Diagnostic Tool Research Articles

Complement Activation in Nephrotic Glomerular Diseases.

The nephrotic syndrome holds significant clinical importance and is characterized by a substantial protein loss in the urine. Damage to the glomerular basement membrane or podocytes frequently underlies renal protein loss. There is an increasing belief in the involvement of the complement system, a part of the innate immune system, in these conditions. Understanding the interactions between the complement system and glomerular structures continually evolves, challenging the traditional view of the blood-urine barrier as a passive filter. Clinical studies suggest that a precise inhibition of the complement system at various points may soon become feasible. However, a thorough understanding of current knowledge is imperative for planning future therapies in nephrotic glomerular diseases such as membranous glomerulopathy, membranoproliferative glomerulonephritis, lupus nephritis, focal segmental glomerulosclerosis, and minimal change disease. This review provides an overview of the complement system, its interactions with glomerular structures, and insights into specific glomerular diseases exhibiting a nephrotic course. Additionally, we explore new diagnostic tools and future therapeutic approaches.

Automated Detection of Pediatric Foreign Body Aspiration from Chest X-rays Using Machine Learning.

Standard chest radiographs are a poor diagnostic tool for pediatric foreign body aspiration. Machine learning may improve upon the diagnostic capabilities of chest radiographs. The objective is to develop a machine learning algorithm that improves the diagnostic capabilities of chest radiographs in pediatric foreign body aspiration. This retrospective, diagnostic study included a retrospective chart review of patients with a potential diagnosis of FBA from 2010 to 2020. Frontal view chest radiographs were extracted, processed, and uploaded to Google AutoML Vision. The developed algorithm was then evaluated against a pediatric radiologist. The study selected 566 patients who were presented with a suspected diagnosis of foreign body aspiration. One thousand six hundred and eighty eight chest radiograph images were collected. The sensitivity and specificity of the radiologist interpretation were 50.6% (43.1-58.0) and 88.7% (85.3-91.5), respectively. The sensitivity and specificity of the algorithm were 66.7% (43.0-85.4) and 95.3% (90.6-98.1), respectively. The precision and recall of the algorithm were both 91.8% with an AuPRC of 98.3%. Chest radiograph analysis augmented with machine learning can diagnose foreign body aspiration in pediatric patients at a level similar to a read performed by a pediatric radiologist despite only using single-view, fixed images. Overall, this study highlights the potential and capabilities of machine learning in diagnosing conditions with a wide range of clinical presentations. 3 Laryngoscope, 134:3807-3814, 2024.

Assessment of post-thrombectomy brain hemorrhage in acute ischemic stroke with dual-energy CT: how reliable is it in clinical practice?

Acute ischemic stroke is currently among the main causes of mortality in Western countries. The current guidelines suggest different flowcharts of diagnostic work-up and treatment modalities, including endovascular thrombectomy. Immediately after intra-arterial recanalization, a brain CT scan is usually performed to assess for the presence of peri-procedural complications; in this setting, it is very hard, if possible, to differentiate blood from iodinated contrast material, which is normally present in ischemic tissue because of BBB disruption. Dual-energy CT may be used for this purpose, exploiting its ability to discriminate different materials. We retrospectively studied 44 patients with acute ischemic stroke who were treated with endovascular recanalization at San Giovanni Bosco Hospital in Turin and were then scanned with DECT technology. Subsequent scan was used as standard, since iodine from contrast staining is usually reabsorbed in 24h and blood persists longer. A χ2 test of independence was performed to examine the relationship between blood detected by DECT scan after the endovascular procedure and the presence of blood in the same areas on the following scans, with a significant result: χ2 (1, N = 37) = 10.7086, p = 0.0010. Patients with blood detected on DECT scans had a double chance of having hemorrhagic infarction in follow-up scans, (RR 2.02). The sensitivity and specificity of DECT were respectively 70% and 90%, with an overall diagnostic accuracy of 76% and a positive and negative predictive value, respectively, of 95% and 53%. Dual-energy CT scan after endovascular recanalization in ischemic stroke identifies early hemorrhagic infarction with excellent specificity and good overall diagnostic accuracy, representing a reliable diagnostic tool in everyday clinical practice.

