The CARE Workshop on Robotics and AI in Medicine, held on December 1, 2025 in Indianapolis, convened leading researchers, clinicians, industry innovators, and federal stakeholders to shape a national vision for advancing robotics and artificial intelligence in healthcare. The event highlighted the accelerating need for coordinated research efforts that bridge engineering innovation with real clinical priorities, emphasizing safety, reliability, and translational readiness with an emphasis on the use of robotics and AI to achieve this readiness goal. Across keynotes, panels, and breakout sessions, participants underscored critical gaps in data availability, standardized evaluation methods, regulatory pathways, and workforce training that hinder the deployment of intelligent robotic systems in surgical, diagnostic, rehabilitative, and assistive contexts. Discussions emphasized the transformative potential of AI enabled robotics to improve precision, reduce provider burden, expand access to specialized care, and enhance patient outcomes particularly in undeserved regions and high risk procedural domains. Special attention was given to austere settings, disaster and relief and military settings. The workshop demonstrated broad consensus on the urgency of establishing a national Center for AI and Robotic Excellence in medicine (CARE). Stakeholders identified priority research thrusts including human robot collaboration, trustworthy autonomy, simulation and digital twins, multi modal sensing, and ethical integration of generative AI into clinical workflows. Participants also articulated the need for high quality datasets, shared test beds, autonomous surgical systems, clinically grounded benchmarks, and sustained interdisciplinary training mechanisms.
ABSTRACT After surgery involving cranial nerves and more generally the central nervous system, nonbacterial meningitis should raise suspicion of herpes simplex virus type 1 reactivation. No time should be wasted in diagnosis and treatment; therefore, a polymerase chain reaction testing on cerebrospinal fluid should be systematic in this situation, without neglecting to consider other differential diagnoses.
Marzena Zielińska, Alicja Bartkowska-Śniatkowska, Magdalena Mierzewska-Schmidt
et al.
The anaesthesia of a young child under 3 years of age is a challenge for every anaesthetist. The peculiarities of this group of patients, particularly neonates and infants, resulting primarily from differences in both physiology, anatomy and the immaturity of individual organs which translate into different pharmacokinetics and pharmacodynamics of the drugs used in anaesthesiology, underlie the significantly more frequently recorded critical events during anaesthesia compared with the adult patient population.
Concerned about the safety of children undergoing anaesthesia and aiming to ensure the highest possible quality and uniform standard of anaesthetic services, the Expert Panel of the Section of Paediatric Anaesthesiology and Intensive Care has prepared a Section position paper on anaesthesia in children under 3 years of age.
Anesthesiology, Medical emergencies. Critical care. Intensive care. First aid
ABSTRACT Insulinomas are the primary etiology of endogenous hyperinsulinemic hypoglycemia, which often manifest with Whipple’s triad and neuroglycopenic symptoms. Given the diverse clinical manifestation and subtle onset of insulinomas generally in a small size, detecting a minority of these generally small tumors can be challenging. We reported a case of a 44‐year‐old female patient with recurrent hypoglycemia accompanied by hyperinsulinemia, and the conventional imaging revealed no abnormality. With the aid of endoscopic ultrasound‐guided fine‐needle aspiration biopsy (EUS‐FNAB), the insulinoma was precisely diagnosed and localized, and successfully excised via operation. The patient’s hyperinsulinemia and hypoglycemic episodes were relieved significantly after surgery. The application of EUS‐FNAB notably enhances the diagnostic accuracy for occult insulinomas, thereby informing appropriate surgical management. Herein, we advocate for invasive EUS examination in patients exhibiting strong clinical and laboratory indicators of insulinoma, even when conventional imaging results are negative.
Svetlana S. Konnova, Pavel A. Lepilin, Anastasia A. Zanishevskaya
et al.
