Association of elastic power in mechanical ventilation with the severity of acute respiratory distress syndrome: a retrospective study

BACKGROUND

Mechanical power (MP) is the total energy released into the entire respiratory system per minute which mainly comprises three components: elastic static power, Elastic dynamic power and resistive power. However, the energy to overcome resistance to the gas flow is not the key factor in causing lung injury, but the elastic power (EP) which generates the baseline stretch of the lung fibers and overcomes respiratory system elastance may be closely related to the ARDS severity. Thus, this study aimed to investigate whether EP is superior to other ventilator variables for predicting the severity of lung injury in ARDS patients.

METHODS

We retrieved patient data from the Medical Information Mart for Intensive Care III (MIMIC-III) database. The retrieved data involved adults (≥ 18 years) diagnosed with ARDS and subjected to invasive mechanical ventilation for ≥ 48 h. We employed univariate and multivariate logistic regression analyses to investigate the correlation between EP and development of moderate-severe ARDS. Furthermore, we utilized restricted cubic spline models to assess whether there is a linear association between EP and incidence of moderate-severe ARDS. In addition, we employed a stratified linear regression model and likelihood ratio test in subgroups to identify potential modifications and interactions.

RESULTS

Moderate-severe ARDS occurred in 73.4% (296/403) of the patients analyzed. EP and MP were significantly associated with moderate-severe ARDS (odds ratio [OR] 1.21, 95% confidence interval [CI] 1.15-1.28, p < 0.001; and OR 1.15, 95%CI 1.11-1.20, p < 0.001; respectively), but EP showed a higher area-under-curve (95%CI 0.72-0.82, p < 0.001) than plateau pressure, driving pressure, and static lung compliance in predicting ARDS severity. The optimal cutoff value for EP was 14.6 J/min with a sensitivity of 75% and specificity of 66%. Quartile analysis revealed that the relationship between EP and ARDS severity remained robust and reliable in subgroup analysis.

CONCLUSION

EP is a good ventilator variable associated with ARDS severity and can be used for grading ARDS severity. Close monitoring of EP is advised in patients undergoing mechanical ventilation. Additional experimental trials are needed to investigate whether adjusting ventilator variables according to EP can yield significant improvements in clinical outcomes.

Platelet distribution width as an useful indicator of influenza severity in children

PURPOSE

The present study aims to investigate the potential of platelet distribution width as an useful parameter to assess the severity of influenza in children.

METHODS

Baseline characteristics and laboratory results were collected and analyzed. Receiver operating characteristic (ROC) curve analysis was used to joint detection of inflammatory markers for influenza positive children, and the scatter-dot plots were used to compare the differences between severe and non-severe group.

RESULTS

Influenza B positive children had more bronchitis and pneumonia (P < 0.05), influenza A infected children had more other serious symptoms (P = 0.007). Neutrophil count, lymphocyte count, neutrophil-to-lymphocyte ratio (NLR), and platelet parameters performed differently among < 4 years and ≥ 4 years children with influenza. Combined detection of platelet parameters and other indicators could better separate healthy children from influenza infected children than single indicator detection. The levels of platelet distribution width of children with severe influenza (A and B) infection was significantly dropped, compared with non-severe group (P < 0.05).

CONCLUSIONS

Platelet distribution width could be a very useful and economic indicator in distinction and severity assessment for children with influenza.

Improved Prediction of Knee Osteoarthritis by the Machine Learning Model XGBoost

Objectives

The accurate prediction of osteoarthritis (OA) severity in patients can be helpful to make the proper decision of intervention. This study aims to build up a powerful model to assess predictive risk factors and severity of knee osteoarthritis (KOA) in the clinical scenario.

Methods

A total of 4796 KOA cases and 1205 features were selected by feature selections from the public OA database, Osteoarthritis Initiative (OAI). Six machine learning-based models were constructed and compared for the accuracy of OA prediction. The gradient-boosting decision tree was used to identify important prediction features in the extreme gradient boosting (XGBoost) model. The performance of models was evaluated by F1-score.

Results

Twenty features were determined as predictors for KOA risk and severity, including the subject characteristics, knee symptoms/risk factors and physical exam. The XGBoost model demonstrated 100% prediction accuracy for 54.7% of examined samples, and the remaining 45.3% of samples showed Kellgren and Lawrence (KL) gradings very close to the actual levels. It showed the highest prediction accuracy with an F1-score of 0.553 among the tested six models.

Conclusions

We demonstrate that the XGBoost is the best model for the prediction of KOA severity in the six examined models. In addition, 20 risk features were determined as the essential predictors of KOA, including the physical exam, knee symptoms/risk factors and subject characteristics, which may be useful for the identification of high-risk KOA cases and for making appropriate treatment decisions as well.

A novel ROS-Related chemiluminescent semiconducting polymer nanoplatform for acute pancreatitis early diagnosis and severity assessment

Acute pancreatitis (AP) is a common and potentially life-threatening inflammatory disease of the pancreas. Reactive oxygen species (ROS) play a key role in the occurrence and development of AP. With increasing ROS levels, the degree of oxidative stress and the severity of AP increase. However, diagnosing AP still has many drawbacks, including difficulties with early diagnosis and undesirable sensitivity and accuracy. Herein, we synthesized a semiconducting polymer nanoplatform (SPN) that can emit ROS-correlated chemiluminescence (CL) signals. The CL intensity increased in solution after optimization of the SPN. The biosafety of the SPN was verified in vitro and in vivo. The mechanism and sensitivity of the SPN for AP early diagnosis and severity assessment were evaluated in three groups of mice using CL intensity, serum marker evaluations and hematoxylin and eosin staining assessments. The synthetic SPN can be sensitively combined with different concentrations of ROS to produce different degrees of high-intensity CL in vitro and in vivo. Notably, the SPN shows an excellent correlation between CL intensity and AP severity. This nanoplatform represents a superior method to assess the severity of AP accurately and sensitively according to ROS related chemiluminescence signals. This research overcomes the shortcomings of AP diagnosis in clinical practice and provides a novel method for the clinical diagnosis of pancreatitis in the future.