Nanobody engineering for SARS-CoV-2 neutralization and detection.

Nanobodies, small protein binders derived from the camelid antibody, are highly potent inhibitors of respiratory viruses that offer several advantages over conventional antibodies as candidates for specific therapies, including high stability and low production costs. In this work, we leverage the unique properties of nanobodies and apply them as building blocks for new therapeutic and diagnostic tools. We report ultra-potent SARS-CoV-2 inhibition by engineered nanobodies comprising multiple modules in structure-guided combinations and develop nanobodies that carry signal molecules, allowing rapid detection of the SARS-CoV-2 spike protein. Our results highlight the potential of engineered nanobodies in the development of effective countermeasures, both therapeutic and diagnostic, to manage outbreaks of emerging viruses.

Navigating Lung Cancer: Exploring Progress and Obstacles - A Comprehensive Review

Lung cancer persists as a significant global health dilemma, characterized by elevated incidence and mortality rates worldwide. Despite recent strides in diagnostic methodologies, screening approaches, and therapeutic modalities, lung cancer retains its status as the foremost cause of cancer-related fatalities internationally. The disease is predominantly categorized into two primary forms: small-cell carcinomas and the notably more prevalent non-small-cell carcinomas, constituting approximately 85% of cases. While smoking stands as the primary risk factor for lung cancer, accounting for 80-90% of related deaths, other factors such as dietary habits, air pollution, genetic predisposition, and prior lung conditions play substantial roles. Diagnostic procedures encompass a range of techniques, including radiography, sputum cytology, bronchoscopy, biomarker analysis, among others. The imperative for progress and refinement in diagnostic tools, especially for early detection and monitoring in high-risk demographics, underscores the urgency. Continual research and enhancement of surgical, systemic, and localized treatments are indispensable in the battle against lung cancer. Despite advancements, challenges persist in achieving timely diagnoses, particularly in high-risk groups, and augmenting overall survival rates. This comprehensive review delves into current research advancements in lung cancer, with specific focus on classification, patient well-being, risk factors, diagnostic methodologies, and treatment options.

Evaluation of CHROMagar Candida Plus for the detection of C. auris with a panel of 206 fungal isolates and 83 colonization screening skin-swabs.

CHROMagar Candida Plus is a new formulation of chromogenic media designed for the detection and differentiation of major clinical Candida species, including Candida auris. The objective of this study is to evaluate CHROMagar Candida Plus when used according to manufacturer's instructions with a panel of 206 fungal isolates and 83 skin-swab specimens originally collected for C. auris colonization screening. Of the 68 C. auris isolates tested, 66/68 displayed the expected light-blue colony morphology and blue halo within 48 h. None of the remaining 138 non-auris isolates appeared similar to C. auris. CHROMagarCandida Plus was, therefore, inclusive to 97% of 68 C. auris isolates tested and supported visual exclusion of 100% of the 138 non-C. auris isolates tested. For the 83 colonization screening specimens, direct plating onto CHROMagarCandida Plus was 60% sensitive and 100% specific when compared to the enrichment broth gold-standard reference method. In sum, these findings demonstrate the utility of this media when working with isolates but also notable limitations when working with primary skin-swabs specimens when competing yeast species are present.IMPORTANCECandida auris is an emerging fungal pathogen of public health concern. As it continues to spread, it is important to publish evaluations of new diagnostic tools. In this study, we share our experience with a new chromogenic media which can help distinguish C. auris from related species.

Unraveling the microbial puzzle: exploring the intricate role of gut microbiota in endometriosis pathogenesis.