Biosensor technologies in medicine, as in many other areas, are replacing labor-intensive methods of monitoring human health. This paper presents the results of experimental studies on label-free sensors based on a hollow core microstructured optical waveguide (HC-MOW) for human blood serum analysis. The MOWs with a hollow core of 247.5 µm in diameter were manufactured and used in our work. These parameters allow the hollow core to be filled with high-viscosity solutions due to the capillary properties of the fiber. Calculations of the spectral properties of the HC-MOW fiber were carried out and experimentally confirmed. Twenty-one blood serum samples from volunteers were analyzed using standard photometry (commercial kits) and an experimental biosensor. The obtained transmission spectra were processed by the principal component analysis method and conclusions were drawn about the possibility of using this biosensor in point-of-care medicine. A significant difference was shown between the blood serum of healthy patients and patients with confirmed diagnoses and a long history of cardiovascular system abnormalities. Algorithms for spectra processing using the Origin program are presented.
Anna Carolyna Gianlorenço, Paulo Eduardo Portes Teixeira, Valton Costa
et al.
<b>Background/Objectives:</b> Speech and motor control share overlapping neural mechanisms, yet their quantitative relationships in Parkinson’s disease (PD) remain underexplored. This study investigated bidirectional associations between acoustic voice features and objective motor metrics to better understand how vocal and motor systems relate in PD. <b>Methods:</b> Cross-sectional baseline data from participants in a randomized neuromodulation trial were analyzed (n = 13). Motor performance was captured using an Integrated Motion Analysis Suite (IMAS), which enabled quantitative, objective characterization of motor performance during balance, gait, and upper- and lower-limb tasks. Acoustic analyses included harmonic-to-noise ratio (HNR), smoothed cepstral peak prominence (CPPS), jitter, shimmer, median fundamental frequency (F0), F0 standard deviation (SD F0), and voice intensity. Univariate linear regressions were conducted in both directions (voice ↔ motor), as well as partial correlations controlling for PD motor symptom severity. <b>Results:</b> When modeling voice outcomes, faster motor performance and shorter movement durations were associated with acoustically clearer voice features (e.g., higher elbow flexion-extension peak speed with higher voice HNR, β = 8.5, R<sup>2</sup> = 0.56, <i>p</i> = 0.01). Similarly, when modeling motor outcomes, clearer voice measures were linked with faster movement speed and shorter movement durations (e.g., higher voice HNR with higher peak movement speed in elbow flexion/extension, β = 0.07, R<sup>2</sup> = 0.56, <i>p</i> = 0.01). <b>Conclusions:</b> Voice and motor measures in PD showed significant bidirectional associations, suggesting shared sensorimotor control. These exploratory findings, while limited by sample size, support the feasibility of integrated multimodal assessment for future longitudinal studies.
Interdisciplinary research is critical for innovation and addressing complex societal issues. We characterise the interdisciplinary knowledge structure of PubMed research articles in medicine as correlation networks of medical concepts and compare the interdisciplinarity of articles between high-ranking (impactful) and less high-ranking (less impactful) medical journals. We found that impactful medical journals tend to publish research that are less interdisciplinary than less impactful journals. Observing that they bridge distant knowledge clusters in the networks, we find that cancer-related research can be seen as one of the main drivers of interdisciplinarity in medical science. Using signed difference networks, we also investigate the clustering of deviations between high and low impact journal correlation networks. We generally find a mild tendency for strong link differences to be adjacent. Furthermore, we find topic clusters of deviations that shift over time. In contrast, topic clusters in the original networks are static over time and can be seen as the core knowledge structure in medicine. Overall, journals and policymakers should encourage initiatives to accommodate interdisciplinarity within the existing infrastructures to maximise the potential patient benefits from IDR.
Mohamed Sedky, Sherif Abd El Aziz, Shaaban Abd Elmoneum
et al.
