6J mice were exposed to 2 h of isoflurane (0.90 vol%) on 10 separate occasions. Time to emergence was measured using the return of the righting reflex. Predictions of the standard effect-site pharmacokinetic-pharmacodynamic (PK-PD) model and neuronal dynamics model of stochastic fluctuations between the awake and anaesthetised states were fit to observed emergence times. Repeated steady-state assessments of the righting reflex obtained during the last 2 h of a 4-h exposure to 0.3, 0.4, 0.6, or 0.7 vol% isoflurane (n=20 per concentration) were used to determine individual probabilities of losing the righting reflex, which was defined as an individual's anaesthetic sensitivity.

RESULTS

Emergence times varied by at least two orders of magnitude after identical anaesthetic exposure. We did not find consistent inter-individual differences in emergence times. Instead, we found that variability in emergence times across trials in each individual was as large as that between two different individuals. Emergence times were not correlated across time. Consistent with previous work, we identified large individual differences in anaesthetic sensitivity which persisted on a time scale of at least 1 week. A standard PK-PD model failed to reproduce inter-trial variability. In contrast, the neuronal dynamics model reproduced both population- and individual-level variability in emergence times.

CONCLUSIONS

Stochastic state switching contributes to inherent variability in emergence from general anaesthesia. Delayed emergence occurred in a small proportion of anaesthetic exposures in a genetically homogeneous population. The neuronal dynamics model predicts that anaesthetic emergence times will be probabilistically long, which might explain delayed emergence observed in clinical settings.

Status and opportunities of machine learning applications in obstructive sleep apnea: A narrative review

Background

Obstructive sleep apnea (OSA) is a prevalent and potentially severe sleep disorder characterized by repeated interruptions in breathing during sleep. Machine learning models have been increasingly applied in various aspects of OSA research, including diagnosis, treatment optimization, and developing biomarkers for endotypes and disease mechanisms.

Objective

This narrative review evaluates the application of machine learning in OSA research, focusing on model performance, dataset characteristics, demographic representation, and validation strategies. We aim to identify trends and gaps to guide future research and improve clinical decision-making that leverages machine learning.

Methods

This narrative review examines data extracted from 254 scientific publications published in the PubMed database between January 2018 and March 2023. Studies were categorized by machine learning applications, models, tasks, validation metrics, data sources, and demographics.

Results

Our analysis revealed that most machine learning applications focused on OSA classification and diagnosis, utilizing various data sources such as polysomnography, electrocardiogram data, and wearable devices. We also found that study cohorts were predominantly overweight males, with an underrepresentation of women, younger obese adults, individuals over 60 years old, and diverse racial groups. Many studies had small sample sizes and limited use of robust model validation.

Conclusion

Our findings highlight the need for more inclusive research approaches, starting with adequate data collection in terms of sample size and bias mitigation for better generalizability of machine learning models in OSA research. Addressing these demographic gaps and methodological opportunities is critical for ensuring more robust and equitable applications of artificial intelligence in healthcare.

Electroencephalogram Correlates of Delayed Emergence After Remimazolam-Induced Anesthesia Compared to Propofol

BACKGROUND

Delayed emergence from anesthesia presents clinical challenges, including prolonged stays in the postanesthesia care unit (PACU). The neurobiological mechanisms underlying delayed emergence, particularly in remimazolam-induced anesthesia, remain poorly understood. This study aimed to explore patterns of brain electrical activity of delayed emergence in remimazolam-induced anesthesia by comparing dynamic changes in electroencephalogram (EEG) activity under various anesthesia states of remimazolam and propofol, focusing on the prefrontal region.

METHODS

Forty-eight patients (age >18) who underwent laparoscopic cholecystectomy randomly received remimazolam- or propofol-induced general anesthesia. Power spectrogram analysis and functional connectivity measures, phase lag entropy (PLE) and phase lag index (PLI), were used to the prefrontal EEG data collected at baseline, unconsciousness, and emergence. Correlation between EEG measures and Patient State Index (PSI) at PACU, as well as time to Aldrete 9, were compared.

RESULTS

During emergence from anesthesia, EEG power revealed that the remimazolam group had higher powers than the propofol group in theta band during eyes-open (EO) (mean of 2.933 [standard deviation of 5.762] vs -2.342 [4.869]; P-value of 0.018 with independent 2-sample t test), and in the alpha band during eyes-closed (EC) (5.821 [7.35] vs -2.399 [4.53]; P < .001) and EO (4.84 [6.411] vs -3.613 [4.556]; P < .001). Conversely, the functional connectivity result showed lower PLE in the alpha band during EC (0.619 [0.0338] vs 0.684 [0.0392]; P < .0001) and EO (0.651 [0.0358] vs 0.692 [0.0428]; P = .015), and in the beta band during EC (0.682 [0.0308] vs 0.712 [0.0236]; P = .016) and EO (0.695 [0.0236] vs 0.725 [0.0195]; P < .001). In line with this, the remimazolam group had lower PSI values at PACU during EC (65.10 [14.67] vs 82.40 [6.678]; P < .0001) and EO (72.35 [12.55] vs 83.53 [6.632]; P = .006) and were slower to reach Aldrete score of 9 (median difference of 17.5; interquartile range of [0.0-21.0]; P < .001). Delayed consciousness recovery (time to Aldrete 9) under remimazolam was significantly correlated with PLE (Pearson's correlation = -.78, P < .0001) and PLI (Pearson's correlation =.69, P = .028) in the alpha band during deep anesthesia.

CONCLUSIONS

Dynamic changes in prefrontal EEG during recovery and the correlation analyses show the potential of EEG in reflecting distinct consciousness recovery profiles between 2 drugs-slower recovery under remimazolam anesthesia. This suggests an association of EEG parameters with a unique behavioral profile of remimazolam, especially reflecting progressive changes in cerebral activity during recovery.

Modified transforaminal epidural steroid injection combined with pulsed radiofrequency: an effective treatment measure for lumbar radiculopathy

Background

Lumbar disc herniation (LDH) is a prevalent condition encountered in the clinical diagnosis and management of spinal surgery. Certain people may experience excruciating radicular pain in the lower extremities. If these symptoms are not promptly alleviated, they may progressively deteriorate, ultimately resulting in radiating pain in the lower extremities, advancing neurological impairments, and potential trouble in standing, significantly impairing the patient's quality of life. Consequently, clinicians require an expedited and efficacious approach to address radicular discomfort resulting from lumbar radiculopathy and promptly reinstate the patient's normal functionality.

Objectives

This study seeks to assess the effectiveness of a modified transforaminal epidural steroid injection (TFESI) in conjunction with pulsed radiofrequency (PRF) for treating lumbar radiculopathy using a retrospective analysis.

