Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review.

When technical requirements are high, and patient outcomes are critical, opportunities for monitoring and improving surgical skills via objective motion analysis feedback may be particularly beneficial. This narrative review synthesises work on technical and non-technical surgical skills, collaborative task performance, and pose estimation to illustrate new opportunities to advance cardiothoracic surgical performance with innovations from computer vision and artificial intelligence. These technological innovations are critically evaluated in terms of the benefits they could offer the cardiothoracic surgical community, and any barriers to the uptake of the technology are elaborated upon. Like some other specialities, cardiothoracic surgery has relatively few opportunities to benefit from tools with data capture technology embedded within them (as is possible with robotic-assisted laparoscopic surgery, for example). In such cases, pose estimation techniques that allow for movement tracking across a conventional operating field without using specialist equipment or markers offer considerable potential. With video data from either simulated or real surgical procedures, these tools can (1) provide insight into the development of expertise and surgical performance over a surgeon's career, (2) provide feedback to trainee surgeons regarding areas for improvement, (3) provide the opportunity to investigate what aspects of skill may be linked to patient outcomes which can (4) inform the aspects of surgical skill which should be focused on within training or mentoring programmes. Classifier or assessment algorithms that use artificial intelligence to 'learn' what expertise is from expert surgical evaluators could further assist educators in determining if trainees meet competency thresholds. With collaborative efforts between surgical teams, medical institutions, computer scientists and researchers to ensure this technology is developed with usability and ethics in mind, the developed feedback tools could improve cardiothoracic surgical practice in a data-driven way.

Pose-based tremor type and level analysis for Parkinson's disease from video.

PURPOSE: Current methods for diagnosis of PD rely on clinical examination. The accuracy of diagnosis ranges between 73 and 84%, and is influenced by the experience of the clinical assessor. Hence, an automatic, effective and interpretable supporting system for PD symptom identification would support clinicians in making more robust PD diagnostic decisions. METHODS: We propose to analyze Parkinson's tremor (PT) to support the analysis of PD, since PT is one of the most typical symptoms of PD with broad generalizability. To realize the idea, we present SPA-PTA, a deep learning-based PT classification and severity estimation system that takes consumer-grade videos of front-facing humans as input. The core of the system is a novel attention module with a lightweight pyramidal channel-squeezing-fusion architecture that effectively extracts relevant PT information and filters noise. It enhances modeling performance while improving system interpretability. RESULTS: We validate our system via individual-based leave-one-out cross-validation on two tasks: the PT classification task and the tremor severity rating estimation task. Our system presents a 91.3% accuracy and 80.0% F1-score in classifying PT with non-PT class, while providing a 76.4% accuracy and 76.7% F1-score in more complex multiclass tremor rating classification task. CONCLUSION: Our system offers a cost-effective PT classification and tremor severity estimation results as warning signs of PD for undiagnosed patients with PT symptoms. In addition, it provides a potential solution for supporting PD diagnosis in regions with limited clinical resources.

No need for fasting prior to doppler ultrasound of pediatric liver transplants: A self-controlled study.

BACKGROUND: Children frequently undergo routine Doppler-ultrasound (DUS) after liver transplantation (LT) for which they are fasted, but this may cause hunger and discomfort. OBJECTIVE: To determine if DUS measurements, with focus on the portal vein (PV), are affected by prandial changes, and if this affects distress and feasibility of the DUS. MATERIALS AND METHODS: Children were prospectively included to undergo a pre- and postprandial DUS on the same day at 6 months after LT. Pre- and anastomotic PV peak systolic velocity (PSV), and hepatic artery and hepatic vein DUS measurements were obtained. Pre- and postprandial measurements, and relative postprandial change of PV velocity ratio (VR) compared to PV anastomotic PSV, were compared using paired-sample t-tests and intraclass correlation coefficients (ICC). Obscuration by bowel gas, difficulty of DUS, and impact of fasting were assessed using 5-point rating scales. RESULTS: Twenty-eight children (median age 3.5 years, IQR 1.6-10.8) were included; four were subsequently excluded because they were not fasted (N = 2) or withdrew consent for the second DUS (N = 2). Measurements between pre- and postprandial DUS, and relative postprandial change of VR compared to PV anastomotic PSV, were not significantly different (p > .05). Test consistency was good (ICC = 0.69, 95% CI = 0.29-0.67) for PV anastomotic PSV, and excellent (95% CI = 0.61-0.93) for PV VR. Obscuration by bowel gas or ease of DUS did not change after eating (p > .05). The majority (16/28, 57.2%) found fasting difficult, and several (13/28, 46.4%) got upset when fasted. CONCLUSION: Children with an LT do not need to be fasted for routine DUS, which may decrease the burden of the examination.