Background: Coronavirus disease 2019 (COVID-19) is firstly reported in Wuhan, China. Then, it was quickly spread and becomes an epidemic. It is due to infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is highly transmissible with a great risk of mortality. Patients with diabetes mellitus (DM) are more prone to infectious agents like SARS-COV-2. Aim: The aim of the study is to evaluate the relationship between DM and COVID-19 infection regarding to its severity, mortality, rate of admission, complications, and prognosis.Patients and methods: A cross sectional study was performed between April 2021 and September 2021 and included 75 patients divided into two groups: Group A (COVID-19 patients with diabetes: n= 25), Group B (COVID-19 patients who developed diabetes: n= 25) and Group C (COVID-19 patients without diabetes: n= 25). Demographics, clinical, laboratory, radiologic, management, complications, and clinical outcomes data were collected and compared between the groups.Results: Patients with diabetes had a higher complication rate, like respiratory failure, acute cardiac injury. The respiratory failure did not significantly different between groups (it was 20%, 28% and 12% in groups A, B and C, respectively, P = .368). However, acute cardiac injury had been significantly increased in groups A than group B and in A and B than group C. (It was 44%, 20% and 8%, in groups A, B and C, respectively, P= 0.01). The mortality rate was also significantly higher among the A and B than C group (56%, 40% vs 8%, P=0.001).Conclusion: Diabetes is an independent risk factor for the prognosis of COVID-19. Diabetic patients should be intensely monitored during treatment, especially those who require insulin therapy.Background: Coronavirus disease 2019 [COVID-19] was first reported in Wuhan, China. It then rapidly spread and became a global epidemic due to infection by severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]. COVID-19 is highly transmissible with a high risk of mortality. Patients with diabetes mellitus [DM] are more susceptible to infectious agents like SARS-CoV-2.Aim of the work: The aim of the study was to evaluate the relationship between DM and COVID-19 infection regarding severity, mortality, admission rate, complications, and prognosis.Patients and Methods: A cross-sectional study was performed between April 2021 and September 2021. It included 75 patients divided into three groups: Group A [COVID-19 patients with diabetes, n=25], Group B [COVID-19 patients who developed diabetes, n=25] and Group C [COVID-19 patients without diabetes, n=25]. Demographic, clinical, laboratory, radiologic, management, complication, and clinical outcome data were collected and compared between the groups.Results: Patients with diabetes had a higher rate of complications like respiratory failure and acute cardiac injury. Respiratory failure was not significantly different between groups [20%, 28% and 12% in groups A, B and C respectively, P=0.368]. However, acute cardiac injury was significantly higher in groups A than B and in A and B than C [[44%, 20% and 8% respectively, P=0.01]. The mortality rate was also significantly higher among groups A and B than C [56%, 40% vs 8%, P=0.001].Conclusion: Diabetes is an independent risk factor for COVID-19 prognosis. Diabetic patients should be closely monitored during treatment, especially those requiring insulin therapy.
Anh Le, Amirreza Hashemi, Mark P. Ottensmeyer
et al.
The design of nuclear imaging scanners is crucial for optimizing detection and imaging processes. While advancements have been made in simplistic, symmetrical modalities, current research is progressing towards more intricate structures, however, the widespread adoption of computer-aided design (CAD) tools for modeling and simulation is still limited. This paper introduces FreeCAD and the GDML Workbench as essential tools for designing and testing complex geometries in nuclear imaging modalities. FreeCAD is a parametric 3D CAD modeler, and GDML is an XML-based language for describing complex geometries in simulations. Their integration streamlines the design and simulation of nuclear medicine scanners, including PET and SPECT scanners. The paper demonstrates their application in creating calibration phantoms and conducting simulations with Geant4, showcasing their precision and versatility in generating sophisticated components for nuclear imaging. The integration of these tools is expected to streamline design processes, enhance efficiency, and facilitate widespread application in the nuclear imaging field.
Extracting medication names from handwritten doctor prescriptions is challenging due to the wide variability in handwriting styles and prescription formats. This paper presents a robust method for extracting medicine names using a combination of Mask R-CNN and Transformer-based Optical Character Recognition (TrOCR) with Multi-Head Attention and Positional Embeddings. A novel dataset, featuring diverse handwritten prescriptions from various regions of Pakistan, was utilized to fine-tune the model on different handwriting styles. The Mask R-CNN model segments the prescription images to focus on the medicinal sections, while the TrOCR model, enhanced by Multi-Head Attention and Positional Embeddings, transcribes the isolated text. The transcribed text is then matched against a pre-existing database for accurate identification. The proposed approach achieved a character error rate (CER) of 1.4% on standard benchmarks, highlighting its potential as a reliable and efficient tool for automating medicine name extraction.
