Diagnostic Accuracy Research Articles

O-057 Newly identified female mutations causing failed fertilization

Abstract Over the past decade, advancements in next-generation sequencing technology, alongside reduced costs, and the rising demand for infertility medical care, have resulted in the discovery of new genes and genetic variants linked to infertility conditions. Phenotypes of ICSI failure, such as oocyte maturation arrest (OMA), fertilization failure (FF) and embryo developmental arrest (EDA), can now be attributed to male or female genetic causes. This represents a transformative shift in patient treatment, allowing the identification of some cases previously classified as unexplained infertility, thereby reducing patient stress. Moreover, it facilitates personalized treatment recommendations, as well as paves the way for the exploration of novel treatment options, thus expanding research opportunities. This talk will review the genetic causes of FF following ICSI, with the main focus on the newly identified female causes, as well as give an update on current diagnostic tests and treatment options for this infertility condition. FF after ICSI still occurs in 1-3% of ICSI cycles, primarily due to oocyte activation deficiency (OAD). Defects in the male PLCζ protein, responsible of inducing calcium oscillations during oocyte activation, have long been known as the leading cause of OAD. Recent discoveries have identified genetic variants in the male genes ACTL7A, ACTL9 and IQCN, which also reduce PLCζ protein content in sperm cells and thus, contribute to FF after ICSI. Additionally, for the first time in 2018, mutations in a female gene (WEE2) crucial for oocyte activation were identified. WEE2 is an oocyte kinase that acts downstream the calcium release during fertilization. Interestingly, genetic variants in other female genes, such as PATL2, TUBB8 and CDC20 associated mainly to OMA and TLE6 and NLRP5 associated mainly to EDA, have also been described to cause failed fertilization in some patients. Determining whether the deficiency lies in sperm- or oocyte-related genes is crucial for tailoring the most effective treatment for FF after ICSI. For sperm-related factors, assisted oocyte activation (AOA), which consists in the artificial induction of calcium oscillations using calcium ionophores, has proven highly beneficial. However, most patients with oocyte-factors do not benefit from AOA (e.g. patients with WEE2 variants). In this regard, wild-type cRNA injection of the defected protein has been shown to rescue fertilization. A more generalist approach, such as maternal spindle transfer, which consists in replacing poor-quality oocyte cytoplasm with healthy cytoplasm from a donor oocyte, represents a potential treatment for these patients, as recently demonstrated in infertile females with repeated IVF failures. Nevertheless, further research into the safety of these procedures is needed before clinical application, and for now, gamete donation should be considered when facing female-related FF.

The Value of Labial Gland Biopsies as a Diagnostic Test for Sjögren’s Syndrome

PurposeThere are a number of diagnostic criteria that can be used to support a diagnosis of Sjögren’s syndrome (SS), a chronic autoimmune condition often characterised by xerostomia and xerophthalmia. Of the available investigations, the most invasive is the labial gland biopsy (LGB) for histopathology, which is associated with a risk of long-term altered sensation to the lip. A positive histological diagnosis is currently considered to be one of the most objective criteria, however there is debate about the interobserver agreement between pathologists, as well as the sensitivity and specificity of this test. We aim to determine if the diagnostic value of the LGB is significant enough to warrant the surgical procedure and its associated risks.MethodsThis study involved assessing the degree of agreement between members of a pathology team for a cohort of 50 LGBs taken for the purpose of confirming or excluding SS. The Tarpley system was used, which involves the allocation of a ‘focus score’. Additionally, the histological diagnoses were compared to the relevant serological findings where available.ResultsAll cases within the cohort had adequate tissue for assessment. 84% agreement (Cohen’s Kappa = 0.585) was seen between the current team’s consensus and the original reporting pathologist on whether the appearance was supportive of SS. However, only 58% agreement was seen for focus scores (Weighted Kappa = 0.496). The agreement between the serology result and whether the histology was supportive of SS was 79% (Cohen’s Kappa = 0.493).ConclusionThe findings raise the possibility that undue emphasis is placed on the value of a histological SS diagnosis. The current system for assessing and grading these biopsies is ambiguous in nature, with a low threshold considered indicative of SS. Due to the risk of complications associated with a LGB, alternative minimally invasive investigations should always be considered. The histological findings in isolation, particularly when a low focus score is seen, may not be predictive of a diagnosis of SS.