Treatment strategies for hepatic artery complications after pediatric liver transplantation: A systematic review.

This study aimed to evaluate the effectiveness of different treatments for hepatic artery thrombosis (HAT) and hepatic artery stenosis (HAS) after pediatric liver transplantation. We systematically reviewed studies published since 2000 that investigated the management of HAT and/or HAS after pediatric liver transplantation. Studies with a minimum of 5 patients in one of the treatment methods were included. The primary outcomes were technical success rate and graft and patient survival. The secondary outcomes were hepatic artery patency, complications, and incidence of HAT and HAS. Of 3570 studies, we included 19 studies with 328 patients. The incidence was 6.2% for HAT and 4.1% for HAS. Patients with an early HAT treated with surgical revascularization had a median graft survival of 45.7% (interquartile range, 30.7%-60%) and a patient survival of 61.3% (interquartile range, 58.7%-66.9%) compared with the other treatments (conservative, endovascular revascularization, or retransplantation). As for HAS, endovascular and surgical revascularization groups had a patient survival of 85.7% and 100% (interquartile range, 85%-100%), respectively. Despite various treatment methods, HAT after pediatric liver transplantation remains a significant issue that has profound effects on the patient and graft survival. Current evidence is insufficient to determine the most effective treatment for preventing graft failure.

Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising.

In many human-computer interaction applications, fast and accurate hand tracking is necessary for an immersive experience. However, raw hand motion data can be flawed due to issues such as joint occlusions and high-frequency noise, hindering the interaction. Using only current motion for interaction can lead to lag, so predicting future movement is crucial for a faster response. Our solution is the Multi-task Spatial-Temporal Graph Auto-Encoder (Multi-STGAE), a model that accurately denoises and predicts hand motion by exploiting the inter-dependency of both tasks. The model ensures a stable and accurate prediction through denoising while maintaining motion dynamics to avoid over-smoothed motion and alleviate time delays through prediction. A gate mechanism is integrated to prevent negative transfer between tasks and further boost multi-task performance. Multi-STGAE also includes a spatial-temporal graph autoencoder block, which models hand structures and motion coherence through graph convolutional networks, reducing noise while preserving hand physiology. Additionally, we design a novel hand partition strategy and hand bone loss to improve natural hand motion generation. We validate the effectiveness of our proposed method by contributing two large-scale datasets with a data corruption algorithm based on two benchmark datasets. To evaluate the natural characteristics of the denoised and predicted hand motion, we propose two structural metrics. Experimental results show that our method outperforms the state-of-the-art, showcasing how the multi-task framework enables mutual benefits between denoising and prediction.

Abnormal glucose homeostasis and fasting intolerance in patients with congenital porto-systemic shunts.

In physiological glucose homeostasis, the liver plays a crucial role in the extraction of glucose from the portal circulation and storage as glycogen to enable release through glycogenolysis upon fasting. In addition, insulin secreted by the pancreas is partly eliminated from the systemic circulation by hepatic first-pass. Therefore, patients with a congenital porto-systemic shunt present a unique combination of (a) postabsorptive hyperinsulinemic hypoglycaemia (HH) because of decreased insulin elimination and (b) fasting (ketotic) hypoglycaemia because of decreased glycogenolysis. Patients with porto-systemic shunts therefore provide important insight into the role of the portal circulation and hepatic function in different phases of glucose homeostasis.

Management of Guillain-Barré syndrome in Bangladesh: Clinical practice, limitations and recommendations for low- and middle-income countries.