Introduction: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". Background: The proliferation of archetypes as a means to represent information of Electronic Health Records has raised the need of binding terminological codes - such as SNOMED CT codes - to their elements, in order to identify them univocally. However, the large size of the terminologies makes it difficult to perform this task manually. Objectives: To establish a baseline of results for the aforementioned problem by using off-the-shelf string comparison-based techniques against which results from more complex techniques could be evaluated. Methods: Nine Typed Comparison METHODS were evaluated for binding using a set of 487 archetype elements. Their recall was calculated and Friedman and Nemenyi tests were applied in order to assess whether any of the methods outperformed the others. Results: Using the qGrams method along with the 'Text' information piece of archetype elements outperforms the other methods if a level of confidence of 90% is considered. A recall of 25.26% is obtained if just one SNOMED CT term is retrieved for each archetype element. This recall rises to 50.51% and 75.56% if 10 and 100 elements are retrieved respectively, that being a reduction of more than 99.99% on the SNOMED CT code set. Conclusions: The baseline has been established following the above-mentioned results. Moreover, it has been observed that although string comparison-based methods do not outperform more sophisticated techniques, they still can be an alternative for providing a reduced set of candidate terms for each archetype element from which the ultimate term can be chosen later in the more-than-likely manual supervision task.
Deng-Ho Yang, Hsiang-Cheng Chen, James Cheng-Chung Wei
Abstract Background Gouty arthritis (GA) is a chronic systemic disease with recurrent acute monoarthritis. In a previous study, a higher incidence of acute flares was observed during the initial marked decrease in serum urate level. Our study evaluated the effect of early urate-lowering therapy in patients with acute GA flares. Methods This study included 40 patients with acute GA; of them, 20 received colchicine 0.5 mg colchicine twice daily, while 20 received probenecid 500 mg and colchicine 0.5 mg twice daily. We evaluated GA severity and laboratory data for 2 weeks after the initial therapy. Medians and interquartile ranges (IQRs) were calculated to evaluate clinical presentations between these two groups. Results Rapidly decreasing median serum uric acid levels was found in the patients treated with probenecid and colchicine compared with the patients treated with colchicine alone on day 8 (− 1.9 [IQR, − 3.7 to 0] vs 0.8 [IQR, − 0.1–2.2]; P < 0.001). However, the median decrease in visual analog scale score did not differ significantly between the two groups (− 5.5 [IQR, − 8.0 to − 3.0] vs − 3.5 [IQR, − 5.9 to − 2.0]; P = 0.080). Conclusion No significant increase was noted in acute gout flare severity or duration among GA patients treated with early aggressive control of hyperuricemia using probenecid plus colchicine.