Endometriosis (EMs) is a prevalent gynecological disorder characterized by the growth of uterine tissue outside the uterine cavity, causing debilitating symptoms and infertility. Despite its prevalence, the exact mechanisms behind EMs development remain incompletely understood. This article presents a comprehensive overview of the relationship between gut microbiota imbalance and EMs pathogenesis. Recent research indicates that gut microbiota plays a pivotal role in various aspects of EMs, including immune regulation, generation of inflammatory factors, angiopoietin release, hormonal regulation, and endotoxin production. Dysbiosis of gut microbiota can disrupt immune responses, leading to inflammation and impaired immune clearance of endometrial fragments, resulting in the development of endometriotic lesions. The dysregulated microbiota can contribute to the release of lipopolysaccharide (LPS), triggering chronic inflammation and promoting ectopic endometrial adhesion, invasion, and angiogenesis. Furthermore, gut microbiota involvement in estrogen metabolism affects estrogen levels, which are directly related to EMs development. The review also highlights the potential of gut microbiota as a diagnostic tool and therapeutic target for EMs. Interventions such as fecal microbiota transplantation (FMT) and the use of gut microbiota preparations have demonstrated promising effects in reducing EMs symptoms. Despite the progress made, further research is needed to unravel the intricate interactions between gut microbiota and EMs, paving the way for more effective prevention and treatment strategies for this challenging condition.

A MOBILE-BASED APPLICATION FOR COVID-19 DIAGNOSIS AND RECOMMENDATION

n 2019, a new coronavirus outbreak emerged, identified in December 2019. The disease exhibits an average incubation period of 5.2 days, with flu-like symptoms, accompanied by cough and fever. COVID-19 affects various organs and tissues in the human body. While expert systems exist for disease diagnosis, they require experts to operate due to their specific platforms. This paper proposes thedevelopment of an efficient, rapid, and precise COVID-19 diagnostic system using mobile phone technology, leveraging the widespread availability of mobile devices. Unlike existing applications, this system's focus is to offer a diagnostic tool accessible to any individual without requiring expert intervention. The framework was implemented using Android Studio and the Dart platform. The resulting mobile application demonstrated user-friendliness and ease of use, ensuring a seamless and intuitive experience for The COVID-19 APP has the potential to reduce disease transmission and enable early treatment initiation, thus mitigating the risk of severe illness. This proactive approach contributes to better overall health outcomes, enhancing individuals' quality of life The mobile phone-based diagnostic system offers an accessible and reliable means for diagnosing COVID-19 without expert involvement. By leveraging mobile technology, this solution can positively impact disease management and foster a healthier population

A New Method Used to Enhance the SPAIR Image of the Spine MRI.

Magnetic resonance imaging (MRI) is a handy diagnostic tool for orthopedic disorders, particularly spinal and joint diseases. The lumbar intervertebral disc is visible in the T1 and T2 weight sequences of the spine MRI, which aids in diagnosing lumbar disc herniation, lumbar spine tuberculosis, lumbar spine tumors, and other conditions. The lumbar intervertebral disc cannot be seen accurately in the Spectral Attenuated Inversion Recovery (SPAIR) due to weaknesses in the fat and frequency offset parameters, which is not conducive to developing the intelligence diagnosis model of medical image. In order to solve this problem, we propose a composite framework, which is first to use the contrast limited adaptive histogram equalization (CLAHE) method to enhance the SPAIR image contrast of the spine MRI and then use the non-local means method to remove the noise of the image to ensure that the image contrast is uniform without losing details. We employ the Information Entropy (IE), Peak signal-to-noise ratio (PSNR), and feature similarity index measure (FSIM) to quantify image quality after enhancement by the composite framework. The outcomes of the experiments' output images and quantitative data indicate that our composite framework is better than others.