P-034 Revolutionizing sperm morphology assessment: A novel artificial intelligence optic microscope (AIOM)-powered platform for consistent and reliable analysis in male infertility diagnosis

Abstract Study question Does AIOM-based live sperm morphology annotation provide consistent and accurate results for assessing sperm morphology? Summary answer AIOM offers precise and reproducible sperm morphology evaluations which can enhance diagnostic efficiency with a single and reliable test. What is known already Semen analysis remains the primary diagnostic tool for male infertility. Unlike concentration and motility, sperm morphology shows a much higher correlation with paternal genetic integrity. However, it poses challenges due to inter-observer and inter-laboratory variability. The 2023 semen proficiency test highlighted these inconsistencies, reporting deviations of up to 13% among laboratories and acceptability ranging from 0% to 43%. This inconsistency is linked to complex staining procedures and interpretive subjectivity. To address these challenges, our study evaluates a novel AIOM-assisted platform, employing a live sperm morphology deep learning model. We aim to explore the platform’s reproducibility and reliability. Study design, size, duration In the first stage, liquefied semen specimens were split into three aliquots, each assigned to one of three operators (operators 1–3). Each operator assessed sperm morphology using Diff-Quik and live sperm morphology using the LensHooke® X12 semen analysis system (Bonraybio, Taichung). In the second stage, a single well-trained operator conducted sperm morphology assessments for three replicates (replicates 1-3) using the two methods. Interclass-correlation coefficients (ICCs) were calculated to assess consistency between replicates and operators. Participants/materials, setting, methods Semen samples (n = 30) were collected post 2-5 day abstinence and liquefied at room temperature for 30 minutes. Specimens were diluted to 100 million/mL with HTF, and underwent Diff-Quik staining according to WHO’s instruction. Aliquot of 3 μL semen specimen was loaded to 10-μm LensHooke® CS3 slide and analyzed by X12 analysis using live sperm morphology algorithm. Main results and the role of chance X12 utilizes a deep learning algorithm to automatically annotate sperm morphology, focusing on parameters such as sperm head, midpiece, tail, and excess residual cytoplasm, ultimately generating outputs for normal morphology and the teratozoospermic index (TZI) based on WHO strict criteria. Compared to manual Diff-Quik analysis, X12 showed higher consistency across all parameters, with ICCs above 0.85, unlike the manual method’s lower ICCs (below 0.70). The determination of abnormal midpiece had the lowest agreement between operators [ICC (95% CI): 0.15 (-0.61–0.58)]. In contrast, X12 demonstrated high agreement in all parameters, with ICC values consistently exceeding 0.85. When comparing the agreement of normal morphology rates between the two methods, a notable difference was observed [(Manual method: 0.59 (0.22–0.8) versus X12: 0.8 (0.61–0.9)]. To minimize inter-operator variability, a highly trained operator conducted three replicates following the manual method, thereby reducing deviations between measures. Remarkably, a single assessment of live sperm morphology produced results that were comparable to the mean average of repeated measures obtained through manual methods. In conclusion, the new platform for sperm morphology assessment, contingent on AIOM technology, is a reproducible and reliable tool in male infertility diagnosis. Limitations, reasons for caution This study’s limitations include its laboratory-based nature and a small sample size. Further research should include a more diverse and larger patient cohort to validate the efficacy and accuracy of AIOM in live sperm morphology assessment. Wider implications of the findings AIOM’s integration of automated interpretation simplifies sperm morphology assessment, reducing sample requirements and is smear-free. This advancement not only enhances diagnostic testing consistency but also eases andrologists’ workloads. This platform can contribute to standardized sperm analysis and improved laboratory management. Trial registration number Not applicable

Abbott realtime MTB assay for detecting Mycobacterium tuberculosis complex in respiratory specimens: a cost-benefit analysis.