Methods

Our study examined patients with unilateral lower limb radicular pain persisting for three months or more due to LDH, in whom conservative therapies were ineffective, from January 1, 2023, to October 31, 2023. This trial comprised 106 patients who received modified TFESI alongside PRF. We evaluated clinical efficacy and follow-up at baseline and at 1 week, 1 month, 3 months, 6 months, and 12 months post-surgery primarily using the Visual Analog Scale (VAS), Oswestry disability index (ODI), and modified MacNab score.

Results

Patients who received modified TFESI in conjunction with PRF exhibited substantial enhancements across all three assessment instruments (VAS, ODI, MacNab) when compared to pre-treatment evaluations (p < 0.0001). The alleviation of radicular discomfort was notably enduring, meeting the patients' expectations. At the 12-month follow-up, we noted that patients often achieved substantial pain alleviation within 6 months, and only a minor proportion of patients encountered pain recurrence by the 12th month, with no notable problems detected.

Conclusions

The modified TFESI in conjunction with PRF is a safe, cost-efficient, and successful therapy modality. Our findings indicated that this method can efficiently and swiftly relieve patients' radicular discomfort and produce enduring therapeutic effects.

The effect of curcumin on postpartum depression and anxiety in primiparous women: a double-blind randomized placebo-controlled clinical trial

Postpartum depression and anxiety are common problems in primiparous women, which can negatively affect Maternal-infant bonding and lead to sexual disorders. It's important to prevent and treat these issues, especially since medication options during breastfeeding may be limited. Our study aimed to investigate the effect of curcumin, a natural substance known for its beneficial properties, on postpartum depression and anxiety in primiparous women. A randomized controlled clinical trial was conducted on 96 primiparous women in Tabriz City. Participants were randomly assigned to either the intervention group (n = 48) or the control group (n = 48) using the random block method. The intervention group received curcumin capsules with a dose of 500 mg, while the control group received a placebo with the same dose once daily for eight weeks. Data was collected using the Edinburgh Postnatal Depression Scale (EPDS) and postpartum-specific Anxiety Scale research short-form (PSAS-RSF) questionnaires. After the intervention, the mean score of depression (mean difference: -2.5; 95% confidence interval: -3.3 to -1.7; P < 0.001) and anxiety (Mean difference: -1.4; 95% confidence interval: -2.1 to -0.7; P < 0.001) in the intervention group were significantly lower than the control group. It seems that curcumin can improve the mental health and quality of life of primiparous women postpartum due to its efficacy in reducing postpartum anxiety and depression, easy accessibility, and cost-effectiveness.

A comparison of McGrath MAC, AIRWAY SCOPE®, and AceScope® video laryngoscopes in novice healthcare providers: a randomized crossover simulation study

BACKGROUND

Video laryngoscopes are widely used for tracheal intubation, particularly in challenging airway scenarios. The McGrath MAC, AIRWAY SCOPE®, and AceScope® are popular video laryngoscopes with different design features. This study aimed to compare the effectiveness and usability of these three devices in novice healthcare providers during simulated tracheal intubation scenarios employing a manikin.

METHODS

Sixty novice healthcare providers, including nurses and pharmacists, were enrolled in this randomized crossover study. Participants performed tracheal intubation using the McGrath MAC, AIRWAY SCOPE, and AceScope in both normal airway and cervical spine immobilization models. Primary outcomes were intubation success rate and time to intubation. Secondary outcomes included user preferences, device ease of use, and the incidence of dental injuries.

RESULTS

The AIRWAY SCOPE demonstrated the shortest intubation time in both normal airway and cervical spine immobilization models (14.90 ± 1.76 s and 23.80 ± 2.43 s, respectively), followed by the McGrath MAC and AceScope. All devices exhibited high success rates, and there were no significant differences in perceived difficulty among the three video laryngoscopes. The incidence of dental injuries was generally comparable among the devices. However, in the cervical spine immobilization model, the AceScope demonstrated a significantly higher rate of dental injuries compared to the McGrath MAC (p < 0.05), highlighting a potential concern for clinical practice.

CONCLUSIONS

The AIRWAY SCOPE was the most efficient video laryngoscope in terms of intubation time, followed by the McGrath MAC and AceScope. However, all devices showed high success rates and no significant differences in perceived difficulty. Further research is needed to validate these findings in clinical settings and investigate the impact of device-specific features on intubation outcomes and dental injury incidence.

TRIAL REGISTRATION

Registration number: jRCT1030240598 ( https://jrct.niph.go.jp/re/reports/detail/91422 ) The registration date of the clinical trial is January 8, 2025.UMIN000050394.

A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements

PURPOSE OF REVIEW

Artificial intelligence (AI) represents a transformative opportunity for pain medicine, offering potential solutions to longstanding challenges in pain assessment and management. This review synthesizes the current state of AI applications with a strategic framework for implementation, highlighting established adaptation pathways from adjacent medical fields.

RECENT FINDINGS

In acute pain, AI systems have achieved regulatory approval for ultrasound guidance in regional anesthesia and shown promise in automated pain scoring through facial expression analysis. For chronic pain management, machine learning algorithms have improved diagnostic accuracy for musculoskeletal conditions and enhanced treatment selection through predictive modeling. Successful integration requires interdisciplinary collaboration and physician coleadership throughout the development process, with specific adaptations needed for pain-specific challenges.

SUMMARY

This roadmap outlines a comprehensive methodological framework for AI in pain medicine, emphasizing four key phases: problem definition, algorithm development, validation, and implementation. Critical areas for future development include perioperative pain trajectory prediction, real-time procedural guidance, and personalized treatment optimization. Success ultimately depends on maintaining strong partnerships between clinicians, developers, and researchers while addressing ethical, regulatory, and educational considerations.

Global trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysis

BACKGROUND

Interest in artificial intelligence (AI) research in anesthesia is growing rapidly. However, there is a lack of bibliometric analysis to measure and analyze global scientific publications in this field. The aim of this study was to identify the hotspots and trends in AI research in anesthesia through bibliometric analysis.

METHODS

English articles and reviews published from 2000 to 2023 were retrieved from the Web of Science Core Collection (WoSCC) database. The extracted data were summarized and analyzed using Microsoft Excel, and bibliometric analysis were conducted with VOSviewer software.

RESULTS

AI research literature in anesthesia has exhibited rapid growth in recent years. The United States leads in the number of publications and citations, with Stanford University as the most prolific institution. Hyung-Chul Lee is the author with the highest number of publications. The journal Anesthesiology is highly recognized and authoritative in this field. Recent keywords include "musculoskeletal pain", "precision medicine", "stratification", "images", "mean arterial pressure", " enhanced recovery after surgery", "frailty", "telehealth", "postoperative delirium" and "postoperative mortality" indicating hot topics in AI research in anesthesia.