Self-paced Multi-view Learning for CT-based severity assessment of COVID-19

Prior studies for the task of severity assessment of COVID-19 (SA-COVID) usually suffer from domain-specific cognitive deficits. They mainly focus on visual cues based on single cognitive functions but fail to reconcile the valuable information from other alternative views. Inspired by the cognitive process of radiologists, this paper shifts naturally from single-symptom measurements to a multi-view analysis, and proposes a novel Self-paced Multi-view Learning (SPML) framework for automated SA-COVID. Specifically, the proposed SPML framework first comprehensively aggregates multi-view contexts in lung infection with different measure paradigms, i.e., Global Feature Branch, Texture Feature Branch, and Volume Feature Branch. In this way, multiple-perspective clues are taken into account to reflect the most essential pathological manifestation on CT images. To alleviate small-sample learning problems, we also introduce an optimization with self-paced learning strategy to cognitively increase the characterization capabilities of training samples by learning from simple to complex. In contrast to traditional batch-wise learning, a pure self-paced way can further guarantee the efficiency and accuracy of SPML when dealing with small and biased samples. Furthermore, we construct a well-established SA-COVID dataset that contains 300 CT images with fine annotations. Extensive experiments on this dataset demonstrate that SPML consistently outperforms the state-of-the-art baselines. The SA-COVID dataset is publicly released at https://github.com/YishuLiu/SA-COVID.

Implementation of the Surgical Apgar Score in Laboratory Animal Science: A Showcase Pilot Study in a Porcine Model and a Review of the Literature

INTRODUCTION

In an attempt to further improve surgical outcomes, a variety of outcome prediction and risk-assessment tools have been developed for the clinical setting. Risk scores such as the surgical Apgar score (SAS) hold promise to facilitate the objective assessment of perioperative risk related to comorbidities of the patients or the individual characteristics of the surgical procedure itself. Despite the large number of scoring models in clinical surgery, only very few of these models have ever been utilized in the setting of laboratory animal science. The SAS has been validated in various clinical surgical procedures and shown to be strongly associated with postoperative morbidity. In the present study, we aimed to review the clinical evidence supporting the use of the SAS system and performed a showcase pilot trial in a large animal model as the first implementation of a porcine-adapted SAS (pSAS) in an in vivo laboratory animal science setting.

METHODS

A literature review was performed in the PubMed and Embase databases. Study characteristics and results using the SAS were reported. For the in vivo study, 21 female German landrace pigs have been used either to study bleeding analogy (n = 9) or to apply pSAS after abdominal surgery in a kidney transplant model (n = 12). The SAS was calculated using 3 criteria: (1) estimated blood loss during surgery; (2) lowest mean arterial blood pressure; and (3) lowest heart rate.

RESULTS

The SAS has been verified to be an effective tool in numerous clinical studies of abdominal surgery, regardless of specialization confirming independence on the type of surgical field or the choice of surgery. Thresholds for blood loss assessment were species specifically adjusted to >700 mL = score 0; 700-400 mL = score 1; 400-55 mL score 2; and <55 mL = score 3 resulting in a species-specific pSAS for a more precise classification.

CONCLUSION

Our literature review demonstrates the feasibility and excellent performance of the SAS in various clinical settings. Within this pilot study, we could demonstrate the usefulness of the modified SAS (pSAS) in a porcine kidney transplantation model. The SAS has a potential to facilitate early veterinary intervention and drive the perioperative care in large animal models exemplified in a case study using pigs. Further larger studies are warranted to validate our findings.

A cell phone app for facial acne severity assessment

Acne vulgaris, the most common skin disease, can cause substantial economic and psychological impacts to the people it affects, and its accurate grading plays a crucial role in the treatment of patients. In this paper, we firstly proposed an acne grading criterion that considers lesion classifications and a metric for producing accurate severity ratings. Due to similar appearance of acne lesions with comparable severities and difficult-to-count lesions, severity assessment is a challenging task. We cropped facial skin images of several lesion patches and then addressed the acne lesion with a lightweight acne regular network (Acne-RegNet). Acne-RegNet was built by using a median filter and histogram equalization to improve image quality, a channel attention mechanism to boost the representational power of network, a region-based focal loss to handle classification imbalances and a model pruning and feature-based knowledge distillation to reduce model size. After the application of Acne-RegNet, the severity score is calculated, and the acne grading is further optimized by the metadata of the patients. The entire acne assessment procedure was deployed to a mobile device, and a phone app was designed. Compared with state-of-the-art lightweight models, the proposed Acne-RegNet significantly improves the accuracy of lesion classifications. The acne app demonstrated promising results in severity assessments (accuracy: 94.56%) and showed a dermatologist-level diagnosis on the internal clinical dataset.The proposed acne app could be a useful adjunct to assess acne severity in clinical practice and it enables anyone with a smartphone to immediately assess acne, anywhere and anytime.

Welfare Assessment on Healthy and Tumor-Bearing Mice after Repeated Ultrasound Imaging

INTRODUCTION

Ultrasound (US) imaging enables tissue visualization in high spatial resolution with short examination times. Thus, it is often applied in preclinical research. Diagnostic US, including contrast-enhanced US (CEUS), is considered to be well-tolerated by laboratory animals although no systematic study has been performed to confirm this claim. Therefore, the aim of this study was to screen for possible effects of US and CEUS examinations on welfare of healthy mice. Additionally, the potential influence of CEUS and molecular CEUS on well-being and therapy response to regorafenib was investigated in breast cancer-bearing mice.

MATERIAL AND METHODS

Forty healthy Balb/c mice were randomly assigned for examination with US or CEUS (3×/week) for 4 weeks. Untreated healthy mice and mice receiving only isoflurane anesthesia served as controls (n = 10/group). Ninety-four 4T1 tumor-bearing Balb/c mice were allocated randomly to the following groups: no imaging, isoflurane anesthesia, CEUS, and molecular CEUS. They either received 10 mg/kg regorafenib or vehicle solution daily by oral gavage. Animals were examined three times within 2 weeks. CEUS measurements were performed using phospholipid microbubbles, and phospholipid microbubbles targeting the vascular endothelial growth factor receptor-2 were applied for molecular CEUS. Welfare evaluation was performed by daily observational score sheets, measuring the heart rate, Rotarod performance, and fecal corticosterone metabolites twice a week. On the last day, pathological changes in serum corticosterone concentrations, hemograms, and organ weights were obtained. Moreover, a potential influence of isoflurane anesthesia, CEUS, and molecular CEUS on regorafenib response in tumor-bearing mice was examined. Analysis of variance and Dunnett's post hoc test were performed as statistical analyses.

RESULTS

Severity parameters were not altered after repeated US and CEUS examinations of healthy mice, but spleen sizes were significantly lower after isoflurane anesthesia. In tumor-bearing mice, no effect on animal welfare after repeated CEUS and molecular CEUS could be observed. However, leukocyte counts and spleen weights of tumor-bearing mice were significantly lower in animals examined with CEUS and molecular CEUS compared to the control groups. This effect was not visible in regorafenib-treated animals.