Molecular screening for Mycobacterium tuberculosis (MTB) can lead to rapid empirical treatment inception and reduce hospitalization time and complementary diagnostic tests. However, in low-prevalence settings, the cost-benefit balance remains controversial due to the high cost. We used a Markov model to perform an economic analysis to evaluate the profit after implementing molecular MTB screening (Period B) compared with conventional culture testing (Period A) in respiratory samples from 7,452 consecutive subjects with presumed tuberculosis (TB). The proportion of positivity was comparable between both periods (P > 0.05), with a total of 2.16 and 1.78 samples/patient requested in periods A and B, respectively (P < 0.001). The mean length of hospital stay was 8.66 days (95%CI: 7.63-9.70) in Period B and 11.51 days (95%CI: 10.15-12.87) in Period A (P = 0.001). The healthcare costs associated with diagnosing patients with presumed TB were reduced by €717.95 per patient with PCR screening. The probability of remaining hospitalized and the need for a greater number of outpatient specialty care visits were the variables with the most weight in the model. Employing PCR as an MTB screening method in a low-prevalence setting may increase the profits to the system.

Use of diagnostic tests in elderly patients consulting the emergency department. Analysis of the emergency department and elder needs cohort (EDEN-8)

ObjectiveAnalyse the association between the use of diagnostic tests and the characteristics of older patients 65 years of age or more who consult the emergency department (ED). MethodsWe performed an analysis of the EDEN cohort that includes patients who consulted 52 Spanish EDs. The association of age, sex, and ageing characteristics with the use of diagnostic tests (blood tests, electrocardiogram (ECG), microbiological cultures, X-ray, computed tomography, ultrasound, invasive techniques) was studied. The association was analysed by calculating the adjusted odds ratios (aOR) and their 95 % confidence intervals (CI) using a logistic regression model. ResultsA total of 25,557 patients were analysed. There was an increase in the use of diagnostic tests based on age, with an aOR for blood test of 1.805 (95 %CI 1.671 – 1.950), ECG 1.793 (95 %CI 1.664 – 1.932) and X-ray 1.707 (95 %CI 1.583 – 1.840) in the group of 85 years or more. The use of diagnostic tests is lower in the female population. Most ageing characteristics (cognitive impairment, previous falls, polypharmacy, dependence, and comorbidity) were independently associated with increased use of diagnostic tests. ConclusionsAge, and the characteristics of ageing itself are generally associated with a greater use of diagnostic tests in the ED.

Hearing Assessment of Free-Ranging Owls and Implications for Wildlife Rehabilitation: 31 Cases (2014-2023).

Owls, members of the avian order Strigiformes, are nocturnal birds of prey that are found worldwide except for Antarctica. Traumatized, free-ranging owls are commonly presented to veterinary hospitals and wildlife rehabilitation facilities with the goal of providing medical care and rehabilitation to enable release back into their natural habitat. Minimal guidelines exist for the release of wildlife, and whereas a need for functional vision is described in raptors, assessing and evaluating hearing is usually not mentioned. This can be problematic for nocturnal predators because hearing is the primary sense utilized by owls when hunting and navigating in their dark environment. The brainstem auditory evoked response (BAER) test is a minimally invasive, objective assessment of hearing commonly used in companion animals. To the authors' knowledge, routine or standardized BAER evaluation has not been reported in traumatized, free-ranging owls. In the following retrospective study, 31 free-ranging owls presented to the University of Georgia Veterinary Teaching Hospital for known or suspected trauma or being found in a debilitated state underwent BAER testing to assess for the presence of complete sensorineural hearing loss. Similar to assessment of hearing in companion animals, the BAER test was elicited using a broad click stimulus delivered at 85 dB nHL. In all owls, qualitative assessment and peak latency measurements of the BAER test reflected hearing ability. This study highlights the importance of hearing in nocturnal raptors, how BAER testing can aid in decision making regarding rehabilitation, and provides a foundation for further investigation of hearing loss in traumatized owls. We suggest that veterinarians working with free-ranging owls in a rehabilitation setting should consider BAER testing as part of routine diagnostic testing.