CONCLUSIONS

Publications on AI research in the field of anesthesia have experienced rapid growth over the past two decades and are likely to continue increasing. Research areas such as depth of anesthesia (DOA) and drug infusion (including electroencephalography and deep learning), perioperative risk assessment and prediction (covering mean arterial pressure, frailty, postoperative delirium, and mortality), image classification and recognition (for applications such as ultrasound-guided nerve blocks, vascular access, and difficult airway assessment), and perioperative pain management (particularly musculoskeletal pain) have garnered significant attention. Additionally, topics such as precision medicine, enhanced recovery after surgery, and telehealth are emerging as new hotspots and future directions in this field.

Video laryngoscopy may improve the intubation outcomes in critically ill patients: a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

The role of video laryngoscopy in critically ill patients requiring emergency tracheal intubation remains controversial. This systematic review and meta-analysis aimed to evaluate whether video laryngoscopy could improve the clinical outcomes of emergency tracheal intubation.

METHODS

We searched the PubMed, Embase, Scopus and Cochrane databases up to 5 September 2024. Randomised controlled trials comparing video laryngoscopy with direct laryngoscopy for emergency tracheal intubation were analysed. The primary outcome was the first-attempt success rate, while secondary outcomes included intubation time, glottic visualisation, in-hospital mortality and complications.

RESULTS

Twenty-six studies (6 in prehospital settings and 20 in hospital settings) involving 5952 patients were analysed in this study. Fifteen studies had low risk of bias. Overall, there was no significant difference in first-attempt success rate between two groups (RR 1.05, 95% CI 0.97 to 1.13, p=0.24, I2=89%). However, video laryngoscopy was associated with a higher first-attempt success rate in hospital settings (emergency department: RR 1.13, 95% CI 1.03 to 1.23, p=0.007, I2=85%; intensive care unit: RR 1.16, 95% CI 1.05 to 1.29, p=0.003, I2=68%) and among inexperienced operators (RR 1.15, 95% CI 1.03 to 1.28, p=0.01, I2=72%). Conversely, the first-attempt success rate with video laryngoscopy was lower in prehospital settings (RR 0.75, 95% CI 0.57 to 0.99, p=0.04, I2=95%). There were no differences for other outcomes except for better glottic visualisation (RR 1.11, 95% CI 1.03 to 1.20, p=0.005, I2=91%) and a lower incidence of oesophageal intubation (RR 0.42, 95% CI 0.24 to 0.71, p=0.001, I2=0%) when using video laryngoscopy.

CONCLUSIONS

In hospital settings, video laryngoscopy improved first-attempt success rate of emergency intubation, provided superior glottic visualisation and reduced incidence of oesophageal intubation in critically ill patients. Our findings support the routine use of video laryngoscopy in the emergency department and intensive care units.

PROSPERO REGISTRATION NUMBER

CRD 42023461887.

Decoding the Multifidus Muscle: Fat Infiltration as a Predictor of Outcome After Lumbar-Lumbar Fusion Surgery

OBJECTIVE

To identify independent risk factors for residual pain following posterior lumbar interbody fusion (PLIF) and assess if multifidus muscle fat infiltration (MFI) predicts persistent postoperative pain.

METHODS

A retrospective study of 336 patients (mean age: 67.18 ± 8.73 years) undergoing PLIF for lumbar degenerative diseases between January 2021 and October 2023, with ≥12 months of follow-up. Visual analog scale (VAS) and Oswestry Disability Index scores were recorded preoperatively, and at 1 day, 1 month, and 12-18 months postoperatively. Patients were divided into nonpain (VAS < 3, n = 180) and pain (VAS ≥ 3, n = 156) groups. Radiological parameters, including Hounsfield unit (HU) values, MFI, multifidus muscle index, spondylolisthesis, nonunion, and screw loosening, were assessed.

RESULTS

Both groups showed significant improvements in VAS and Oswestry Disability Index (P < 0.05), yet 46.43% of patients reported VAS ≥ 3 at final follow-up. The pain group had higher rates of spondylolisthesis, multisegmental surgery, nonunion, and screw loosening (P < 0.05). MFI was the strongest correlate of pain, followed by surgical extent and nonunion. Multivariate regression identified higher MFI (odds ratio [OR = 1.094, P = 0.001), more fused segments (OR = 1.960, P = 0.015), lumbar spondylolisthesis (OR = 2.231, P = 0.018), and lower HU values (OR = 0.991, P = 0.015) as predictors of pain.

CONCLUSIONS

MFI, lower HU values, greater surgical extent, and spondylolisthesis are independent predictors of postoperative pain after PLIF, emphasizing the need for targeted preoperative and rehabilitation strategies.

Pain Management in Cancer Patients With Artificial Intelligence: Narrative Review

Background: Pain is a significant symptom in cancer patients that is frequently not effectively treated, and managing it is seen as a crucial aspect of caring for these patients. This severe pain frequently causes a significant disturbance in their quality of life. At present, there are different challenges in utilizing a range of pharmacological and nonpharmacological treatments for managing pain in cancer patients. Recent technological advancements, particularly in artificial intelligence, have improved the management of pain in cancer patients. Artificial intelligence and its algorithms offer potential solutions for pain relief in cancer patients with reduced side effects. Study Design: The current review aimed to assess the validity of studies on using artificial intelligence in pain management for cancer patients. Four databases have been used to review all published studies from the start of 2023: PubMed, Scopus, Web of Science, and Google Scholar. The search mechanism for articles was mainly using valid and mesh-based keywords, asking experts, and reviewing the literature and including "Pain," "Pain management," "Cancer," and "Artificial intelligence." During the initial search, a total of 450 articles were found, and after considering the inclusion and exclusion criteria and reviewing the abstract and content of the articles, 15 articles were finally included in the study. Results: AI-based solutions can provide individual pain relief plans. When AI analyzes large patient data such as physiological signals, responses to treatment, and symptoms of patients who have been diagnosed with pain, it is possible to accurately adjust therapeutic measures. Conclusions: AI enables healthcare providers to offer timely care and assistance to cancer patients through remote monitoring and telehealth services, even when they are not physically present. Despite the presence of hurdles such as ensuring ethical AI practices and protecting data privacy, the integration of AI in oncology pain management brings optimism for the future.

Industrial applications of large language models

Large language models (LLMs) are artificial intelligence (AI) based computational models designed to understand and generate human like text. With billions of training parameters, LLMs excel in identifying intricate language patterns, enabling remarkable performance across a variety of natural language processing (NLP) tasks. After the introduction of transformer architectures, they are impacting the industry with their text generation capabilities. LLMs play an innovative role across various industries by automating NLP tasks. In healthcare, they assist in diagnosing diseases, personalizing treatment plans, and managing patient data. LLMs provide predictive maintenance in automotive industry. LLMs provide recommendation systems, and consumer behavior analyzers. LLMs facilitates researchers and offer personalized learning experiences in education. In finance and banking, LLMs are used for fraud detection, customer service automation, and risk management. LLMs are driving significant advancements across the industries by automating tasks, improving accuracy, and providing deeper insights. Despite these advancements, LLMs face challenges such as ethical concerns, biases in training data, and significant computational resource requirements, which must be addressed to ensure impartial and sustainable deployment. This study provides a comprehensive analysis of LLMs, their evolution, and their diverse applications across industries, offering researchers valuable insights into their transformative potential and the accompanying limitations.