CONCLUSIONS

Repeated US and (molecular) CEUS have no detectable impact on animal welfare in healthy and tumor-bearing mice. However, CEUS and molecular CEUS in combination with isoflurane anesthesia might attenuate immunological processes in tumor-bearing animals and may consequently affect responses to antitumor therapy.

Does Sex Matter in Liver Surgery? Comparison of Severity Assessments between Female and Male Rats after Partial Hepatectomy: A Pilot Study

INTRODUCTION

Current animal-based biomedical research, including studies on liver function and disease, is conducted almost exclusively on male animals to mitigate confounding effects of the estrous cycle. However, liver diseases afflict both men and women, so translational research findings should also be applicable to female patients. This pilot study investigated sex differences in objective and subjective severity assessment parameters in rats following 50% partial hepatectomy.

MATERIALS AND METHODS

This study was performed using Wistar Han rats, in which measurements of body weight, spontaneous motor activity in the open field (OF) (movement distance, movement velocity, rearing frequency), and fecal corticosterone metabolites were conducted at baseline and at multiple times after partial hepatectomy. Subjective postsurgical severity assessments were conducted using modified score sheets. Blood parameters such as leukocyte count and serum aspartate aminotransferase, as well as estrogens and testosterone were measured from samples obtained during partial hepatectomy and at sacrifice. In addition, the amount of resected liver tissue was measured at partial hepatectomy, and the proliferated liver was weighed at sacrifice.

RESULTS

Fecal corticosterone metabolite concentrations differed significantly between males and females at baseline and following hepatectomy. Also, leukocyte counts and estrogen concentrations were significantly different between sexes before partial hepatectomy. Alternatively, there were no sex differences in severity assessments, body weight changes, and behavior in the OF at any measurement time point. Liver weight was significantly different in males and females at the time point of partial hepatectomy and sacrifice.

CONCLUSION

The results of this pilot study suggest that males and females respond similarly following partial hepatectomy. Examination of both sexes is very important for translation to humans, where both men and women suffer from liver disease. Furthermore, the use of both sexes in animal-based research would improve the utilization of the animal breeding in terms of the 3 Rs. However, due to some limitations, larger scale investigations including a broader spectrum of pathophysiolological, behavioral, and pharmacokinetic measures are planned.

Clinical, Experimental, and Computational Validation of a New Doppler-Based Index for Coarctation Severity Assessment

BACKGROUND

Long-term morbidity including hypertension often persists in coarctation patients despite current guidelines. Coarctation severity can be invasively assessed via peak-to-peak catheter pressure gradient (PPCG), which is estimated noninvasively via simplified Bernoulli equation and conventionally reported as peak instantaneous Doppler gradient (PIDG). However, underlying simplifications of the equation limit diagnostic accuracy. We studied the diagnostic performance of a new Doppler-based diastolic index called the continuous flow pressure gradient (CFPG) versus conventional indices in assessing coarctation severity.

METHODS

In a rabbit model mimicking human aortic coarctation, temporal blood pressure waveforms revealed the diastolic instantaneous pressure gradients and spectral Doppler features impacted by coarctation severity. We therefore hypothesized that CFPG provides superior correlation with coarctation gradients measured invasively. PIDG and CFPG were quantified using color flow echocardiography in humans and rabbits with discrete coarctations. Results were compared with PPCG in rabbits (n = 34) and arm-leg systolic gradients (n = 25) in humans via 1-way analysis of variance, Pearson's correlation, linear regression, and Bland-Altman analysis.

RESULTS

A threshold of CFPG ≥ 4.6 mm Hg was identified via the Youden index as representative of PPCG ≥ 20 mm Hg (the current guideline value for coarctation intervention) in rabbits, while a CFPG ≥1.0 mm Hg represented an arm-leg systolic gradient ≥20 mm Hg in humans. Accuracy measures revealed superior correlation of CFPG (R2 > 0.80) and mild receiver operating characteristic improvement (area under the receiver operating characteristic curve, 0.94-0.95) compared with PIDG (R2 < 0.63; area under the receiver operating characteristic curve, 0.89-0.95). Inter-/intraobserver variability tested by intraclass correlation coefficient revealed measurement reliability with differences ≤8.2% and 10.7%, respectively. Computational simulations of anesthetized versus conscious hemodynamics showed parameters were minimally impacted by isoflurane inherent in the data used to derive CFPG. These results confirm the potential diagnostic accuracy of CFPG in echocardiography-based coarctation severity assessment. We are optimistic that CFPG will be useful for translation of results from preclinical studies that revisit current guidelines to limit morbidity in humans with aortic coarctation.

Behavioral phenotyping of young Scn1a haploinsufficient mice

Dravet syndrome is a rare, severe, infancy-onset epileptic encephalopathy associated with a high premature mortality. In most patients, Dravet syndrome is caused by a heterozygous loss-of-function mutation in the SCN1A gene encoding the alpha 1 subunit of the sodium channel. Of the variety of SCN1A variants identified in patients with Dravet syndrome, SCN1A missense mutations occur in one-third of cases. The novel Scn1a-A1783V mouse model of Dravet syndrome carries the human Ala1783Val missense variant. Recently, the behavioral phenotype of Scn1a-A1783V haploinsufficient adult mice has been characterized, which may provide a valuable basis for assessment of novel therapeutic approaches. However, there is still limited information on the developmental course of behavioral alterations in the Scn1a-A1783V mouse model, which is of particular relevance for conclusions about face validity and severity classification of the model. Based on reference data from young wildtype mice, we analyzed selected behavioral parameters and fecal corticosterone metabolites in the Scn1a-A1783V mouse model during post-weaning development. Differences in the preference for a sweet saccharin solution between Dravet mice and wildtype mice were observed once mice reached sexual maturity. Nest building behavior was already influenced by the Scn1a genotype during prepubescence. Sexually mature Dravet mice showed a significantly reduced burrowing performance as compared to their wildtype littermates. In the open-field test, pronounced hyperactivity and increased thigmotactic behavior were evident in prepubescent and sexually mature Dravet mice. Analysis of Irwin scores revealed several genotype-dependent changes in handling-associated parameters during the course of adolescence. The information obtained provides insight into the age-dependence of behavioral patterns in the novel Scn1a-A1783V mouse model of Dravet syndrome. In addition, the dataset confirms the suitability of the applied behavioral composite measure scheme for evidence-based assessment of cumulative severity in genetic mouse lines.