<h4>Objective</h4>General anesthesia can disturb the hormone levels in surgical patients. Hormone deficiency is one of the major symptoms of craniopharyngioma (CP) in pediatric patients. The aim of this prospective randomized controlled clinical study is to evaluate whether propofol and sevoflurane influence the perioperative hormone levels in these patients and to determine which anesthesia technique causes less impact on hormone levels.<h4>Materials</h4>Sixty-four ASA I and II pediatric patients with CP undergoing elective neurosurgery were randomly divided into the sevoflurane group (S group, n = 32) and the propofol group (P group, n = 32). Anesthesia was maintained with sevoflurane and propofol until the end of the operation. Demographic information, operation information and hemodynamic variables were recorded. The levels of hormones were evaluated preoperatively as the baseline (T0), 1h after the beginning of the operation (T1), immediately at the end of the operation (T2) and 72 h postoperatively (T3).<h4>Results</h4>There were no significant differences in the two groups in terms of patients' demographics and intraoperative information, such as operation duration, blood loss and transfusion volumes, and fluid infusion volume (P>0.05). In both groups, compared to those at T0, the levels of TSH, FT3, TT3 and ACTH at T1, T2 and T3 were significantly lower. The levels of FSH, PRL and GH at T3 were also significantly lower (P<0.05). The FT3 and TT3 levels of both groups at T2 and T3 were significantly lower than those at T1, but the ACTH level was significantly increased (P<0.05). Compared to the levels at T2, the TSH, FT3, FT4 and ACTH levels of the two groups at T3 were significantly reduced (P<0.05). The baseline hormone levels of both groups were similar (P>0.05). At T1, the FT3, TT3, FT4, TT4 and ACTH levels in the P group were significantly lower than those in the S group (P<0.05). At T2, the TT3 and ACTH levels of the P group were significantly lower than those of the S group (P<0.05) At T3, the TT4 level in the P group was significantly lower than that of the S group (P<0.05).<h4>Conclusion</h4>Propofol and sevoflurane could reduce the levels of hormones intraoperatively and postoperatively in pediatric patients with craniopharyngioma. However, propofol reduced hormone levels more intensively, mainly intraoperatively. Postoperatively, propofol and sevoflurane had similar inhibition effects on the shift in hormone levels. Therefore, in pediatric patients with craniopharyngioma undergoing neurosurgery, sevoflurane might be the preferred anesthetic because it causes less interruption of hormone levels. However, because of their similar postoperative effects, which long-term effects of sevoflurane or propofol could produce optimal clinical situations? Thus more extensive clinical studies are needed.<h4>Trial registration</h4>Clinical trial registration. This trail was registered at Chinese Clinical Trial Registry (http://www.chictr.org.cn, Jun Xiong) on 28/12/2021, registration number was ChiCTR2100054885.
Dongyeop Jang, Tae-Rim Yun, Choong-Yeol Lee
et al.
Traditional Korean medicine (TKM) emphasizes individualized diagnosis and treatment. This uniqueness makes AI modeling difficult due to limited data and implicit processes. Large language models (LLMs) have demonstrated impressive medical inference, even without advanced training in medical texts. This study assessed the capabilities of GPT-4 in TKM, using the Korean National Licensing Examination for Korean Medicine Doctors (K-NLEKMD) as a benchmark. The K-NLEKMD, administered by a national organization, encompasses 12 major subjects in TKM. We optimized prompts with Chinese-term annotation, English translation for questions and instruction, exam-optimized instruction, and self-consistency. GPT-4 with optimized prompts achieved 66.18% accuracy, surpassing both the examination's average pass mark of 60% and the 40% minimum for each subject. The gradual introduction of language-related prompts and prompting techniques enhanced the accuracy from 51.82% to its maximum accuracy. GPT-4 showed low accuracy in subjects including public health & medicine-related law, internal medicine (2) which are localized in Korea and TKM. The model's accuracy was lower for questions requiring TKM-specialized knowledge. It exhibited higher accuracy in diagnosis-based and recall-based questions than in intervention-based questions. A positive correlation was observed between the consistency and accuracy of GPT-4's responses. This study unveils both the potential and challenges of applying LLMs to TKM. These findings underline the potential of LLMs like GPT-4 in culturally adapted medicine, especially TKM, for tasks such as clinical assistance, medical education, and research. But they also point towards the necessity for the development of methods to mitigate cultural bias inherent in large language models and validate their efficacy in real-world clinical settings.