BACKGROUND AND AIMS: Considerable variation in clinical practice for management of Guillain-Barré syndrome (GBS) has been observed worldwide. Diagnosis and treatment are challenging in low- and middle-income countries (LMIC) due to lack of facilities and treatment availability. We aimed to evaluate current clinical practice and limitations and to provide recommendation for GBS management in low-resource settings. METHODS: We conducted an explanatory-sequential mixed-methods survey among neurologists and internists working in tertiary and secondary government hospitals in Bangladesh. There were two phases: (1) quantitative (cross-sectional survey to evaluate clinical practice and limitations); (2) qualitative (key informant interview to explain certain clinical practice and provide recommendations for GBS management in LMIC). Data were analyzed by frequencies, χ2 test and thematic analysis. RESULTS: Among 159 physicians (65 neurologists and 94 internists), 11% and 8% physicians used Brighton and NINDS criteria respectively to diagnose GBS. Specific treatment protocols of GBS were used by 12% physicians. Overcrowding of patients, inadequate diagnostic facilities, high costs of standard therapy, and inadequate logistics and trained personnel for intensive care unit and rehabilitation services were considered major challenges for GBS management. In qualitative part, respondents recommended regular training for the physicians, development of cost-effective treatment strategies and appropriate patients' referral and management guideline considering existing limitations in health service delivery and socio-economic status of the country. INTERPRETATION: Current study design and recommendations might be applied for other LMIC. Such data can assist policymakers to identify areas requiring urgent attention and take required action to improve GBS management in LMIC.

Prevalence, management and efficacy of treatment in portal vein obstruction after paediatric liver transplantation: protocol of the retrospective international multicentre PORTAL registry.

INTRODUCTION: Portal vein obstruction (PVO) consists of anastomotic stenosis and thrombosis, which occurs due to a progression of the former. The aim of this large-scale international study is to assess the prevalence, current management practices and efficacy of treatment in patients with PVO. METHODS AND ANALYSIS: The Portal vein Obstruction Revascularisation Therapy After Liver transplantation registry will facilitate an international, retrospective, multicentre, observational study, with 25 centres around the world already actively involved. Paediatric patients (aged <18 years) with a diagnosed PVO between 1 January 2001 and 1 January 2021 after liver transplantation will be eligible for inclusion. The primary endpoints are the prevalence of PVO, primary and secondary patency after PVO intervention and current management practices. Secondary endpoints are patient and graft survival, severe complications of PVO and technical success of revascularisation techniques. ETHICS AND DISSEMINATION: Medical Ethics Review Board of the University Medical Center Groningen has approved the study (METc 2021/072). The results of this study will be disseminated via peer-reviewed publications and scientific presentations at national and international conferences. TRIAL REGISTRATION NUMBER: Netherlands Trial Register (NL9261).

A Video-Based Augmented Reality System for Human-in-the-Loop Muscle Strength Assessment of Juvenile Dermatomyositis.

As the most common idiopathic inflammatory myopathy in children, juvenile dermatomyositis (JDM) is characterized by skin rashes and muscle weakness. The childhood myositis assessment scale (CMAS) is commonly used to measure the degree of muscle involvement for diagnosis or rehabilitation monitoring. On the one hand, human diagnosis is not scalable and may be subject to personal bias. On the other hand, automatic action quality assessment (AQA) algorithms cannot guarantee 100% accuracy, making them not suitable for biomedical applications. As a solution, we propose a video-based augmented reality system for human-in-the-loop muscle strength assessment of children with JDM. We first propose an AQA algorithm for muscle strength assessment of JDM using contrastive regression trained by a JDM dataset. Our core insight is to visualize the AQA results as a virtual character facilitated by a 3D animation dataset, so that users can compare the real-world patient and the virtual character to understand and verify the AQA results. To allow effective comparisons, we propose a video-based augmented reality system. Given a feed, we adapt computer vision algorithms for scene understanding, evaluate the optimal way of augmenting the virtual character into the scene, and highlight important parts for effective human verification. The experimental results confirm the effectiveness of our AQA algorithm, and the results of the user study demonstrate that humans can more accurately and quickly assess the muscle strength of children using our system.