Severity Assessment in Rats Undergoing Subarachnoid Hemorrhage Induction by Endovascular Perforation or Corresponding Sham Surgery

INTRODUCTION

Animal models for preclinical research of subarachnoid hemorrhage (SAH) are widely used as much of the pathophysiology remains unknown. However, the burden of these models inflicted on the animals is not well characterized. The European directive requires severity assessment-based allocation to categories. Up to now, the classification into predefined categories is rather subjective and often without underlying scientific knowledge. We therefore aimed at assessing the burden of rats after SAH or the corresponding sham surgery to provide a scientific assessment.

METHODS

We performed a multimodal approach, using different behavior tests, clinical and neurological scoring, and biochemical markers using the common model for SAH of intracranial endovascular filament perforation in male Wistar rats. Up to 7 days after surgery, animals with SAH were compared to sham surgery and to a group receiving only anesthesia and analgesia.

RESULTS

Sham surgery (n = 15) and SAH (n = 16) animals showed an increase in the clinical score the first days after surgery, indicating clinical deterioration, while animals receiving only anesthesia without surgery (n = 5) remained unaffected. Body weight loss occurred in all groups but was more pronounced and statistically significant only after surgery. The analysis of burrowing, open field (total distance, erections), balance beam, and neuroscore showed primarily an effect of the surgery itself in sham surgery and SAH animals. Only concerning balance beam and neuroscore, a difference was visible between sham surgery and SAH. The outcome of the analysis of systemic and local inflammatory parameters and of corticosterone in blood and its metabolites in feces was only robust in animals suffering from larger bleedings. Application of principal component analysis resulted in a clear separation of sham surgery and SAH animals from their respective baseline as well as from the anesthesia-only group at days 1 and 3, with the difference between sham surgery and SAH being not significant.

DISCUSSION/CONCLUSION

To our knowledge, we are the first to publish detailed clinical score sheet data combined with advanced behavioral assessment in the endovascular perforation model for SAH in rats. The tests chosen here clearly depict an impairment of the animals within the first days after surgery and are consequently well suited for assessment of the animals' suffering in the model. A definitive classification into one of the severity categories named by the EU directive is yet pending and has to be performed in the future by including the assessment data from different neurological and nonneurological disease models.

COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment

There is an urgent need for automated methods to assist accurate and effective assessment of COVID-19. Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis methods. In this paper, we present an end-to-end multitask learning (MTL) framework (COVID-MTL) that is capable of automated and simultaneous detection (against both radiology and NAT) and severity assessment of COVID-19. COVID-MTL learns different COVID-19 tasks in parallel through our novel random-weighted loss function, which assigns learning weights under Dirichlet distribution to prevent task dominance; our new 3D real-time augmentation algorithm (Shift3D) introduces space variances for 3D CNN components by shifting low-level feature representations of volumetric inputs in three dimensions; thereby, the MTL framework is able to accelerate convergence and improve joint learning performance compared to single-task models. By only using chest CT scans, COVID-MTL was trained on 930 CT scans and tested on separate 399 cases. COVID-MTL achieved AUCs of 0.939 and 0.846, and accuracies of 90.23% and 79.20% for detection of COVID-19 against radiology and NAT, respectively, which outperformed the state-of-the-art models. Meanwhile, COVID-MTL yielded AUC of 0.800 ± 0.020 and 0.813 ± 0.021 (with transfer learning) for classifying control/suspected, mild/regular, and severe/critically-ill cases. To decipher the recognition mechanism, we also identified high-throughput lung features that were significantly related (P < 0.001) to the positivity and severity of COVID-19.

A deep-learning-based framework for severity assessment of COVID-19 with CT images

Millions of positive COVID-19 patients are suffering from the pandemic around the world, a critical step in the management and treatment is severity assessment, which is quite challenging with the limited medical resources. Currently, several artificial intelligence systems have been developed for the severity assessment. However, imprecise severity assessment and insufficient data are still obstacles. To address these issues, we proposed a novel deep-learning-based framework for the fine-grained severity assessment using 3D CT scans, by jointly performing lung segmentation and lesion segmentation. The main innovations in the proposed framework include: 1) decomposing 3D CT scan into multi-view slices for reducing the complexity of 3D model, 2) integrating prior knowledge (dual-Siamese channels and clinical metadata) into our model for improving the model performance. We evaluated the proposed method on 1301 CT scans of 449 COVID-19 cases collected by us, our method achieved an accuracy of 86.7% for four-way classification, with the sensitivities of 92%, 78%, 95%, 89% for four stages. Moreover, ablation study demonstrated the effectiveness of the major components in our model. This indicates that our method may contribute a potential solution to severity assessment of COVID-19 patients using CT images and clinical metadata.

Improving Diagnostic Workup Following Traumatic Spinal Cord Injury: Advances in Biomarkers

PURPOSE OF REVIEW

Traumatic spinal cord injury (SCI) is a life-changing event with drastic implications for patients due to sensorimotor impairment and autonomous dysfunction. Current clinical evaluations focus on the assessment of injury level and severity using standardized neurological examinations. However, they fail to predict individual trajectories of recovery, which highlights the need for the development of advanced diagnostics. This narrative review identifies recent advances in the search of clinically relevant biomarkers in the field of SCI.

RECENT FINDINGS

Advanced neuroimaging and molecular biomarkers sensitive to the disease processes initiated by the SCI have been identified. These biomarkers range from advanced neuroimaging techniques, neurophysiological readouts, and molecular biomarkers identifying the concentrations of several proteins in blood and CSF samples. Some of these biomarkers improve current prediction models based on clinical readouts. Validation with larger patient cohorts is warranted. Several biomarkers have been identified-ranging from imaging to molecular markers-that could serve as advanced diagnostic and hence supplement current clinical assessments.

SAA and CRP are potential indicators in distinction and severity assessment for children with influenza

PURPOSE

The clinical values of C-reactive protein (CRP) and serum amyloid A (SAA) to distinguish non-severe from severe influenza in children are rarely reported.

METHODS

Baseline characteristics and laboratory results were collected and analyzed. Receiver operating characteristic (ROC) curve analysis was used for combined detection of indicators for children with influenza, and scatter-dot plots were used to compare the differences between non-severe and severe influenza.

RESULTS

Children with influenza B had more bronchitis and pneumonia (P < 0.05) and children with influenza A had more other serious symptoms (P = 0.015). Lymphocyte count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), CRP, and SAA performed differently among children with influenza A and B. Joint detection of SAA and other indicators could better separate healthy children from children with influenza than single indicator detection. The CRP and SAA levels of children with severe influenza B infection and SAA levels of children with severe influenza A infection were significantly elevated compared with children with non-severe influenza (P < 0.05).