Gelagey Baye Temesgen,1 Menakath Menon,2 Solomon Tebeje Gizaw,2 Bayu Wondimneh Yimenu,1 Melaku Mekonen Agidew3 1Department of Biomedical Sciences, Debre Markos University, Debre Markos, Ethiopia; 2Department of Medical Biochemistry School of Medicine, College of Health Sciences Addis Ababa University, Addis Ababa, Ethiopia; 3Department of Medical Biochemistry, School of Medicine, Debre Tabor University, Debre Tabor, EthiopiaCorrespondence: Gelagey Baye Temesgen Tel +251 918479703Fax +251 587780673Email gelagaybaye@gmail.comIntroduction: H. pylori are gram-negative, microaerophilic helical-shaped bacteria with multiple flagella and commonly exist in the stomach. This infection may cause significant mucosal inflammation and damage, leading to ulcers in the stomach. It can also affect organ systems external to the gastrointestinal tract. To assess cardiovascular risk factors and to predict cardiovascular disorders, we are evaluating and comparing lipid profile and inflammatory marker between H. pylori-positive and negative patients.Objective: To evaluate and compare lipid profile (TC; TG; LDL; HDL) and inflammatory marker (hs-CRP) in dyspeptic patients with and without H. pylori infection.Methods: Comparative cross-sectional study was conducted from September 2020 to January 2021 at Debre Markos Referral Hospital, Debre Markos Health Center, and Hidassie Health Center, Ethiopia. Each of 50 H. pylori-positive and negative dyspeptic patients were studied. The data were checked for completeness and analyzed by SPSS version 25.0 Software. A p-value < 0.05 was considered statistically significant.Results: Serum mean high-density lipoprotein (HDL) values were 37.54 ± 7.98 mg/dL and 43.12 ± 7.86 mg/dL (p < 0.05) for H. pylori-positive and negative dyspeptic patients, respectively, and median serum high sensitive C reactive protein (hs-CRP) levels were 6.29 mg/L (1.66– 41.34) and 3.35 mg/L (0.39– 10.01) (p < 0.05) for H. pylori-positive and negative dyspeptic patients, respectively.Conclusion: H. pylori infection significantly alters serum high-density lipoprotein (HDL) and high sensitive C reactive protein (hs-CRP) levels in dyspeptic patients, as a result, increase the potential risk of cardiovascular diseases.Keywords: H. pylori, dyspepsia, lipid profile, hs-CRP, inflammation, cardiovascular diseases
Circadian clocks are highly conserved transcriptional regulators that control ~24 hr oscillations in gene expression, physiological function, and behavior. Circadian clocks exist in almost every tissue and are thought to control tissue-specific gene expression and function, synchronized by the brain clock. Many disease states are associated with loss of circadian regulation. How and when circadian clocks fail during pathogenesis remains largely unknown because it is currently difficult to monitor tissue-specific clock function in intact organisms. Here, we developed a method to directly measure the transcriptional oscillation of distinct neuronal and peripheral clocks in live, intact Drosophila, which we term Locally Activatable BioLuminescence, or LABL. Using this method, we observed that specific neuronal and peripheral clocks exhibit distinct transcriptional properties. Loss of the receptor for PDF, a circadian neurotransmitter critical for the function of the brain clock, disrupts circadian locomotor activity but not all tissue-specific circadian clocks. We found that, while peripheral clocks in non-neuronal tissues were less stable after the loss of PDF signaling, they continued to oscillate. We also demonstrate that distinct clocks exhibit differences in their loss of oscillatory amplitude or their change in period, depending on their anatomical location, mutation, or fly age. Our results demonstrate that LABL is an effective tool that allows rapid, affordable, and direct real-time monitoring of individual clocks in vivo.
Omayma O Abdelaleem, Olfat G. Shaker, Mohamed M. Mohamed
et al.
Background: Ischemic stroke is one of the serious complications of diabetes. Non-coding RNAs are established as promising biomarkers for diabetes and its complications. The present research investigated the expression profiles of serum TUG1, LINC00657, miR-9, and miR-106a in diabetic patients with and without stroke.Methods: A total of 75 diabetic patients without stroke, 77 patients with stroke, and 71 healthy controls were recruited in the current study. The serum expression levels of TUG1, LINC00657, miR-9, and miR-106a were assessed using quantitative real-time polymerase chain reaction assays.Results: We observed significant high expression levels of LINC00657 and miR-9 in the serum of diabetic patients without stroke compared to control participants. At the same time, we found marked increases of serum TUG1, LINC00657, and miR-9 and a marked decrease of serum miR-106a in diabetic patients who had stroke relative to those without stroke. Also, we revealed positive correlations between each of TUG1, LINC00657, and miR-9 and the National Institutes of Health Stroke Scale (NIHSS). However, there was a negative correlation between miR-106a and NIHSS. Finally, we demonstrated a negative correlation between LINC00657 and miR-106a in diabetic patients with stroke.Conclusion: Serum non-coding RNAs, TUG1, LINC00657, miR-9, and miR-106a displayed potential as novel molecular biomarkers for diabetes complicated with stroke, suggesting that they might be new therapeutic targets for the treatment of diabetic patients with stroke.