Effectiveness and safety of catheter-directed thrombolysis in conjunction with percutaneous mechanical thrombectomy for acute iliofemoral deep vein thrombosis: A meta-analysis.

BACKGROUND: Patients with severe acute low iliofemoral deep vein thrombosis (DVT), such as phlegmasia cerulea dolens, benefit from catheter-directed thrombolysis (CDT). This meta-analysis investigated the effectiveness and safety of adjuvant percutaneous mechanical thrombectomy (PMT) during CDT compared with CDT alone in the treatment of acute iliofemoral DVT. METHODS: A meta-analysis was performed in accordance with the PRISMA guidelines. Medline, Embase, the Cochrane Library, China National Knowledge Internet, and Wanfang data were searched for studies on the management of acute iliofemoral DVT by means of CDT or CDT with adjuvant PMT. Randomized, controlled trials and nonrandomized studies were included. The primary outcomes were venous patency rate, major bleeding complications, and post-thrombotic syndrome occurrence within 2 years of the procedure. The secondary outcomes were thrombolytic time and volume, as well as the rates of thigh detumescence and iliac vein stenting. RESULTS: The meta-analysis included 20 eligible studies with a total of 1686 patients. The rates of venous patency (mean difference, 10.11; 95% confidence interval [CI], 5.59-14.62) and thigh detumescence (mean difference, 3.64; 95% CI, 1.10-6.18) of the adjuvant PMT group were higher than those of the CDT alone group. Compared with CDT alone, the adjuvant PMT group experienced fewer incidences of major bleeding complications (odds ratio, 0.45; 95% CI, 0.26-0.77) and occurrences of post-thrombotic syndrome within 2 years of the procedure (odds ratio, 0.55; 95% CI, 0.33-0.92). Furthermore, the duration of thrombolytic therapy was shorter, and the total dose of administered thrombolytics was lower with adjuvant PMT. CONCLUSIONS: Adjuvant PMT during CDT is associated with improved clinical outcomes and a lower incidence of major bleeding complications. The studies investigated were, however, single-center cohort studies, and future randomized controlled trials are needed to substantiate these findings.

Doppler-ultrasound reference values after pediatric liver transplantation: a consecutive cohort study.

OBJECTIVES: Doppler ultrasound (DUS) is the main imaging modality to evaluate vascular complications of pediatric liver transplants (LT). The current study aimed to determine reference values and their change over time. METHODS: A consecutive cohort of pediatric patients undergoing an LT were retrospectively included between 2015 and 2020. Timepoints for standardized DUS were intra-operative and postoperative (day 0), days 1-7, months 1 and 3, and years 1 and 2. DUS measurements of the hepatic artery (HA), portal vein (PV), and hepatic vein(s) (HV) were included if there were no complications during 2 years follow-up. Measurements consisted of: peak systolic velocity (PSV) and resistive index (RI) for the HA, PSV for the PV, and venous pulsatility index (VPI) for the HV. Generalized estimating equations were used to analyze change over time. RESULTS: One hundred twelve pediatric patients with 123 LTs were included (median age 3.3 years, interquartile range 0.7-10.1). Ninety-five HAs, 100 PVs, and 115 HVs without complications were included. Reference values for HA PSV and RI, PV PSV, and HV VPI were obtained for all timepoints (4043 included data points in total) and presented using 5th-95th percentiles and threshold values. All reference values changed significantly over time (p = 0.032 to p < 0.001). CONCLUSIONS: DUS reference values of hepatic vessels in children after LT are presented, reference values change over time with specific vessel-dependent patterns. Timepoint-specific reference values improve the interpretation of DUS values and may help to better weigh their clinical significance. KEY POINTS: • Doppler ultrasound reference values of pediatric liver transplantations are not static but change over time. Applying the correct reference values for the specific timepoint may further improve the interpretation of the measurements. • The pattern of change over time of Doppler ultrasound measurements differs between the hepatic vessel and measurement; knowledge of these patterns may help radiologists to better understand normal postoperative hemodynamic changes.