CONCLUSIONS

SAA and CRP could be potential indicators in distinction and severity assessment for children with influenza; however, age should be taken into account when using them in children with influenza B.

Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images

Understanding chest CT imaging of the coronavirus disease 2019 (COVID-19) will help detect infections early and assess the disease progression. Especially, automated severity assessment of COVID-19 in CT images plays an essential role in identifying cases that are in great need of intensive clinical care. However, it is often challenging to accurately assess the severity of this disease in CT images, due to variable infection regions in the lungs, similar imaging biomarkers, and large inter-case variations. To this end, we propose a synergistic learning framework for automated severity assessment of COVID-19 in 3D CT images, by jointly performing lung lobe segmentation and multi-instance classification. Considering that only a few infection regions in a CT image are related to the severity assessment, we first represent each input image by a bag that contains a set of 2D image patches (with each cropped from a specific slice). A multi-task multi-instance deep network (called M 2 UNet) is then developed to assess the severity of COVID-19 patients and also segment the lung lobe simultaneously. Our M 2 UNet consists of a patch-level encoder, a segmentation sub-network for lung lobe segmentation, and a classification sub-network for severity assessment (with a unique hierarchical multi-instance learning strategy). Here, the context information provided by segmentation can be implicitly employed to improve the performance of severity assessment. Extensive experiments were performed on a real COVID-19 CT image dataset consisting of 666 chest CT images, with results suggesting the effectiveness of our proposed method compared to several state-of-the-art methods.

A novel, automated, quantification of abnormal lung parenchyma in patients with COVID-19 infection: Initial description of feasibility and association with clinical outcome

OBJECTIVE

Ground-glass opacities are the most frequent radiologic features of COVID-19 patients. We aimed to determine the feasibility of automated lung volume measurements, including ground-glass volumes, on the CT of suspected COVID-19 patients. Our goal was to create an automated and quantitative measure of ground-glass opacities from lung CT images that could be used clinically for diagnosis, triage and research.

DESIGN

Single centre, retrospective, observational study.

MEASUREMENTS

Demographic data, respiratory support treatment (synthetised in the maximal respiratory severity score) and CT-images were collected. Volume of abnormal lung parenchyma was measured with conventional semi-automatic software and with a novel automated algorithm based on voxels X-Ray attenuation. We looked for the relationship between the automated and semi-automated evaluations. The association between the ground-glass opacities volume and the maximal respiratory severity score was assessed.

MAIN RESULTS

Thirty-seven patients were included in the main outcome analysis. The mean duration of automated and semi-automated volume measurement process were 15 (2) and 93 (41) min, respectively (p=8.05*10^-8). The intraclass correlation coefficient between the semi-automated and automated measurement of ground-glass opacities and restricted normally aerated lung were both superior to 0.99. The association between the automated measured lung volume and the maximal clinical severity score was statistically significant for the restricted normally aerated (p=0.0097, effect-size: -385mL) volumes and for the ratio of ground-glass opacities/restricted normally aerated volumes (p=0.027, effect-size: 3.3).

CONCLUSION

The feasibility and preliminary validity of automated impaired lung volume measurements in a high-density COVID-19 cluster was confirmed by our results.

BPBSAM: Body part-specific burn severity assessment model

BACKGROUND AND OBJECTIVE

Burns are a serious health problem leading to several thousand deaths annually, and despite the growth of science and technology, automated burns diagnosis still remains a major challenge. Researchers have been exploring visual images-based automated approaches for burn diagnosis. Noting that the impact of a burn on a particular body part can be related to the skin thickness factor, we propose a deep convolutional neural network based body part-specific burns severity assessment model (BPBSAM).

METHOD

Considering skin anatomy, BPBSAM estimates burn severity using body part-specific support vector machines trained with CNN features extracted from burnt body part images. Thus BPBSAM first identifies the body part of the burn images using a convolutional neural network in training of which the challenge of limited availability of burnt body part images is successfully addressed by using available larger-size datasets of non-burn images of different body parts considered (face, hand, back, and inner forearm). We prepared a rich labelled burn images datasets: BI & UBI and trained several deep learning models with existing models as pipeline for body part classification and feature extraction for severity estimation.

RESULTS

The proposed novel BPBSAM method classified the severity of burn from color images of burn injury with an overall average F1 score of 77.8% and accuracy of 84.85% for the test BI dataset and 87.2% and 91.53% for the UBI dataset, respectively. For burn images body part classification, the average accuracy of around 93% is achieved, and for burn severity assessment, the proposed BPBSAM outperformed the generic method in terms of overall average accuracy by 10.61%, 4.55%, and 3.03% with pipelines ResNet50, VGG16, and VGG19, respectively.

CONCLUSIONS

The main contributions of this work along with burn images labelled datasets creation is that the proposed customized body part-specific burn severity assessment model can significantly improve the performance in spite of having small burn images dataset. This highly innovative customized body part-specific approach could also be used to deal with the burn region segmentation problem. Moreover, fine tuning on pre-trained non-burn body part images network has proven to be robust and reliable.

Update on Atopic Dermatitis: Diagnosis, Severity Assessment, and Treatment Selection

Atopic dermatitis (AD) is one of the most common inflammatory skin diseases affecting children and adults. The intense pruritus and rash can be debilitating, significantly impairing quality of life. Until recently, treatment was largely nonspecific and, in severe disease, sometimes ineffective and/or fraught with many side effects. Now, multiple agents targeting specific disease pathways are available or in development. Two new therapies, crisaborole and dupilumab, have become available since 2016, and dupilumab has dramatically improved outcomes for adults with severe AD. This article provides an overview of AD, including strategies for differential diagnosis and assessment of disease severity to guide treatment selection. Key clinical trials for crisaborole and dupilumab are reviewed, and other targeted treatments now in development are summarized. Two cases, representing childhood-onset and adult-onset AD, are discussed to provide clinical context for diagnosis, severity assessment, and treatment selection and outcomes.

Performance of severity parameters to detect chemotherapy-induced pain and distress in mice

According to European Union directive 2010/63/EU a severity classification of experimental procedures performed on laboratory animals is mandatory. This includes a prospective evaluation of all interventions performed within the experiment, as well as an assessment of the actual burden of each animal during the experiment. In this regard, the evaluation and scoring of defined criteria regarding the health state of animals could help to early identify deteriorations in animal health and facilitate the application of humane endpoints. This article discusses the applicability of an adapted score sheet in BALB/cAnNRj mice receiving either cisplatin, doxorubicin or busulfan, three chemotherapeutic agents with different toxicological profiles and longitudinal non-invasive molecular imaging. The health state was investigated by score sheets documenting general state, body weight, spontaneous behaviour and treatment specific parameters (e.g. anaemia, neurotoxicity, persistent diarrhoea). Although blood and serum analyses clearly indicated various organ damage, most scoring parameters except for body weight did not report on the deceasing animal health state. Thus, there is need for more sensitive observational parameters to judge the animal's health state and welfare.