Coflex Interspinous Stabilization with Decompression for Lumbar Spinal Stenosis: An Average 14-Year Follow-Up

Background: This study aimed to evaluate the long-term clinical usefulness and radiologic changes around the Coflex device following decompression with Coflex insertion for degenerative lumbar spinal stenosis (DLSS), with an average follow-up of 14 years. Methods: This retrospective study included 147 patients who underwent decompression and Coflex insertion for single-level DLSS at a single institution between January 2007 and December 2010. Patients with spinal stenosis unresponsive to 3 months of conservative treatment were treated surgically. The mean follow-up duration was 173.9 ± 23.7 (range, 119-214) months. Results: The mean visual analog scale score decreased from 8.22 ± 1.06 preoperatively to 2.08 ± 1.58 postoperatively. Intervertebral disc height and foramen height at the Coflex insertion site decreased by 5.3% and 2.0%, respectively, after surgery. The reoperation rate at the operated site was 25% (n = 37). A significantly higher reoperation rate was observed in patients with translational instability (odds ratio [OR], 7.77; 95% confidence interval [CI], 2.453-24.658; p < 0.01) and angular instability (OR, 1.59; 95% CI, 0.492-5.133; p < 0.001). Eight patients underwent reoperation due to rapid progression of instability within 2 years of Coflex insertion; thereafter, a similar cumulative incidence rate was consistently observed. The adjacent-segment reoperation rate was 10.8% (n = 16). Conclusions: The Coflex interspinous device helps preserve disc and foramen height but is associated with a high reoperation rate, particularly in patients with spinal instability. Therefore, careful patient selection is crucial when considering its use.

From Spreadsheets and Bespoke Models to Enterprise Data Warehouses: GPT-enabled Clinical Data Ingestion into i2b2

Objective

Clinical and phenotypic data available to researchers are often found in spreadsheets or bespoke data models. Bridging these to enterprise data warehouses would enable sophisticated analytics and cohort discovery for users of platforms like NHGRI's Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVlL). We combine data mapping methodologies, biomedical ontologies, and large language models (LLMs) to load these data into Informatics for Integrating Biology and the Bedside (i2b2), making them available to AnVIL users.

Materials and Methods

We developed few-shot prompts for ChatGPT-4o to generate Python scripts that facilitate the extract, transform, and load (ETL) process into i2b2. The scripts first convert a designated data dictionary (in various formats) into an intermediate common format, and then into an i2b2 ontology. Finally, the original data file is converted into i2b2 facts, using standard ontologies hosted by the National Center for Biomedical Ontology (NCBO).

Results

ChatGPT-4o correctly produced Python code to facilitate ETL. We converted phenotype data from three synthetic datasets from three disparate data models available in AnVIL. Our prompts generated scripts which successfully converted data on 3,458 fake patients, making it queryable in i2b2.

Discussion

For a few datasets, iterative prompt refinement might reduce ETL efficiency gains. However, prompt reuse significantly reduces incremental effort for additional data models. At scale, we anticipate our pipeline offers substantial time savings, which could transform future ETL workflows.

Conclusion

We developed an LLM-powered ETL pipeline to convert disparate datasets into i2b2 format, enabling advanced analytics and cohort discovery across heterogeneous data models.

Clinical profiles and treatment outcomes of dental rehabilitation in patients treated under general anesthesia: a comparison between healthy and special healthcare needs children

Background

The dental treatment of pediatric patients under general anesthesia is considered one of the most important behavioral management techniques that parents have accepted. The aim of this study is to compare the clinical profiles and treatment outcomes of healthy patients and special healthcare needs (SHCN) pediatric dental patients who underwent a full dental rehabilitation under general anesthesia (DRGA).

Methods

This study utilizes a retrospective cross-sectional design. Records were reviewed for all pediatric patients referred to the dental clinic from December 2020 to June 2023 and placed on the waiting list for DRGA. The data collected included demographics, medical history, types of dental treatment performed, medications prescribed, and admission/discharge details. Statistical analyses included chi-square, Fisher's exact, Mann-Whitney U, Kruskal-Wallis tests, as appropriate, and logistic regression.

Results

This study involved 378 pediatric dental patients treated under general anesthesia (GA), 46.3% were classified as healthy, while 53.7% had SHCN. The SHCN group was significantly older (mean age 6.6 ± 2.7 years vs. 5.1 ± 1.6 years, p < 0.0001) and required more extensive treatments, including extractions (p < 0.0001), longer hospital stays (mean: 5.9 vs. 0.9 days, p < 0.0001), and more frequent preoperative consultations (p < 0.0001). The group with children younger than 6 years had a higher proportion of healthy patients (73.9%), received more conservative treatment such as stainless-steel crowns and pulpotomies (p < 0.0001), and had shorter hospital stays by 1.3 days compared to the 6-14-year-old group. SHCN status was a strong predictor of admission after DRGA compared to healthy ones (OR: 59).

Conclusion

This study highlights the distinct differences in the clinical profiles and treatment outcomes of healthy patients and SHCN pediatric patients undergoing DRGA, with the latter patients requiring more complex care and experiencing extended hospitalization. These findings underscore the importance of tailoring dental treatment plans to the unique needs of pediatric patients to optimize outcomes.

Risk factors for administration of additional neuromuscular block reversal in adults undergoing general anaesthesia: a single centre retrospective case-control study

BACKGROUND

Residual neuromuscular block continues to be a modifiable risk factor for major postoperative pulmonary complications in adults.

METHODS

We performed a large retrospective case-control study at a single center to evaluate both the prevalence and risk factors for clinically significant residual neuromuscular block following reversal with neostigmine.

RESULTS

We found that clinically significant residual neuromuscular block after reversal with neostigmine is rare, occurring in 3.2% of adults. Risk factors for incomplete reversal with neostigmine following rocuronium administration included: increasing age, ASA physical class status III and IV, a cumulative dose of rocuronium > 0.43 mg•kg-1hr-1, an interval of < 48 min between the last dose of rocuronium and neostigmine administration, a qualitative train-of-four count < 2 at the time of reversal with neostigmine, emergency case status, thoracic surgery, and African American race.

CONCLUSION

Reversing neuromuscular block with sugammadex in patients at higher risk of incomplete reversal with neostigmine can improve outcomes and reduce costs, especially in cases where qualitative assessment is utilized or when quantitative monitoring is unavailable.