Gas Sensing Performance of Zinc Oxide Nanoparticles Fabricated via Ochradenus baccatus Leaf

ZnO nanoparticles (NPs) were prepared by green synthesis using plant leaf extraction of Ochradenus baccatus and characterized by XRD, FESEM, HRTEM, and Raman spectroscopy techniques. Since elevated CO levels have been associated with inflammatory conditions, cardiovascular diseases, and respiratory disorders and the methane gas primarily produced by gut microbiota and linked to gastrointestinal disorders and other abnormal methane levels in breath samples, the nanoparticles were applied for gas sensor fabrication. Thus, the gas sensors fabricated using ZnO nanoparticles were investigated for CH4, H2, CO, and NO2 gases. The gas sensing was performed for the fabricated sensors at various operating temperatures and gas concentrations. Interestingly, leaf-extracted green synthesized ZnO NPs were more sensitive to CH4, CO, and NO2 gases than to H2. The results of sensing studies revealed that the nanoparticles exhibit a selectivity toward gas depending on the gas type. The sensor response was also studied against the humidity. These findings bridge between the laboratory and industry sectors for future gas sensors development, which can be used for exhaled breath analysis and serve as potential diagnostic tools for highly sensitive contagious diseases.

Bacterial Community- and Hospital-Acquired Pneumonia in Patients with Critical COVID-19-A Prospective Monocentric Cohort Study.

The impact of bacterial pneumonia on patients with COVID-19 infection remains unclear. This prospective observational monocentric cohort study aims to determine the incidence of bacterial community- and hospital-acquired pneumonia (CAP and HAP) and its effect on mortality in critically ill COVID-19 patients admitted to the intensive care unit (ICU) at University Hospital Olomouc between 1 November 2020 and 31 December 2022. The secondary objectives of this study include identifying the bacterial etiology of CAP and HAP and exploring the capabilities of diagnostic tools, with a focus on inflammatory biomarkers. Data were collected from the electronic information hospital system, encompassing biomarkers, microbiological findings, and daily visit records, and subsequently evaluated by ICU physicians and clinical microbiologists. Out of 171 patients suffering from critical COVID-19, 46 (27%) had CAP, while 78 (46%) developed HAP. Critically ill COVID-19 patients who experienced bacterial CAP and HAP exhibited higher mortality compared to COVID-19 patients without any bacterial infection, with rates of 38% and 56% versus 11%, respectively. In CAP, the most frequent causative agents were chlamydophila and mycoplasma; Enterobacterales, which were multidrug-resistant in 71% of cases; Gram-negative non-fermenting rods; and Staphylococcus aureus. Notably, no strains of Streptococcus pneumoniae were detected, and only a single strain each of Haemophilus influenzae and Moraxella catarrhalis was isolated. The most frequent etiologic agents causing HAP were Enterobacterales and Gram-negative non-fermenting rods. Based on the presented results, commonly used biochemical markers demonstrated poor predictive and diagnostic accuracy. To confirm the diagnosis of bacterial CAP in our patient cohort, it was necessary to assess the initial values of inflammatory markers (particularly procalcitonin), consider clinical signs indicative of bacterial infection, and/or rely on positive microbiological findings. For HAP diagnostics, it was appropriate to conduct regular detailed clinical examinations (with a focus on evaluating respiratory functions) and closely monitor the dynamics of inflammatory markers (preferably Interleukin-6).

Amplicon and Cas9-targeted nanopore sequencing of Varroa destructor at the onset of an outbreak in Australia

Varroa destructor is a major pest of European honey bees (Apis mellifera), causing significant economic and welfare impacts. Australia remained the last continent free from V. destructor. In June 2022, a detection of V. destructor was reported in sentinel colonies at the Port of Newcastle, Australia. Rapid and accurate identification of the species was critical for timely response and management. In this case study, two Nanopore DNA sequencing methods, PCR amplicon sequencing and Cas9-targeted sequencing, were used to rapidly diagnose the species and mitochondrial haplotype of Varroa mites in parasitized colonies. Nanopore PCR amplicon sequencing provided molecular identification of the species and halogroup determination within 24 hours based on a 458 bp amplicon of the mitochondrial Cytochrome c oxidase subunit I (COXI) gene. We also developed and applied a Cas9-targeted Nanopore sequencing technique that used eight guide RNAs to enrich for 5240 bp of the mitochondrial genome. This method delivered richer data for identification within the same timeframe. Our results underscore the efficacy of Nanopore amplicon sequencing and represent the first reported application of Cas9-targeted Nanopore sequencing within a biosecurity framework. These findings enhance the repertoire of diagnostic tools available for biosecurity applications.