[French adaptation of a new score for global assessment of psoriasis severity: The Simplified Psoriasis Index (SPI)]

OBJECTIVE

Although several scores exist to assess psoriasis severity, most have marked limitations that rule out their use in routine clinical practice. A new score, the Simplified Psoriasis Index (SPI), has recently been developed and validated in adults in Britain for such use. It has separate components for current severity (SPI-s), psychosocial impact (SPI-p) and past history and interventions (SPI-p), and it is suitable for either professional assessment or patient self-assessment. The aim of this work was to produce a validated translation of SPI into French (as spoken in France).

METHODS

The index was translated and validated using a strict methodology comprising respectively five and eight phases for the professional (proSPI) and self-administered instruments (saSPI). Translation of the saSPI instrument also involved a cognitive debriefing with five psoriasis patients.

RESULTS

Linguistic discrepancies and subtle differences of meaning arising during the process were closely examined. The developer of the instrument ensured conceptual accuracy. A panel of health experts guaranteed that medical terms were correctly translated. Five patients with plaque psoriasis (two female and three male of median age 45 years [range: 31-78]) tested the SPI-p version during cognitive interviews and found the questionnaire clear and easy to understand.

CONCLUSION

Validated French translations of both SPI instruments are now available for use in routine clinical practice. Further investigations are currently underway to validate the psychometric properties of the instrument.

Benefits of non-invasive methods compared to telemetry for distress analysis in a murine model of pancreatic cancer

Prospective severity assessment is legally required in many countries to ensure high-quality research along with high welfare standards for laboratory animals. Mice and rats, the most common laboratory species, are prey animals that usually suppress signs of pain and suffering. Therefore, highly sensitive readout parameters are necessary to adequately quantify distress. The present study compared the performance of different non-invasive methods in determining animal distress, such as measuring body weight, distress score, faecal corticosterone metabolites, burrowing, and nesting behaviour, with continuous monitoring of heart rate, body temperature and activity by telemetry. The distress caused by two surgical interventions was compared and the burden caused by tumour growth was described. Transmitter implantation caused higher distress than laparotomy plus carcinoma cell injection into the pancreas. Surprisingly, no significant increase in distress was observed during tumour growth. The receiver operating characteristic curve analysis revealed that some non-invasive distress-parameters, i.e., distress-score and burrowing activity, exhibited slightly better performance to quantify distress than the most suitable parameters measured by telemetry. Due to the high burden caused by the implantation of the telemetric device, the use of non-invasive methods to assess distress in laboratory animals after surgical interventions should be favoured in future studies.

Severity Assessment in CDKL5 Deficiency Disorder

BACKGROUND

Pathologic mutations in cyclin-dependent kinase-like 5 cause CDKL5 deficiency disorder, a genetic syndrome associated with severe epilepsy and cognitive, motor, visual, and autonomic disturbances. This disorder is a relatively common genetic cause of early-life epilepsy. A specific severity assessment is lacking, required to monitor the clinical course and needed to define the natural history and for clinical trial readiness.

METHODS

A severity assessment was developed based on clinical and research experience from the International Foundation for CDKL5 Research Centers of Excellence consortium and the National Institutes of Health Rett and Rett-Related Disorders Natural History Study consortium. An initial draft severity assessment was presented and reviewed at the annual CDKL5 Forum meeting (Boston, 2017). Subsequently it was iterated through four cycles of a modified Delphi process by a group of clinicians, researchers, industry, patient advisory groups, and parents familiar with this disorder until consensus was achieved. The revised version of the severity assessment was presented for review, comment, and piloting to families at the International Foundation for CDKL5 Research-sponsored family meeting (Colorado, 2018). Final revisions were based on this additional input.

RESULTS

The final severity assessment comprised 51 items that comprehensively describe domains of epilepsy; motor; cognition, behavior, vision, and speech; and autonomic functions. Parental ratings of therapy effectiveness and child and family functioning are also included.

CONCLUSIONS

A severity assessment was rapidly developed with input from multiple stakeholders. Refinement through ongoing validation is required for future clinical trials. The consensus methods employed for the development of severity assessment may be applicable to similar rare disorders.

Pectus Carinatum: a non-invasive and objective measurement of severity

To date, standard methods for assessing the severity of chest wall deformities are mostly linked to X-ray and CT scans. However, the use of radiations limits their use when there is a need to monitor the development of the pathology over time. This is particularly important when dealing with patients suffering from Pectus Carinatum, whose treatment mainly requires the use of corrective braces and a systematic supervision. In recent years, the assessment of severity of chest deformities by means of radiation-free devices became increasingly popular but not yet adopted as standard clinical practice. The present study aims to define an objective measure by defining a severity index (named External Pectus Carinatum Index) used to monitor the course of the disease during treatment. Computed on the optical acquisition of the patients' chest by means of an appositely devised, fast and easy-to-use, body scanner, the proposed index has been validated on a sample composed of a control group and a group of Pectus Carinatum patients. The index proved to be reliable and accurate in the characterization of the pathology, enabling the definition of a threshold that allows to distinguish the cases of patients with PC from those of healthy subjects. Graphical abstract.

Assessing severity of anaphylaxis: a data-driven comparison of 23 instruments

Backgroud

The severity of an allergic reaction can range from mild local symptoms to anaphylactic shock. To score this, a number of instruments have been developed, although heterogeneous in design and purpose. Severity scoring algorithms are therefore difficult to compare, but are frequently used beyond their initial purpose. Our objective was to compare the most used severity scoring instruments by a data-driven approach on both milder reactions and anaphylaxis.

Methods

All positive challenges to foods or drugs (n = 2828) including anaphylaxis (n = 616) at Odense University Hospital, Denmark from 1998 to 2016 were included and severity was scored according to Sampson5. Based on recommendations from an expert group, the symptoms and values from Sampson5 were for all reactions and anaphylaxis only translated and compared by kappa statistics with 22 instruments, ranging from 3 to 6 steps.

Results

For milder reactions, there was a significant correlation between the number of steps in an instrument and the number of challenges that could be translated, whereas all instruments were good to identify food anaphylaxis. Some instruments scored reactions more severely than Sampson5, other scored them milder and some scored food and drug challenges differently. Instruments for hymenoptera reactions were difficult to apply on food and drug reactions, and thus distributed severity differently. Algorithms hampered the translation between instruments, and 7 instruments were poor concerning drug anaphylaxis, including the only instrument developed specifically for drug reactions.