A Review of Non-Cardiac Complications of General Anesthesia: The Current State of Knowledge

General anesthesia, despite the constant development of anesthesiology, still carries certain risks. To provide safe anesthesia, it is crucial to properly qualify patients and to react in an appropriate manner when problems occur. It is therefore essential to have knowledge of risk factors, pathophysiology, symptoms, and management patterns regarding complications. This review comprehensively describes respiratory complications such as airway spasm, conditions leading to intraoperative hypoxemia, postoperative pulmonary complications (PPC), and complications of cross airway compromise, from aspects including respiratory complications and mechanical injuries. Moreover, events characteristic of this type of anesthesia, such as anaphylaxis, postoperative nausea and vomiting (PONV), neurological complications, accidental awakening during general anesthesia (AAGA), hypothermia, and malignant hyperthermia (MH), have been included. Each complication is elaborated on in terms of risk groups and factors, symptoms, and prevention and treatment options, taking into account the interrelationship of particular conditions. Although that issue is well reported in the literature, this review, in addition to a comprehensive summary of the most important non-cardiovascular and hemodynamic complications, takes into account the latest findings on methods of prevention, diagnosis, and intraoperative monitoring. The article combines a comprehensive compilation of basic information on the most significant complications, including their diagnosis and methods of intervention, along with consideration of the latest scientific developments and indication of future research directions. This review is based on the most recent articles possible, published between 2006 and 2024.

Multi-layered data framework for enhancing postoperative outcomes and anaesthesia management through natural language processing

Anaesthesia management is a critical aspect of perioperative care, directly influencing postoperative recovery, pain management, and patient outcomes. Despite advancements in anaesthesia techniques, variability in patient responses and unexpected postoperative complications remain significant challenges. The research proposes a multi-layered architecture named Anaesthesia CareNet for analyzing data from diverse sources to enhance personalized anaesthesia management and postoperative outcome prediction. The architecture is structured into two primary layers: Data processing and Predictive Modeling. In the Data processing layer, advanced Natural Language Processing (NLP) techniques such as Named Entity Recognition (NER), normalization, lemmatization, and stemming are applied to clean and standardize the unstructured clinical data. Generative Pre-trained Transformer 3 (GPT-3), a Large Language Model (LLM) is employed as a feature extraction method, allowing the system to process and analyze complex clinical narratives and unstructured textual data from patient records. This enables more precise and personalized predictions, not only improving anaesthesia management but also laying the groundwork for broader applications in life sciences. The extracted data is passed into the predictive modeling layer, where the Intelligent Golden Eagle Fine-Tuned Logistic Regression (IGE-LR) model is applied. By analyzing correlations between patient characteristics, surgical details, and postoperative recovery patterns, IGE-LR enables the prediction of complications, pain management requirements, and recovery trajectories beyond anaesthesia; the methodology has potential applications in diverse areas such as diagnostics, drug discovery, and personalized medicine, where large-scale data analysis, predictive modeling, and real-time adaptability are crucial for improving patient outcomes. The proposed IGE-LR method achieves higher performance with 91.7 % accuracy, 90.6 % specificity, and 90 % AUC, with a recall of 91.3 %, precision of 90.1 %, and an F1-Score of 90.4 %. By leveraging advanced NLP and predictive analytics, Anaesthesia CareNet exemplifies how AI-driven frameworks can transform life sciences, advancing personalized healthcare and creating a more precise, efficient, and dynamic approach to treatment management.

Prospective in-depth analysis of anaesthetic management of spontaneous ventilation VATS for lung cancer resection: a matched pairs comparison to intubated VATS

BACKGROUND

Spontaneous ventilation video-assisted thoracoscopic surgery (SV-VATS) has been propagated for nearly two decades without a prospective in-depth analysis of anaesthetic management and anaesthetic processing times. This would be important as anaesthetic management of SV-VATS imposes fundamental changes to standards in thoracic anaesthesia and may increase anaesthetic risks. Therefore, this study aimed to provide such in-depth analysis and compare the results to data from matched intubated VATS (I-VATS) patients. 3D-reconstruction of bronchial airways helped to estimate the risk reduction by avoiding double-lumen tube (DLT) intubation according to common selection methods in SV-VATS patients.

METHODS

SV-VATS patients receiving anatomical (N = 22) and non-anatomical (N = 16) lung cancer resections were prospectively enrolled. A retrospective I-VATS control cohort (N = 76) allowed for a 2:1 propensity score matching. DLT sizes necessary for SV-VATS patients according to common selection methods were evaluated by 3D-reconstruction of the left main bronchus and the ≥ 1 mm criterion.

RESULTS

SV-VATS patients required substantially less propofol dosage (P < 0.001) with an increase in variability of drug dosing (P < 0.001) and higher BIS values (P < 0.001) as compared to I-VATS patients. SV-VATS lead to higher variability in respiratory parameters (P < 0.001) with less driving pressure (P < 0.001) and similar mean tidal volumes, oxygenation, and hemodynamic parameters compared to I-VATS. Spontaneous ventilation was achieved by allowing for permissive hypercapnia and respiratory acidosis. Anaesthetic processing time was reduced by 7 min (P < 0.001). 5-10% of female and 5% of male patients would have received a DLT larger than their bronchial airway.

CONCLUSIONS

Our study provides the first prospective quantitative in-depth analysis of a standardised anaesthetic management regime for SV-VATS, including anaesthetic processing times. Respiratory parameters during SV-VATS are compatible with reduced mechanical power as compared to patients undergoing I-VATS. The anaesthetic management regime reduced the risk of airway damage imposed by choosing too-large DLTs in up to 10% of patients without compromising oxygenation and hemodynamic stability. Changes in anaesthetic processing time by 7 min would not allow for a higher caseload of SV-VATS for lung cancer surgery.

CLINICAL TRIAL NUMBER

Not applicable.

Advances in Targeted and Systemic Therapy for Salivary Gland Carcinomas: Current Options and Future Directions

Salivary gland carcinomas (SGCs) represent a rare and heterogeneous group of malignancies accounting for 3-6% of all head and neck cancers. While surgical resection and radiotherapy remain the standard for locoregional control, systemic treatment is indicated for recurrent or metastatic disease. Advances in molecular profiling have identified actionable targets such as NTRK gene fusions, HER2, immune checkpoint regulators, androgen receptors, and RET receptors. These have facilitated the development of targeted therapies, including TRK inhibitors, HER2-directed agents, and androgen receptor modulators, as well as emerging combinations of immunotherapy and chemotherapy. Despite these advancements, challenges such as resistance mechanisms and limited therapeutic efficacy persist. Overall response rates remain relatively low across most systemic therapies, reflecting a persistent unmet clinical need. This review discusses the current landscape of treatment options and explores promising clinical trials and future directions to enhance outcomes for patients with SGCs.

Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation

Enhanced External Counterpulsation (EECP), as a non-invasive, cost-effective, and efficient adjunctive circulatory technique, has been widely applied in in the cardiovascular field. Numerous studies and clinical observations have confirmed the obvious advantages of EECP in promoting blood flow perfusion to vital organs such as the heart, brain, and kidneys. However, many potential mechanisms of EECP remain insufficiently validated, necessitating researchers to dedicate substantial time and effort to in-depth investigations. In this work, large language models (such as ChatGPT and Ernie Bot) were used to identify top research priorities in five key topics in the field of EECP: mechanisms, device improvements, cardiovascular applications, neurological applications, and other applications. After generating specific research priorities in each domain through language models, a panel of nine experienced EECP experts was invited to independently evaluate and score them based on four parameters: relevance, originality, clarity, and specificity. Notably, high average and median scores for these evaluation parameters were obtained, indicating a strong endorsement from experts in the EECP field. This study preliminarily suggests that large language models like ChatGPT and Ernie Bot could serve as powerful tools for identifying and prioritizing research priorities in the EECP domain.

Supersulfide controls intestinal inflammation by suppressing CD4+ T cell proliferation

Inflammatory bowel disease (IBD) is characterized by chronic intestinal inflammation where CD4+ T lymphocytes play an essential role. Accumulating evidence suggests that immune responses driven by CD4+ T cells are critically regulated by various metabolic pathways including oxidative phosphorylation and glycolysis. Here we show that CARS2/CPERS-dependent supersulfide metabolism restrains CD4+ T cell proliferation in a cell-intrinsic manner. Under steady state, Cars2 +/- mice exhibited spontaneous accumulation of effector/memory CD4+ T cells in the colon with age. In lymphopenic conditions, Cars2 +/- CD4+ T cells showed enhanced cell cycle entry with reduced expression of a cell cycle inhibitor Trp53 and triggered an exacerbated form of colitis, the response being rescued by treatment with a supersulfide donor glutathione trisulfide (GSSSG). Furthermore, re-analysis of publicly available gene datasets of human colonic CD4+ T lymphocytes revealed that downregulation of CARS2 was associated with pathogenesis of IBD, and indeed, addition of GSSSG inhibited human CD4+ T cell proliferation in vitro. Together these observations reveal that CARS2/CPERS-dependent supersulfide metabolism is essential for homeostasis of intestinal effector/memory CD4+ T cells, and further suggest that dysregulation of the same metabolic pathway can lead to development of gut inflammation both in mice and humans.

Morphine Contributes to Epithelial-Mesenchymal Transition in Triple-Negative Breast Cancer Cells by Blocking COX-2 Methylation via Regulating the miR-23a-3p/DNMT3A Feedback

To investigate the effects and mechanisms of morphine on epithelial-mesenchymal transformation (EMT) in triple-negative breast cancer (TNBC). The levels of miR-23a-3p, DNMT3A, and COX-2 in tumor tissues from metastatic TNBC patients treated with morphine were assessed using qRT-PCR. Functional assays assessed morphine's impact on TNBC cell malignancy. Dual luciferase reporter and RNA pull-down assays investigated the interaction between miR-23a-3p and DNMT3A. miR-23a-3p inhibitor and DNMT3A siRNA were transfected into TNBC cells. Protein expression was analyzed by Western blot. Methylation status of miR-23a-3p and COX-2 was assessed via methylation-specific PCR. Rescue experiments were performed to research whether morphine modulates EMT in TNBC through COX-2 methylation regulation via the miR-23a-3p/DNMT3A feedback loop. The effects of morphine on TNBC in nude mice xenotransplantation were studied. In metastatic TNBC patients treated with morphine, miR-23a-3p and COX-2 expression were elevated, and DNMT3A levels were reduced. In TNBC cells, morphine enhanced migration, invasion, and EMT, and suppressed apoptosis. It upregulated miR-23a-3p and COX-2; downregulated DNMT3A; and inhibited methylation of miR-23a-3p and COX-2. miR-23a-3p directly inhibited DNMT3A expression. In morphine-treated TNBC cells, silencing DNMT3A reduced methylation of miR-23a-3p and COX-2. miR-23a-3p inhibitor suppressed migration, invasion, and EMT, and promoted apoptosis; however, these effects were reversed by DNMT3A silencing. In vivo, morphine promoted tumor EMT and metastasis in TNBC; reduced miR-23a-3p and COX-2 methylation; and decreased DNMT3A expression. Morphine accelerated EMT in TNBC by inhibiting COX-2 methylation through the miR-23a-3p/DNMT3A loop.

Evaluating the Efficacy of Large Language Models in Generating Medical Documentation: A Comparative Study of ChatGPT-4, ChatGPT-4o, and Claude

BACKGROUND

Large language models (LLMs) have demonstrated transformative potential in health care. They can enhance clinical and academic medicine by facilitating accurate diagnoses, interpreting laboratory results, and automating documentation processes. This study evaluates the efficacy of LLMs in generating surgical operation reports and discharge summaries, focusing on accuracy, efficiency, and quality.

METHODS

This study assessed the effectiveness of three leading LLMs-ChatGPT-4.0, ChatGPT-4o, and Claude-using six prompts and analyzing their responses for readability and output quality, validated by plastic surgeons. Readability was measured with the Flesch-Kincaid, Flesch reading ease scores, and Coleman-Liau Index, while reliability was evaluated using the DISCERN score. A paired two-tailed t-test (p<0.05) compared the statistical significance of these metrics and the time taken to generate operation reports and discharge summaries against the authors' results.

RESULTS

Table 3 shows statistically significant differences in readability between ChatGPT-4o and Claude across all metrics, while ChatGPT-4 and Claude differ significantly in the Flesch reading ease and Coleman-Liau indices. Table 6 reveals extremely low p-values across BL, IS, and MM for all models, with Claude consistently outperforming both ChatGPT-4 and ChatGPT-4o. Additionally, Claude generated documents the fastest, completing tasks in approximately 10 to 14 s. These results suggest that Claude not only excels in readability but also demonstrates superior reliability and speed, making it an efficient choice for practical applications.

CONCLUSION

The study highlights the importance of selecting appropriate LLMs for clinical use. Integrating these LLMs can streamline healthcare documentation, improve efficiency, and enhance patient outcomes through clearer communication and more accurate medical reports.

LEVEL OF EVIDENCE V

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

The impact of KRAS mutations on risk of venous thromboembolism recurrence in patients with metastatic colorectal cancer

BACKGROUND

The relationship between KRAS mutations and the risk of venous thromboembolism (VTE) recurrence in metastatic colorectal cancer (mCRC) patients with established cancer-associated thrombosis (CAT) remains uncertain. This study aims to (1) evaluate the predictive value of seven KRAS mutation subtypes for VTE recurrence and (2) assess the impact of incorporating these mutations into two existing VTE risk scores: the Khorana score and the Ottawa score.