Multiplex Assay of Cytokines with Tunable Detection Ranges for the Precise Diagnosis of Breast Cancer.

Precise profiling of the cytokine panel consisting of different levels of cytokines can provide personalized information about several diseases at certain stages. In this study, we have designed and fabricated an "all-in-one" diagnostic tool kit to bioassay multiple inflammatory cytokines ranging from picograms per milliliter to μg/mL in a small cytokine panel. Taking advantage of the kit fabricated by the DNA-encoded assembly of nanocatalysts in dynamic regulation and signal amplification, we have demonstrated the multiplex, visual, and quantitative detection of C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) with limits of detection of 1.6 ng/mL (61.54 pM), 20 pg/mL (1.57 pM), and 4 pg/mL (0.19 pM), respectively. This diagnostic tool kit can work well with commercial kits for detecting serum cytokines from breast cancer patients treated with immunotherapies. Furthermore, a small cytokine panel composed of CRP, PCT, and IL-6 is revealed to be significantly heterogeneous in each patient and highly dynamic for different treatment courses, showing promise as a panel of quantitative biomarker candidates for individual treatments. So, our work may provide a versatile diagnostic tool kit for the visual detection of clinical biomarkers with an adjustable broad detection range.

Automated Detection of Rheumatic Heart Disease via Unsegmented Heart Sound Analysis

Rheumatic Heart Disease (RHD) remains a significant cause of morbidity and mortality in many parts of the world, particularly in low-resource settings. Early detection and intervention are critical to mitigating its progression and reducing associated complications. This paper presents an automated approach for the detection of RHD utilizing unsegmented heart sound analysis through deep learning techniques. By leveraging Spectro-temporal representations of raw heart sound signals, our proposed method aims to capture subtle yet discriminative patterns indicative of RHD pathology. The deep learning model is trained on a dataset comprising a diverse range of heart sounds, including those from both RHD-positive and RHD-negative individuals. Through rigorous evaluation of unseen data, our approach demonstrates promising performance in accurately distinguishing between RHD and healthy heart sounds. Furthermore, the proposed methodology offers the potential for scalable and cost-effective screening in resource-limited settings, thereby facilitating early identification and management of RHD cases. This work contributes to the advancement of computer-aided diagnostic tools for cardiovascular diseases, with implications for improving healthcare outcomes and reducing the burden of RHD globally. Key Words: Rheumatic Heart Disease, Heart Sound Analysis, Deep Learning, Automated Detection, Unsegmented Signals, Spectro-Temporal Representation, Cardiovascular Disease.

COPD stage detection: leveraging the auto-metric graph neural network with inspiratory and expiratory chest CT images.

Chronic obstructive pulmonary disease (COPD) is a common lung disease that can lead to restricted airflow and respiratory problems, causing a significant health, economic, and social burden. Detecting the COPD stage can provide a timely warning for prompt intervention in COPD patients. However, existing methods based on inspiratory (IN) and expiratory (EX) chest CT images are not sufficiently accurate and efficient in COPD stage detection. The lung region images are autonomously segmented from IN and EX chest CT images to extract the lung radiomics and 3D CNN features. Furthermore, a strategy for concatenating and selecting features was employed in COPD stage detection based on radiomics and 3D CNN features. Finally, we combine all the radiomics, 3D CNN features, and factor risks (age, gender, and smoking history) to detect the COPD stage based on the Auto-Metric Graph Neural Network (AMGNN). The AMGNN with radiomics and 3D CNN features achieves the best performance at 89.7 of accuracy, 90.9 of precision, 89.5 of F1-score, and 95.8 of AUC compared to six classic machine learning (ML) classifiers. Our proposed approach demonstrates high accuracy in detecting the stage of COPD using both IN and EX chest CT images. This method can potentially establish an efficient diagnostic tool for patients with COPD. Additionally, we have identified radiomics and 3D CNN as more appropriate biomarkers than Parametric Response Mapping (PRM). Moreover, our findings indicate that expiration yields better results than inspiration in detecting the stage of COPD.