Conclusion

The distributions of severity differed between the 23 instruments in both food and drug allergy, and thus rendering translation especially between scoring systems with 3 and 5 grades difficult. Fine-graded and simple instruments are preferred for comparison especially among milder reactions, and instruments applied to non-intended situations may not reflect a true severity picture.

Hospitalization for community-acquired febrile urinary tract infection: validation and impact assessment of a clinical prediction rule

Background

There is a lack of severity assessment tools to identify adults presenting with febrile urinary tract infection (FUTI) at risk for complicated outcome and guide admission policy. We aimed to validate the Prediction Rule for Admission policy in Complicated urinary Tract InfeCtion LEiden (PRACTICE), a modified form of the pneumonia severity index, and to subsequentially assess its use in clinical practice.

Methods

A prospective observational multicenter study for model validation (2004–2009), followed by a multicenter controlled clinical trial with stepped wedge cluster-randomization for impact assessment (2010–2014), with a follow up of 3 months. Paricipants were 1157 consecutive patients with a presumptive diagnosis of acute febrile UTI (787 in validation cohort and 370 in the randomized trial), enrolled at emergency departments of 7 hospitals and 35 primary care centers in the Netherlands.

The clinical prediction rule contained 12 predictors of complicated course. In the randomized trial the PRACTICE included guidance on hospitalization for high risk (>100 points) and home discharge for low risk patients (<75 points), in the control period the standard policy regarding hospital admission was applied. Main outcomes were effectiveness of the clinical prediction rule, as measured by primary hospital admission rate, and its safety, as measured by the rate of low-risk patients who needed to be hospitalized for FUTI after initial home-based treatment, and 30-day mortality.

Results

A total of 370 patients were included in the randomized trial, 237 in the control period and 133 in the intervention period. Use of PRACTICE significantly reduced the primary hospitalization rate (from 219/237, 92%, in the control group to 96/133, 72%, in the intervention group, p < 0.01). The secondary hospital admission rate after initial outpatient treatment was 6% in control patients and 27% in intervention patients (1/17 and 10/37; p < 0.001).

Conclusions

Although the proposed PRACTICE prediction rule is associated with a lower number of hospital admissions of patients presenting to the ED with presumptive febrile urinary tract infection, futher improvement is necessary to reduce the occurrence of secondary hospital admissions.

Trial registration

NTR4480 http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4480, registered retrospectively 25 mrt 2014 (during enrollment of subjects).

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-017-2509-3) contains supplementary material, which is available to authorized users.

Comparison of the Poisoning Severity Score and National Poison Data System schemes for the severity assessment of animal poisonings: a pilot study

CONTEXT

To date, there are no publicly available schemes designed and evaluated specifically for severity assessment of animal poisonings. This poses challenges for the evaluation and comparison of animal poisoning exposure data.

OBJECTIVE

Our objective for this pilot study was to evaluate agreement between raters using the Poisoning Severity Score (PSS) and National Poison Data System (NPDS) medical outcome scheme for severity assessment of canine exposures reported to a multistate poison center (PC) and to identify issues regarding their use for severity assessment of animal poisonings. Agreement between both schemes was also assessed.

METHODS

The first 196 canine exposures reported to a multistate PC between 1 January and 31 August 2016 were selected and initial inquiry data from exposures was scored by four independent raters. Interrater agreement and agreement between the severity systems was calculated using weighted kappa (Κ) (Light's kappa). Reported clinical effects were also described.

RESULTS

Interrater agreement for both the PSS (Κ 0.31; 95% CI 0.19, 0.43) and NPDS schemes (Κ 0.34; 95% CI 0.22, 0.44) was low. Agreement between the schemes was slight (Κ 0.05; 95% CI -0.08, 0.16) for pooled results from all four raters. For the PSS, 71.7% (n = 281) of ratings were minor, 23.0% (n = 90) moderate, and 5.4% (n = 21) severe. For the NPDS, 69.6% (n = 273) of ratings were minor, 27.0% (n = 106) moderate, and 3.3% (n = 13) severe. The top three reported clinical effects included vomiting (n = 86, 29.9%) drowsiness/lethargy (n = 38, 13.2%), and diarrhea (n = 24, 8.3%).

DISCUSSION AND CONCLUSIONS

This study shows considerable variability between raters using either the PSS or NPDS schemes for canine exposures severity assessment. The subjective nature of the schemes, the influence of intra- and interrater variation, and predominance of minor cases on the study findings should be taken into account when interpreting this data. Further evaluation of these schemes is warranted and could help inform their future use for animal poisoning severity assessment.

Fecal Calprotectin Level Reflects the Severity of Clostridium difficile Infection

Clostridium difficile is a significant nosocomial and community-acquired pathogen, and is the leading cause of antibiotic-induced diarrhea associated with high morbidity and mortality. Given that the treatment outcome depends on the severity of C. difficile infection (CDI), we aimed to establish an efficient method of assessing severity, and focused on the stool biomarker fecal calprotectin (FC). FC directly reflects the intestinal inflammation status of a patient, and can aid in interpreting the current guidelines, which requires the integration of indirect laboratory parameters. The distinction of 80 patients with CDI versus 71 healthy controls and 30 severe infection cases versus 50 mild cases was possible using FC as a marker. The area under the receiver operating characteristic curves were 0.821 and 0.746 with a sensitivity of 75% and 70% and specificity of 79% and 80%, for severe versus mild cases, respectively. We suggest FC as a predictive marker for assessing CDI severity, which is expected to improve the clinical management of CDI.

Comparison of the frequency of bacterial and viral infections among children with community-acquired pneumonia hospitalized across distinct severity categories: a prospective cross-sectional study

Background

The comparison of the frequencies of bacterial and viral infections among children with community-acquired pneumonia (CAP) admitted in distinct severity categories, in an original study, is lacking in literature to-date. We aimed to achieve this goal.

Methods

Children aged 2-59-months-old hospitalized with CAP were included in this prospective study in Salvador, Brazil. Clinical data and biological samples were collected to investigate 11 viruses and 8 bacteria. Severity was assessed by using the World Health Organization criteria.