METHODS

Between 2019 and 2023, we identified patients with histologically confirmed mCRC who had symptomatic or incidental index VTE and received anticoagulation therapy. Regression analyses were conducted to calculate hazard ratios (HRs) for recurrent VTE associated with the seven KRAS mutation subtypes. We used receiver operating characteristic (ROC) curves to assess the performance of both the original scores and the modified scores that included KRAS mutations. To quantify the improvements of the modified scores, we calculated the net reclassification improvement (NRI).

RESULTS

A total of 2,195 patients were enrolled. KRAS G12C, KRAS G12A, and KRAS G13D mutations were significantly associated with a higher risk of recurrent VTE compared to other subtypes, with HRs of 1.84 (95% CI: 1.09-2.97), 2.02 (95% CI: 1.07-3.79), and 1.55 (95% CI: 1.02-2.27), respectively. The original Khorana and Ottawa scores demonstrated moderate predictive ability for VTE recurrence, each with an area under the ROC curve (ROC-AUC) of 0.56 (95% CI: 0.52-0.60). Incorporating the KRAS G12C, KRAS G12A, and KRAS G13D mutations improved the AUCs to 0.70 (95% CI: 0.67-0.74) for the modified Khorana score and 0.71 (95% CI: 0.67-0.74) for the modified Ottawa score. After dichotomizing risk using thresholds from ROC analysis, the NRI values were 0.54 (95% CI: 0.43-0.65) for the modified Khorana score and 0.48 (95% CI: 0.37-0.60) for the modified Ottawa score.

CONCLUSIONS

The KRAS G12C, KRAS G12A, and KRAS G13D mutations are significantly associated with an increased risk of recurrent VTE. Incorporating these specific KRAS mutations into existing risk scores may enhance their predictive accuracy for recurrent VTE in patients with mCRC.

Pain Assessment in Osteoarthritis: Present Practices and Future Prospects Including the Use of Biomarkers and Wearable Technologies, and AI-Driven Personalized Medicine

Osteoarthritis (OA) is a highly prevalent chronic joint disorder affecting ~600 million individuals worldwide and is characterized by complex pain mechanisms that significantly impair patient quality of life. Challenges exist in accurately assessing and measuring pain in OA due to variations in pain perception among individuals and the heterogeneous nature of the disease. Conventional pain assessment methods, such as patient-reported outcome measures and clinical evaluations, often fail to fully capture the heterogeneity of pain experiences among individuals with OA. This review will summarize and evaluate current methods of pain assessment in OA and highlight future directions for standardized pain assessment. We discuss the role of animal models in enhancing our understanding of OA pain pathophysiology and highlight the necessity of translational research to advance pain assessment strategies. Key challenges explored include identifying phenotypes of pain susceptibility, integrating biomarkers into clinical practice, and adopting personalized pain management approaches through the incorporation of multi-modal data and multilevel analysis. We underscore the imperative for continued innovation in pain assessment and management to improve outcomes for patients with OA.

Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis

Background

Cancer survivors and their caregivers, particularly those from disadvantaged backgrounds with limited health literacy or racial and ethnic minorities facing language barriers, are at a disproportionately higher risk of experiencing symptom burdens from cancer and its treatments. Large language models (LLMs) offer a promising avenue for generating concise, linguistically appropriate, and accessible educational materials tailored to these populations. However, there is limited research evaluating how effectively LLMs perform in creating targeted content for individuals with diverse literacy and language needs.

Objective

This study aimed to evaluate the overall performance of LLMs in generating tailored educational content for cancer survivors and their caregivers with limited health literacy or language barriers, compare the performances of 3 Generative Pretrained Transformer (GPT) models (ie, GPT-3.5 Turbo, GPT-4, and GPT-4 Turbo; OpenAI), and examine how different prompting approaches influence the quality of the generated content.

Methods

We selected 30 topics from national guidelines on cancer care and education. GPT-3.5 Turbo, GPT-4, and GPT-4 Turbo were used to generate tailored content of up to 250 words at a 6th-grade reading level, with translations into Spanish and Chinese for each topic. Two distinct prompting approaches (textual and bulleted) were applied and evaluated. Nine oncology experts evaluated 360 generated responses based on predetermined criteria: word limit, reading level, and quality assessment (ie, clarity, accuracy, relevance, completeness, and comprehensibility). ANOVA (analysis of variance) or chi-square analyses were used to compare differences among the various GPT models and prompts.

Results

Overall, LLMs showed excellent performance in tailoring educational content, with 74.2% (267/360) adhering to the specified word limit and achieving an average quality assessment score of 8.933 out of 10. However, LLMs showed moderate performance in reading level, with 41.1% (148/360) of content failing to meet the sixth-grade reading level. LLMs demonstrated strong translation capabilities, achieving an accuracy of 96.7% (87/90) for Spanish and 81.1% (73/90) for Chinese translations. Common errors included imprecise scopes, inaccuracies in definitions, and content that lacked actionable recommendations. The more advanced GPT-4 family models showed better overall performance compared to GPT-3.5 Turbo. Prompting GPTs to produce bulleted-format content was likely to result in better educational content compared with textual-format content.

Conclusions

All 3 LLMs demonstrated high potential for delivering multilingual, concise, and low health literacy educational content for cancer survivors and caregivers who face limited literacy or language barriers. GPT-4 family models were notably more robust. While further refinement is required to ensure simpler reading levels and fully comprehensive information, these findings highlight LLMs as an emerging tool for bridging gaps in cancer education and advancing health equity. Future research should integrate expert feedback, additional prompt engineering strategies, and specialized training data to optimize content accuracy and accessibility.

Assessment of Chronic Postsurgical Pain Knowledge Among Surgical Nurses in a Turkish University Hospital

Objective: Chronic postsurgical pain (CPSP) is a significant yet often underrecognized complication following surgical procedures, impacting patients' quality of life. Surgical nurses play a crucial role in postoperative care and pain management, making their knowledge of CPSP essential for improving patient outcomes. The aim of the study was to assess CPSP knowledge among surgical nurses in a Turkish University Hospital. Methods: This descriptive cross-sectional study included a total of 175 nurses. Data were collected from nurses employed in the surgical units of İnönü University hospital between May 15 and June 15, 2023. Personal information and knowledge-level forms created by the researchers were used for data collection. IBM SPSS Statistics v.25 was used for the statistical analysis. Results: The mean CPSP knowledge score of the nurses working in surgical clinics was 9.26 ± 1.40 (min. = 0, max. = 12) and 75.4% of them had sufficient knowledge. Surgical nurses' knowledge level of CPSP was influenced by their education level (p ≤ 0.001) and total duration of employment in the surgical department (p=0.002). Conclusions: Although most surgical nurses had sufficient CPSP knowledge, gaps remained, particularly among those with lower education levels and less experience. Targeted training programs and continuous professional development initiatives are recommended to enhance CPSP awareness and improve postoperative pain management practices.