Cholangiocarcinoma: Recent Advances in Molecular Pathobiology and Therapeutic Approaches.

Cholangiocarcinomas (CCA) pose a complex challenge in oncology due to diverse etiologies, necessitating tailored therapeutic approaches. This review discusses the risk factors, molecular pathology, and current therapeutic options for CCA and explores the emerging strategies encompassing targeted therapies, immunotherapy, novel compounds from natural sources, and modulation of gut microbiota. CCA are driven by an intricate landscape of genetic mutations, epigenetic dysregulation, and post-transcriptional modification, which differs based on geography (e.g., for liver fluke versus non-liver fluke-driven CCA) and exposure to environmental carcinogens (e.g., exposure to aristolochic acid). Liquid biopsy, including circulating cell-free DNA, is a potential diagnostic tool for CCA, which warrants further investigations. Currently, surgical resection is the primary curative treatment for CCA despite the technical challenges. Adjuvant chemotherapy, including cisplatin and gemcitabine, is standard for advanced, unresectable, or recurrent CCA. Second-line therapy options, such as FOLFOX (oxaliplatin and 5-FU), and the significance of radiation therapy in adjuvant, neoadjuvant, and palliative settings are also discussed. This review underscores the need for personalized therapies and demonstrates the shift towards precision medicine in CCA treatment. The development of targeted therapies, including FDA-approved drugs inhibiting FGFR2 gene fusions and IDH1 mutations, is of major research focus. Investigations into immune checkpoint inhibitors have also revealed potential clinical benefits, although improvements in survival remain elusive, especially across patient demographics. Novel compounds from natural sources exhibit anti-CCA activity, while microbiota dysbiosis emerges as a potential contributor to CCA progression, necessitating further exploration of their direct impact and mechanisms through in-depth research and clinical studies. In the future, extensive translational research efforts are imperative to bridge existing gaps and optimize therapeutic strategies to improve therapeutic outcomes for this complex malignancy.

New Perspectives on the Role of Liquid Biopsy in Bladder Cancer: Applicability to Precision Medicine.

Bladder cancer (BC) is one of the most common tumors in the world. Cystoscopy and tissue biopsy are the standard methods in screening and early diagnosis of suspicious bladder lesions. However, they are invasive procedures that may cause pain and infectious complications. Considering the limitations of both procedures, and the recurrence and resistance to BC treatment, it is necessary to develop a new non-invasive methodology for early diagnosis and multiple evaluations in patients under follow-up for bladder cancer. In recent years, liquid biopsy has proven to be a very useful diagnostic tool for the detection of tumor biomarkers. This non-invasive technique makes it possible to analyze single tumor components released into the peripheral circulation and to monitor tumor progression. Numerous biomarkers are being studied and interesting clinical applications for these in BC are being presented, with promising results in early diagnosis, detection of microscopic disease, and prediction of recurrence and response to treatment.

Point-of-Care Ultrasound (POCUS) in Adult Cardiac Arrest: Clinical Review.