Results

One hundred eighty-one patients were classified as “non-severe” (n = 53; 29.3 %), “severe” (n = 111; 61.3 %), or “very severe” (n = 17; 9.4 %) CAP. Overall, aetiology was detected among 156 (86.2 %) cases; viral (n = 84; 46.4 %), bacterial (n = 26; 14.4 %) and viral-bacterial (n = 46; 25.4 %) infections were identified. Viral infection frequency was similar in severe/very severe and non-severe cases (46.1 % vs. 47.2 %; p = 0.9). Pneumococcal infection increased across “non-severe” (13.2 %), “severe” (23.4 %), and “very severe” (35.3 %) cases (qui-squared test for trend p = 0.04). Among patients with detected aetiology, after excluding cases with co-infection, the frequency of sole bacterial infection was different (p = 0.04) among the categories; non-severe (12.5 %), severe (29.3 %) or very severe (55.6 %). Among these patients, sole bacterial infection was independently associated with severity (OR = 4.4 [95 % CI:1.1–17.6]; p = 0.04) in a model controlled for age (OR = 0.7 [95 % CI:0.5–1.1]; p = 0.1).

Conclusions

A substantial proportion of cases in distinct severity subgroups had respiratory viral infections, which did not differ between severity categories. Bacterial infection, particularly pneumococcal infection, was more likely among severe/very severe cases.

Electronic supplementary material

The online version of this article (doi:10.1186/s12887-016-0645-3) contains supplementary material, which is available to authorized users.

Clinical evaluation of the Tokyo Guidelines 2013 for severity assessment of acute cholangitis

BACKGROUND

We evaluated the severity assessment criteria for acute cholangitis (AC) of the Tokyo Guidelines 2013 (TG13) and developed a scoring system for predicting the need for urgent/early biliary drainage.

METHODS

We retrospectively reviewed 66 AC cases prospectively managed based on the TG07 and divided into an urgent/early biliary drainage group (n = 30) and elective biliary drainage group (n = 36).

RESULTS

There were 26 mild, 27 moderate, and 13 severe cases based on the TG13. The TG13 assessment in 12 of the 17 cases requiring early biliary drainage based on the TG07 was moderate, but underestimated the other five cases as mild AC. When five predictors (blood urea nitrogen >20 mg/dL, SIRS presence, platelet count <120 000/μL, serum albumin level <3.0 g/dL, age ≥75 years old) were used to devise a scoring system, the receiver-operator characteristic curve of the scores showed good test performance for predicting the need for urgent/early biliary drainage. The area under the curve (AUC) was 0.95 and higher than the TG13 AUC (0.80).

CONCLUSIONS

The TG13 is practical, but some AC cases requiring urgent/early biliary drainage were underestimated as mild AC. The scoring system allows identification of high-risk AC patients and will improve the TG13.

Japanese guidelines for the management of acute pancreatitis: Japanese Guidelines 2015

BACKGROUND

Japanese (JPN) guidelines for the management of acute pancreatitis were published in 2006. The severity assessment criteria for acute pancreatitis were later revised by the Japanese Ministry of Health, Labour and Welfare (MHLW) in 2008, leading to their publication as the JPN Guidelines 2010. Following the 2012 revision of the Atlanta Classifications of Acute Pancreatitis, in which the classifications of regional complications of pancreatitis were revised, the development of a minimally invasive method for local complications of pancreatitis spread, and emerging evidence was gathered and revised into the JPN Guidelines.

METHODS

A comprehensive evaluation was carried out on the evidence for epidemiology, diagnosis, severity, treatment, post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis and clinical indicators, based on the concepts of the GRADE system (Grading of Recommendations Assessment, Development and Evaluation). With the graded recommendations, where the evidence was unclear, Meta-Analysis team for JPN Guidelines 2015 conducted an additional new meta-analysis, the results of which were included in the guidelines.

RESULTS

Thirty-nine questions were prepared in 17 subject areas, for which 43 recommendations were made. The 17 subject areas were: Diagnosis, Diagnostic imaging, Etiology, Severity assessment, Transfer indication, Fluid therapy, Nasogastric tube, Pain control, Antibiotics prophylaxis, Protease inhibitor, Nutritional support, Intensive care, management of Biliary Pancreatitis, management of Abdominal Compartment Syndrome, Interventions for the local complications, Post-ERCP pancreatitis and Clinical Indicator (Pancreatitis Bundles 2015). Meta-analysis was conducted in the following four subject areas based on randomized controlled trials: (1) prophylactic antibiotics use; (2) prophylactic pancreatic stent placement for the prevention of post-ERCP pancreatitis; (3) prophylactic non-steroidal anti-inflammatory drugs (NSAIDs) for the prevention of post-ERCP pancreatitis; and (4) peritoneal lavage. Using the results of the meta-analysis, recommendations were graded to create useful information. In addition, a mobile application was developed, which made it possible to diagnose, assess severity and check pancreatitis bundles.

CONCLUSIONS

The JPN Guidelines 2015 were prepared using the most up-to-date methods, and including the latest recommended medical treatments, and we are confident that this will make them easy for many clinicians to use, and will provide a useful tool in the decision-making process for the treatment of patients, and optimal medical support. The free mobile application and calculator for the JPN Guidelines 2015 is available via http://www.jshbps.jp/en/guideline/jpn-guideline2015.html.

Inertial sensing algorithms for long-term foot angle monitoring for assessment of idiopathic toe-walking

When children walk on their toes for no known reason, the condition is called Idiopathic Toe Walking (ITW). Assessing the true severity of ITW can be difficult because children can alter their gait while under observation in clinic. The ability to monitor the foot angle during daily life outside of clinic may improve the assessment of ITW. A foot-worn, battery-powered inertial sensing device has been designed to monitor patients' foot angle during daily activities. The monitor includes a 3-axis accelerometer, 2-axis gyroscope, and a low-power microcontroller. The device is necessarily small, with limited battery capacity and processing power. Therefore a high-accuracy but low-complexity inertial sensing algorithm is needed. This paper compares several low-complexity algorithms' aptitude for foot-angle measurement: accelerometer-only measurement, finite impulse response (FIR) and infinite impulse response (IIR) complementary filtering, and a new dynamic predict-correct style algorithm developed using fuzzy c-means clustering. A total of 11 subjects each walked 20 m with the inertial sensing device fixed to one foot; 10 m with normal gait and 10 m simulating toe walking. A cross-validation scheme was used to obtain a low-bias estimate of each algorithm's angle measurement accuracy. The new predict-correct algorithm achieved the lowest angle measurement error: <5° mean error during normal and toe walking. The IIR complementary filtering algorithm achieved almost-as good accuracy with less computational complexity. These two algorithms seem to have good aptitude for the foot-angle measurement problem, and would be good candidates for use in a long-term monitoring device for toe-walking assessment.