Neuropathic Pain: A Comprehensive Bibliometric Analysis of Research Trends, Contributions, and Future Directions

BACKGROUND

Neuropathic pain represents a significant public health concern due to its complex pathophysiology and the disability it can cause. Despite advancements in understanding its underlying mechanisms and potential treatments, challenges persist in achieving effective management. This bibliometric analysis aims to offer a comprehensive overview of research trends, key contributors, and existing gaps in the literature on neuropathic pain, providing valuable insights to guide future studies and enhance clinical approaches.

METHODS

A bibliometric analysis was conducted using the Web of Science Core Collection (WoSCC) database. Key metrics, including publication trends, citation patterns, co-authorship networks, and keyword co-occurrence, were evaluated. Statistical analyses included average annual percentage change (APC) assessments and trend forecasting with an Auto Regressive Integrated Moving Average (ARIMA) model.

RESULTS

A total of 9,974 studies published between 2005 and 2024 were included. Publications peaked between 2021 and 2022 but showed a slight decline thereafter, with forecasts predicting a steady increase from 2025 to 2030. Most papers were published in high-impact Q1 journals, reflecting the quality of research. Co-authorship analysis revealed central hubs of collaboration in the USA and China, with limited integration of smaller countries into the global research network. Keyword analysis identified multiple thematic clusters, including "chronic pain," "molecular mechanisms," and "clinical management." Specific gaps were noted in understanding personalized therapeutic approaches, and non-pharmacological interventions.

CONCLUSIONS

This analysis underscores the critical need for continued research to address gaps in diagnosis, treatment, and management of neuropathic pain. Strengthening international collaborations and fostering multidisciplinary efforts will be pivotal in advancing this field.

Perceptions of complementary health approaches: A cross-sectional comparison of clinical practice and research only trainees

BACKGROUND AND PURPOSE

Complementary health approaches (CHAs) encompass a diverse range of practices used both independently and alongside conventional medical treatments. Understanding how graduate students across disciplines perceive CHAs is important because these trainees will occupy roles as clinical practitioners, medical researchers, healthcare policy makers, and consumers. The purpose of this research was to (a) explore differences in perceptions of CHAs across disciplines, (b) examine differences between medical versus mental health trainees' willingness to recommend CHAs, and (c) determine whether an association exists between descriptive terminology and willingness to recommend CHAs.

MATERIALS AND METHODS

Ratings of familiarity, perceptions of legitimacy, and willingness to recommend CHAs were examined among graduate trainees (N = 416). Responses from (a) clinical practice versus (b) research only trainees; and, within clinical fields, (c) medical versus (d) mental health trainees were compared via sequential rank agreement.

RESULTS

Clinical practice trainees were more familiar with CHAs than research only trainees. Mental health trainees were most familiar with CHAs and perceived them as more legitimate than medical trainees. Perceptions of CHA legitimacy positively correlated with willingness to recommend across disciplines. Medical trainees associated CHAs with the term "alternative; " mental health trainees characterized them as "complementary." Association with "complementary" correlated with increased willingness to recommend.

CONCLUSION

Mental health trainees characterize CHAs as "complementary; " they are also most likely to perceive CHAs as legitimate and to recommend them in practice. Clinical trainees and providers might be more likely to integrate CHAs into practice if characterized as "legitimate" and "complementary."

Hyper-DREAM, a Multimodal Digital Transformation Hypertension Management Platform Integrating Large Language Model and Digital Phenotyping: Multicenter Development and Initial Validation Study

Within the mHealth framework, systematic research that collects and analyzes patient data to establish comprehensive digital health archives for hypertensive patients, and leverages large language models (LLMs) to assist clinicians in health management and Blood Pressure (BP) control remains limited. In this study, our aims to describe the design, development and usability evaluation process of a management platform (Hyper-DREAM) for hypertension. Our multidisciplinary team employed an iterative design approach over the course of a year to develop the Hyper-DREAM platform. This platform's primary functionalities encompass multimodal data collection (personal hypertensive digital phenotype archive), multimodal interventions (BP measurement, medication assistance, behavior modification, and hypertension education) and multimodal interactions (clinician-patient engagement and BP Coach component). In August 2024, the mHealth App Usability Questionnaire (MAUQ) was conducted involving 51 hypertensive patients recruited from three distinct centers. In parallel, six clinicians engaged in management activities and contributed feedback via the Doctor's Software Satisfaction Questionnaire (DSSQ). Concurrently, a real-world comparative experiment was conducted to evaluate the usability of the BP Coach, ChatGPT-4o Mini, ChatGPT-4o and clinicians. The comparative experiment demonstrated that the BP Coach achieved significantly higher scores in utility (mean scores 4.05, SD 0.87) and completeness (mean scores 4.12, SD 0.78) when compared to ChatGPT-4o Mini, ChatGPT-4o, and clinicians. In terms of clarity, the BP Coach was slightly lower than clinicians (mean scores 4.03, SD 0.88). In addition, the BP Coach exhibited lower performance in conciseness (mean scores 3.00, SD 0.96). Clinicians reported a marked improvement in work efficiency (2.67 vs. 4.17, P < .001) and experienced faster and more effective patient interactions (3.0 vs. 4.17, P = .004). Furthermore, the Hyper-DREAM platform significantly decreased work intensity (2.5 vs. 3.5, P = .01) and minimized disruptions to daily routines (2.33 vs. 3.55, P = .004). The Hyper-DREAM platform demonstrated significantly greater overall satisfaction compared to the WeChat-based standard management (3.33 vs. 4.17, P = .01). Additionally, clinicians exhibited a markedly higher willingness to integrate the Hyper-DREAM platform into clinical practice (2.67 vs. 4.17, P < .001). Furthermore, patient management time decreased from 11.5 min (SD 1.87) with Wechat-based standard management to 7.5 min (SD 1.84, P = .01) with Hyper-DREAM. Hypertensive patients reported high satisfaction with the Hyper-DREAM platform, including ease of use (mean scores 1.60, SD 0.69), system information arrangement (mean scores 1.69, SD 0.71), and usefulness (mean scores 1.57, SD 0.58). In conclusion, our study presents Hyper-DREAM, a novel artificial intelligence-driven platform for hypertension management, designed to alleviate clinician workload and exhibiting significant promise for clinical application. The Hyper-DREAM platform is distinguished by its user-friendliness, high satisfaction rates, utility, and effective organization of information. Furthermore, the BP Coach component underscores the potential of LLMs in advancing mHealth approaches to hypertension management.