Mollaret’s Meningitis due to Herpes Simplex Virus 2: A Case Report and Review of the Literature

Mollaret’s meningitis is a rare neurological disorder characterized by recurrent episodes of aseptic lymphocytic meningitis, often associated with herpes simplex virus 2 (HSV-2) infection. We report the case of a 39 y.o. Italian woman who experienced four episodes of aseptic lymphocytic meningitis between 2004 and 2023, diagnosed as Mollaret’s meningitis. In each episode, the patient presented with fever, severe headache and photophobia. In two episodes cutaneous vesicles in the left gluteal area preceding meningitis symptoms were also reported. A diagnostic evaluation included a physical–chemical analysis and a real-time PCR of the cerebrospinal fluid (CSF). The CSF presented pleocytosis with lymphocytic predominance and a positive HSV-2 load, with a peak of 1234 copies/mL. The patient was treated successfully with acyclovir, and the symptoms resolved without neurological sequelae. This case highlights the importance of comprehensive diagnostic testing and vigilant monitoring to manage Mollaret’s syndrome effectively.

Improved water supply infrastructure to reduce acute diarrhoeal diseases and cholera in Uvira, Democratic Republic of the Congo: Results and lessons learned from a pragmatic trial.

Safely managed drinking water is critical to prevent diarrhoeal diseases, including cholera, but evidence on the effectiveness of piped water supply in reducing these diseases in low-income and complex emergency settings remains scarce. We conducted a trial of water supply infrastructure improvements in Uvira (DRC). Our primary objective was to estimate the relationship between a composite index of water service quality and the monthly number of suspected cholera cases admitted to treatment facilities and, as a secondary analysis, the number of cases confirmed by rapid diagnostic tests. Other exposures included the quantity of supplied water and service continuity. We used Poisson generalised linear models with generalised estimating equations to estimate incidence rate ratios. Associations between suspected cholera incidence and water service quality (RR 0·86, 95% CI 0·73-1·01), quantity (RR 0·80, 95% CI 0·62-1·02) and continuity (RR 0·81, 95% CI 0·77-0·86) were estimated. The magnitudes of the associations were similar between confirmed cholera incidence and water service quality (RR 0·84, 95% CI 0·73-0·97), quantity (RR 0·76, 95% CI 0·61-0·94) and continuity (RR 0·75, 95% CI 0·69-0·81). These results suggest that an additional 5 L/user/day or 1.2 hour per day of water production could reduce confirmed cholera by 24% (95% CI 6-39%) and 25% (95% CI 19-31%), respectively. Ensuring a sufficient and continuous piped water supply may substantially reduce the burden of endemic cholera and diarrhoeal diseases but evaluating this rigorously is challenging. Pragmatic strategies are needed for public health research on complex interventions in protracted emergency settings. The trial is registered in ClinicalTrials.gov ID NCT02928341. https://classic.clinicaltrials.gov/ct2/show/NCT02928341.

P-735 Is Artificial Intelligence (AI) currently able to provide evidence-based scientific responses on methods that can improve the outcomes of embryo transfers?