Waitlist mortality of young patients with biliary atresia: Impact of allocation policy and living donor liver transplantation.

Patients with biliary atresia (BA) below 2 years of age in need of a transplantation largely rely on partial grafts from deceased donors (deceased donor liver transplantation [DDLT]) or living donors (living donor liver transplantation [LDLT]). Because of high waitlist mortality in especially young patients with BA, the Eurotransplant Liver Intestine Advisory Committee (ELIAC) has further prioritized patients with BA listed before their second birthday for allocation of a deceased donor liver since 2014. We evaluated whether this Eurotransplant (ET) allocation prioritization changed the waitlist mortality of young patients with BA. We used a pre-post cohort study design with the implementation of the new allocation rule between the two periods. Participants were patients with BA younger than 2 years who were listed for liver transplantation in the ET database between 2001 and 2018. Competing risk analyses were performed to assess waitlist mortality in the first 2 years after listing. We analyzed a total of 1055 patients with BA, of which 882 had been listed in the preimplementation phase (PRE) and 173 in the postimplementation phase (POST). Waitlist mortality decreased from 6.7% in PRE to 2.3% in POST ( p = 0.03). Interestingly, the proportion of young patients with BA undergoing DDLT decreased from 32% to 18% after ET allocation prioritization ( p = 0.001), whereas LDLT increased from 55% to 74% ( p = 0.001). The proportional increase in LDLT decreased the median waitlist duration of transplanted patients from 1.5 months in PRE to 0.85 months in POST ( p = 0.003). Since 2014, waitlist mortality in young patients with BA has strongly decreased in the ET region. Rather than associated with prioritized allocation of deceased donor organs, the decreased waitlist mortality was related to a higher proportion of patients undergoing LDLT.

Ultrasound-based "CEUS-Bosniak"classification for cystic renal lesions: an 8-year clinical experience.

PURPOSE: Renal cysts comprise benign and malignant entities. Risk assessment profits from CT/MRI imaging using the Bosniak classification. While Bosniak-IIF, -III, and -IV cover complex cyst variants, Bosniak-IIF and -III stand out due to notorious overestimation. Contrast-enhanced ultrasound (CEUS) is promising to overcome this deficit but warrants standardization. This study addresses the benefits of a combined CEUS and CT/MRI evaluation of renal cysts. The study provides a realistic account of kidney tumor boards' intricacies in trying to validate renal cysts. METHODS: 247 patients were examined over 8 years. CEUS lesions were graded according to CEUS-Bosniak (IIF, III, IV). 55 lesions were resected, CEUS-Bosniak- and CT/MRI-Bosniak-classification were correlated with histopathological diagnosis. Interobserver agreement between the classifications was evaluated statistically. 105 lesions were followed by ultrasound, and change in CEUS-Bosniak-types and lesion size were documented. RESULTS: 146 patients (156 lesions) were included. CEUS classified 67 lesions as CEUS-Bosniak-IIF, 44 as CEUS-Bosniak-III, and 45 as CEUS-Bosniak-IV. Histopathology of 55 resected lesions revealed benign cysts in all CEUS-Bosniak-IIF lesions (2/2), 40% of CEUS-Bosniak-III and 8% of CEUS-Bosniak-IV, whereas malignancy was uncovered in 60% of CEUS-Bosniak-III and 92% of CEUS-Bosniak-IV. Overall, CEUS-Bosniak-types matched CT/MRI-Bosniak types in 58% (fair agreement, κ = 0.28). CEUS-Bosniak resulted in higher stages than CT/MRI-Bosniak (40%). Ultrasound follow-up of 105 lesions detected no relevant differences between CEUS-Bosniak-types concerning cysts size. 99% of lesions showed the same CEUS-Bosniak-type. CONCLUSION: The CEUS-Bosniak classification is an essential tool in clinical practice to differentiate and monitor renal cystic lesions and empowers diagnostic work-up and patient care.

Doppler Ultrasound of Vascular Complications After Pediatric Liver Transplantation: Incidence, Time of Detection, and Positive Predictive Value.