Point-of-Care Ultrasound (POCUS) is a rapid and valuable diagnostic tool available in emergency and intensive care units. In the context of cardiac arrest, POCUS application can help assess cardiac activity, identify causes of arrest that could be reversible (such as pericardial effusion or pneumothorax), guide interventions like central line placement or pericardiocentesis, and provide real-time feedback on the effectiveness of resuscitation efforts, among other critical applications. Its use, in addition to cardiovascular life support maneuvers, is advocated by all resuscitation guidelines. The purpose of this narrative review is to summarize the key applications of POCUS in cardiac arrest, highlighting, among others, its prognostic, diagnostic, and forensic potential. We conducted an extensive literature review utilizing PubMed by employing key search terms regarding ultrasound and its use in cardiac arrest. Apart from its numerous advantages, its limitations and challenges such as the potential for interruption of chest compressions during image acquisition and operator proficiency should be considered as well and are discussed herein.

Étude CamiCon : évaluation d’un nouvel outil pour la réalisation d’un calendrier mictionnel automatisé et connecté

IntroductionA voiding diary (VD) is a key element in the evaluation of patients with overactive bladder (OAB) at initial presentation and during treatment to assess its effectiveness. In order to be clinically relevant, it must be performed over 3 days according to the International Continence Society (ICS). Unfortunately, some patients find it cumbersome. We aimed to evaluate the reliability and patient satisfaction when using a connected tank device. Material and methodWe conducted a single-center prospective study including 41 patients. Each patient completed a paper voiding diary and then a diary with Diary Pod® (DP) or inversely depending on the study arm. Data from 34 patients were collected. After completion of both diaries, patients completed a satisfaction questionnaire sent by email via GoogleForm. Study statistics were performed with Jamovi® and Excel® software. ResultData from 34 patients were analyzed. There was a statically significant difference (P=0.046) between the mean volume calculated from the paper VD and that calculated from the connected VD (DP). There was no statistically significant difference (P=0.112) between the mean number of daytime voids, mean number of nighttime voids (P=0.156), mean water intake (P=0.183) reported on the paper VD and the connected VD. Thirteen (42%) paper VD and 1 connected VD did not include documentation of the presence or absence of urine leakage or urgency. There was no statistically significant difference between the two calendars regarding the presence or absence of urine leakage (P=0.180) and urinary urgency (P=0.564). Eighty-four percent (26/31) preferred the connected tank to the usual method (paper/pen), while 55% (17/31) and 29% (9/31) of the participants respectively answered that the DP was “very definitely” or “definitely” an aid for performing VD. Nevertheless, 39% (12/31) and 55% (17/31) considered its price to be high or fair and only 22% (7/31) were inclined to buy it. ConclusionThis study showed that the Diary connected reservoir Pod® is a reliable and innovative tool for voiding schedules. It facilitates data collection for the majority of patients (83%) and could, through better patient compliance, provide better quality data and help their interpretation by the physician. These factors could encourage the implementation of the connected voiding diary as a diagnostic tool. It would also be used for the assessment of treatment effectiveness in daily clinical practice as well as in research. Its cost remains a major obstacle, judged by 39% of patients to be too high, and could therefore be proposed in specific situations requiring precise data.

An evaluation of common stock assessment diagnostic tools for choosing among state-space models with multiple random effects processes

State-space models have received increasing attention in fisheries stock assessments given their flexibility to incorporate multiple sources of process errors. Identifying which process errors to include is important because incorrectly including some process errors can induce bias in management quantities. Existing model selection tools commonly applied in traditional statistical catch-at-age models may not perform as well for state-space models. We evaluated the efficacy of common diagnostic tools for correctly identifying the presence, absence, and magnitude of three process errors (survival, selectivity, and natural mortality) in a simulation–estimation experiment. No model diagnostic tools could consistently identify the correct process error structure in all situations. Incorrectly attributing the process error from natural mortality to other processes, or vice versa, led to relatively large bias in management quantities. Furthermore, incorrectly including an additional source of process error in the assessment models exhibited similar performance to the correct model and generally showed unbiased estimates of management quantities; incorrectly excluding a source of process error, however, generated large biases. Thus, despite not having generally reliable model diagnostic tools for state-space assessments, practitioners should err on the side of using overly complex models, except for natural mortality unless there is external corroborating evidence of changing natural mortality.