Abstract Study question Could chatbots potentially be used as tools for both patients’ and physicians’ education in an infertility journey? Summary answer Artificial Intelligence (AI) is not yet in a position to give clear, evidence-based recommendations in the field of fertility, particularly concerning embryo transfer. What is known already The rapid development of AI has raised questions about its potential uses in different sectors of everyday life. Individuals from diverse fields have tried to incorporate its usage in their personal but also in their professional lives, with varying levels of success. Specifically in medicine, ChatGPT has been studied intensely with more than 400 related articles having been indexed in PubMed until May 2023, while AI has reportedly also succeeded in several standardized medical tests and passed several Medical Board examinations. Hence the question arises whether chatbots could be used as tools for clinical decision-making or patients’ and physicians’ education. Study design, size, duration We used nine of the most popular free AI chatbots available (ChatGPT, Bard, Writesonic, You, Perplexity, Learnt, Bing, Magickpen, and Rytr) and entered the following command: “Write me a 300-word scientific essay about evidence-based methods that can improve the outcomes of embryo transfer” in May 2023. We collected the responses and extracted the methods each chatbot suggested. When sufficient similarity among answers was present we categorized the answers under one category to facilitate the study. Participants/materials, setting, methods We calculated descriptive statistics and the prevalence of each response. We used as a comparator for widely acceptable practices that are proven to improve embryo transfer outcomes the 2017 ASRM guideline on performing embryo transfer taking also into consideration more current literature. Data was compared using chi-squared tests and a level of p &amp;lt; 0.05 was used as the threshold of statistical significance. Main results and the role of chance The range of the recommendations was from one to nine per chatbot (median = 4, IQR = 2) with an average of 4.78 suggestions per chatbot. Out of a total of 43 recommendations, which could be grouped into 19 similar categories, only 3/19 (15.8%) were evidence-based practices, those being “ultrasound-guided embryo transfer”, which was also the most commonly appearing response, appearing in 7/9 (77.8%) chatbots, “single embryo transfer” appearing in 4/9 (44.4%) chatbots and “use of a soft catheter” in 2/9 (22.2%) chatbots. Some controversial responses appeared even more often than the two latter evidence-based ones with “preimplantation genetic testing (PGT)” being the second most common response with 6/9 chatbots suggesting it (66.7%) and the vague suggestion of “optimal endometrium preparation” being in the third place with 5/9 chatbots (55.6%), both non-evidence-based practices to improve embryo transfer. The majority of the recommendations were unique, with 10 answers appearing only once (1/9; 11.1%), those being “endometrial scratching”, “natural cycle embryo transfer”, “use of GnRH antagonist protocol”, “blastocyst transfer”, “use of specialized catheter”, “preimplantation genetic screening (PGS)”, “mock embryo transfer”, “uninterrupted embryo culture”, “minimizing transfer time”, and “maintaining temperature and pH of the culture media”. Limitations, reasons for caution Firstly, we only used some of the most popular chatbots and not all existing ones. Additionally, chatbots tend to give different answers when repeatedly asked the same questions. However, we believe that our study effectively captures the prevailing practices of chatbot users, who typically pose a question only once. Wider implications of the findings Both patients and physicians should be wary of guiding care based on chatbot recommendations in infertility since the majority of responses consists of scientifically unsupported recommendations. Chatbot results might improve with time especially if trained to obtain information from validated medical databases, however, this will have to be verified scientifically. Trial registration number N/A

The use of natural language processing for the identification of ageing syndromes including sarcopenia, frailty and falls in electronic healthcare records: a systematic review.

Recording and coding of ageing syndromes in hospital records is known to be suboptimal. Natural Language Processing algorithms may be useful to identify diagnoses in electronic healthcare records to improve the recording and coding of these ageing syndromes, but the feasibility and diagnostic accuracy of such algorithms are unclear. We conducted a systematic review according to a predefined protocol and in line with Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Searches were run from the inception of each database to the end of September 2023 in PubMed, Medline, Embase, CINAHL, ACM digital library, IEEE Xplore and Scopus. Eligible studies were identified via independent review of search results by two coauthors and data extracted from each study to identify the computational method, source of text, testing strategy and performance metrics. Data were synthesised narratively by ageing syndrome and computational method in line with the Studies Without Meta-analysis guidelines. From 1030 titles screened, 22 studies were eligible for inclusion. One study focussed on identifying sarcopenia, one frailty, twelve falls, five delirium, five dementia and four incontinence. Sensitivity (57.1%-100%) of algorithms compared with a reference standard was reported in 20 studies, and specificity (84.0%-100%) was reported in only 12 studies. Study design quality was variable with results relevant to diagnostic accuracy not always reported, and few studies undertaking external validation of algorithms. Current evidence suggests that Natural Language Processing algorithms can identify ageing syndromes in electronic health records. However, algorithms require testing in rigorously designed diagnostic accuracy studies with appropriate metrics reported.

Cost-Effectiveness of Plasma Microbial Cell-Free DNA Sequencing When Added to Usual Care Diagnostic Testing for Immunocompromised Host Pneumonia.