Purpose Doppler ultrasound (DUS) is widely used to detect vascular complications after pediatric liver transplantation (LT). This study aimed to assess the moment of first detection of vascular complications with DUS, and to determine the positive predictive value (PPV) of DUS. Materials and Methods Patients aged 0-18 years who underwent LT between 2015 and 2019 were retrospectively included. 92 LTs in 83 patients were included (median age: 3.9 years, interquartile range: 0.7-10.5). Patients underwent perioperative (intra-operative and immediately postoperative) and daily DUS surveillance during the first postoperative week, and at 1, 3, and 12 months. Vascular complications were categorized for the hepatic artery, portal vein, and hepatic veins. DUS findings were compared to surgical or radiological findings during the 1-year follow-up. Results 52 vascular complications were diagnosed by DUS in 35/92 LTs (38%). 15 out of 52 (28.8%) were diagnosed perioperatively, 29/52 (55.8%) were diagnosed on postoperative days 1-7, and 8/52 (15.4%) after day 7. The PPV for all vascular complications diagnosed with DUS was 92.3%. During the 1-year follow-up, 18/19 (94.7%) hepatic artery complications, 19/26 (73.1%) portal vein complications, and 7/7 (100%) hepatic vein complications were diagnosed perioperatively or during the first week. Conclusion The majority of vascular complications during the first year after pediatric LT were diagnosed by DUS perioperatively or during the first week, with a high PPV. Our findings provide important information regarding when to expect different types of vascular complications on DUS, which might improve DUS post-LT surveillance protocols.

A Two-stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction.

Musculoskeletal and neurological disorders are the most common causes of walking problems among older people, and they often lead to diminished quality of life. Analyzing walking motion data manually requires trained professionals and the evaluations may not always be objective. To facilitate early diagnosis, recent deep learning-based methods have shown promising results for automated analysis, which can discover patterns that have not been found in traditional machine learning methods. We observe that existing work mostly applies deep learning on individual joint features such as the time series of joint positions. Due to the challenge of discovering inter-joint features such as the distance between feet (i.e. the stride width) from generally smaller-scale medical datasets, these methods usually perform sub-optimally. As a result, we propose a solution that explicitly takes both individual joint features and inter-joint features as input, relieving the system from the need of discovering more complicated features from small data. Due to the distinctive nature of the two types of features, we introduce a two-stream framework, with one stream learning from the time series of joint position and the other from the time series of relative joint displacement. We further develop a mid-layer fusion module to combine the discovered patterns in these two streams for diagnosis, which results in a complementary representation of the data for better prediction performance. We validate our system with a benchmark dataset of 3D skeleton motion that involves 45 patients with musculoskeletal and neurological disorders, and achieve a prediction accuracy of 95.56%, outperforming state-of-the-art methods.

MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray.

Computed tomography (CT) is an effective med-ical imaging modality, widely used in the field of clinical medicine for the diagnosis of various pathologies. Advances in Multidetector CT imaging technology have enabled additional functionalities, including generation of thin slice multi planar cross-sectional body imaging and 3D reconstructions. However, this involves patients being exposed to a considerable dose of ionising radiation. Excessive ionising radiation can lead to deterministic and harmful effects on the body. This paper proposes a Deep Learning model that learns to reconstruct CT projections from a few or even a single-view X-ray. This is based on a novel architecture that builds from neural radiance fields, which learns a continuous representation of CT scans by disentangling the shape and volumetric depth of surface and internal anatomical structures from 2D images. Our model is trained on chest and knee datasets, and we demonstrate qual-itative and quantitative high-fidelity renderings and compare our approach to other recent radiance field-based methods. Our code and link to our datasets are available at https://qithub.com/abrilcf/mednerf Clinical relevance- Our model is able to infer the anatomical 3D structure from a few or a single-view X-ray showing future potential for reduced ionising radiation exposure during the imaging process.

Cerebral Palsy Prediction with Frequency Attention Informed Graph Convolutional Networks.