Precision medicine provides customized treatments to patients based on their characteristics and is a promising approach to improving treatment efficiency. Large scale omics data are useful for patient characterization, but often their measurements change over time, leading to longitudinal data. Random forest is one of the state-of-the-art machine learning methods for building prediction models, and can play a crucial role in precision medicine. In this paper, we review extensions of the standard random forest method for the purpose of longitudinal data analysis. Extension methods are categorized according to the data structures for which they are designed. We consider both univariate and multivariate responses and further categorize the repeated measurements according to whether the time effect is relevant. Information of available software implementations of the reviewed extensions is also given. We conclude with discussions on the limitations of our review and some future research directions.
Muhammad M Hammami, 1, 2 Muhammad B Hammami, 3 Reem Aboushaar 4 1Clinical Studies and Empirical Ethics Department, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia; 2Alfaisal University College of Medicine, Riyadh, Saudi Arabia; 3Division of Gastroenterology, Department of Medicine, John Hopkins University, Baltimore, MD, USA; 4MS IV, Florida Atlantic University, Boca Raton, FL, USACorrespondence: Muhammad M HammamiClinical Studies and Empirical Ethics Department, King Faisal Specialist Hospital and Research Centre, P O Box # 3354 (MBC 03), Riyadh 11211, Saudi ArabiaTel +966-11-442-4527Fax +966-11-442-7894Email Muhammad@kfshrc.edu.saBackground: Organ donation is commonly evaluated by biomedical ethicists based largely on principlism with autonomy at the top of the “moral mountain.” Lay people may differ in the way they invoke and balance the various ethical interests. We explored lay people’s ethical attitudes to organ donation.Methods: Respondents (n=196) ranked 42 opinion-statements on organ donation according to a 9-category symmetrical distribution. Statements’ scores were analyzed by averaging-analysis and Q-methodology.Results: Respondents’ mean (SD) age was 34.5 (10.6) years, 53% were women, 69% Muslims (30% Christians), 29% Saudis (26% Filipinos), and 38% healthcare-related. The most-agreeable statements were “Acceptable if benefit to recipient large,” “Explicit donor consent and family approval for live donation,” “Acceptable if directed to family member,” and “Explicit donor consent and family approval for postmortem donation.” The most-disagreeable statements were “Donor consent and family approval not required for postmortem donation,” “Acceptable with purely materialistic motivation,” and “Only donor no-known objection for postmortem donation.” Women, Christians, and healthcare respondents gave higher rank to “Explicit donor consent and family approval for live donation,” “Only donor family consent required for postmortem donation,” and “Acceptable if organ distribution equitable,” respectively, and Muslims gave more weight to donor/family harm (p ≤ 0.001). Q-methodology identified various ethical resolution models that were associated with religious affiliation and included relatively “motives-concerned,” “family-benefit-concerned,” “familism-oriented,” and “religious or non-religious altruism-concerned” models. Of 23 neutral statements on averaging-analysis, 48% and 65% received extreme ranks in ≥ 1 women and men Q-methodology models, respectively.Conclusion: 1) On average, recipient benefit, requirement of both explicit donor consent and family approval, donor-recipient relationship, and motives were predominant considerations; 2) ranking of some statements was associated with respondents’ demographics; 3) Q-methodology identified various ethical resolution models that were partially masked by averaging-analysis; and 4) strong virtue and familism approaches in our respondents provide some empirical evidence against principlism adequacy.Keywords: organ donation, familism, virtue, ethics of care, principlism, Q-methodology