Early diagnosis and intervention are clinically con-sidered the paramount part of treating cerebral palsy (CP), so it is essential to design an efficient and interpretable automatic prediction system for CP. We highlight a significant difference between CP infants' frequency of human movement and that of the healthy group, which improves prediction performance. However, the existing deep learning-based methods did not use the frequency information of infants' movement for CP prediction. This paper proposes a frequency attention informed graph convolutional network and validates it on two consumer-grade RGB video datasets, namely MINI-RGBD and RVI-38 datasets. Our proposed frequency attention module aids in improving both classification performance and system interpretability. In addition, we design a frequency-binning method that retains the critical frequency of the human joint position data while filtering the noise. Our prediction performance achieves state-of-the-art research on both datasets. Our work demonstrates the effectiveness of frequency information in supporting the prediction of CP non-intrusively and provides a way for supporting the early diagnosis of CP in the resource-limited regions where the clinical resources are not abundant.

Validation and adjustment of modified Erasmus GBS outcome score in Bangladesh.

OBJECTIVE: We have assessed and improved the performance of the modified Erasmus GBS Outcome Score (mEGOS) among patients with Guillain-Barré syndrome (GBS) from Bangladesh. METHODS: Validation cohort consisted of patients with GBS from two prospective cohort studies in Bangladesh. Poor outcome was defined as being unable to walk independently at week 4 and week 26. We excluded patients able to walk independently, patients who died within the first week, or with missing GBS disability scores. Performance of mEGOS at entry and week 1 was determined based on the discriminative ability (ability to differentiate between patients able and unable to walk independently; measured using the area under the receiver operating characteristic curves [AUC]) and calibration (observed probability versus predicted probability of poor outcome). RESULTS: A total of 506 patients aged ≥6-year-old were enrolled, with 471 and 366 patients included in mEGOS validation analysis at entry and week 1, respectively. The AUC values for predicting poor outcome (1) at week 4 were 0.69 (mEGOS entry) and 0.78 (mEGOS week 1) and (2) at week 26 were 0.67 (mEGOS entry) and 0.70 (mEGOS week 1). Mean predicted probabilities of poor outcome corresponded with observed outcomes except for the probability of poor outcome at week 4 which was overestimated by mEGOS week 1. This was resolved by updating the model intercept. INTERPRETATION: The mEGOS shows valid outcome predictions among patients with GBS from Bangladesh. The model can aid the identification of patients at high risk of poor outcome and help to adequately allocate healthcare resources in low-resource settings.

Draft Genome Sequences of Four Strains of Campylobacter jejuni Isolated from Patients with Axonal Variant of Guillain-Barré Syndrome in Bangladesh.

Four Campylobacter jejuni strains (Z191005RS, Z191005SS, Z201020RS, and Z201020SS) isolated from the axonal variant of Guillain-Barré syndrome (GBS) were sequenced using Illumina technology. The average genome size was from 1.61 to 1.63 gb, with a very high coverage ranging from 654× to 758×, which facilitates the possibility of rare variant calling.

The potential and limitations of intrahepatic cholangiocyte organoids to study inborn errors of metabolism.

Inborn errors of metabolism (IEMs) comprise a diverse group of individually rare monogenic disorders that affect metabolic pathways. Mutations lead to enzymatic deficiency or dysfunction, which results in intermediate metabolite accumulation or deficit leading to disease phenotypes. Currently, treatment options for many IEMs are insufficient. Rarity of individual IEMs hampers therapy development and phenotypic and genetic heterogeneity suggest beneficial effects of personalized approaches. Recently, cultures of patient-own liver-derived intrahepatic cholangiocyte organoids (ICOs) have been established. Since most metabolic genes are expressed in the liver, patient-derived ICOs represent exciting possibilities for in vitro modeling and personalized drug testing for IEMs. However, the exact application range of ICOs remains unclear. To address this, we examined which metabolic pathways can be studied with ICOs and what the potential and limitations of patient-derived ICOs are to model metabolic functions. We present functional assays in patient ICOs with defects in branched-chain amino acid metabolism (methylmalonic acidemia), copper metabolism (Wilson disease), and transporter defects (cystic fibrosis). We discuss the broad range of functional assays that can be applied to ICOs, but also address the limitations of these patient-specific cell models. In doing so, we aim to guide the selection of the appropriate cell model for studies of a specific disease or metabolic process.