Immunocompromised host pneumonia (ICHP) is an important cause of morbidity and mortality, yet usual care (UC) diagnostic tests often fail to identify an infectious etiology. A US-based, multicenter study (PICKUP) among ICHP patients with hematological malignancies, including hematological cell transplant recipients, showed that plasma microbial cell-free DNA (mcfDNA) sequencing provided significant additive diagnostic value. The objective of this study was to perform a cost-effectiveness analysis (CEA) of adding mcfDNA sequencing to UC diagnostic testing for hospitalized ICHP patients. A semi-Markov model was utilized from the US third-party payer's perspective such that only direct costs were included, using a lifetime time horizon with discount rates of 3% for costs and benefits. Three comparators were considered: (1) All UC, which included non-invasive (NI) and invasive testing and early bronchoscopy; (2) All UC & mcfDNA; and (3) NI UC & mcfDNA & conditional UC Bronch (later bronchoscopy if the initial tests are negative). The model considered whether a probable causative infectious etiology was identified and if the patient received appropriate antimicrobial treatment through expert adjudication, and if the patient died in-hospital. The primary endpoints were total costs, life-years (LYs), equal value life-years (evLYs), quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio per QALY. Extensive scenario and probabilistic sensitivity analyses (PSA) were conducted. At a price of $2000 (2023 USD) for the plasma mcfDNA, All UC & mcfDNA was more costly ($165,247 vs $153,642) but more effective (13.39 vs 12.47 LYs gained; 10.20 vs 9.42 evLYs gained; 10.11 vs 9.42 QALYs gained) compared to All UC alone, giving a cost/QALY of $16,761. NI UC & mcfDNA & conditional UC Bronch was also more costly ($162,655 vs $153,642) and more effective (13.19 vs 12.47 LYs gained; 9.96 vs 9.42 evLYs gained; 9.96 vs 9.42 QALYs gained) compared to All UC alone, with a cost/QALY of $16,729. The PSA showed that above a willingness-to-pay threshold of $50,000/QALY, All UC & mcfDNA was the preferred scenario on cost-effectiveness grounds (as it provides the most QALYs gained). Further scenario analyses found that All UC & mcfDNA always improved patient outcomes but was not cost saving, even when the price of mcfDNA was set to $0. Based on the evidence available at the time of this analysis, this CEA suggests that mcfDNA may be cost-effective when added to All UC, as well as in a scenario using conditional bronchoscopy when NI testing fails to identify a probable infectious etiology for ICHP. Adding mcfDNA testing to UC diagnostic testing should allow more patients to receive appropriate therapy earlier and improve patient outcomes.

Optimization of Variational Mode Decomposition-Convolutional Neural Network-Bidirectional Long Short Term Memory Rolling Bearing Fault Diagnosis Model Based on Improved Dung Beetle Optimizer Algorithm

(1) Background: Rolling bearings are important components in mechanical equipment, but they are also components with a high failure rate. Once a malfunction occurs, it will cause mechanical equipment to malfunction and may even affect personnel safety. Therefore, studying the fault diagnosis methods for rolling bearings is of great significance and is also a current research hotspot and frontier. However, the vibration signals of rolling bearings usually exhibit nonlinear and non-stationary characteristics, and are easily affected by industrial environmental noise, making it difficult to accurately diagnose bearing faults. (2) Methods: Therefore, this article proposes a rolling bearing fault diagnosis model based on an improved dung beetle optimizer (DBO) algorithm-optimized variational mode decomposition-convolutional neural network-bidirectional long short-term memory (VMD-CNN-BiLSTM). Firstly, an improved DBO algorithm named CSADBO is proposed by integrating multiple strategies such as chaotic mapping and cooperative search. Secondly, the optimal parameter combination of VMD was adaptively determined through the CSADBO algorithm, and the optimized VMD algorithm was used to perform modal decomposition on the bearing vibration signal. Then, CNN-BiLSTM was used as the model for fault classification, and hyperparameters of the model were optimized using the CSADBO algorithm. (3) Results: Finally, multiple experiments were conducted on the bearing dataset of Case Western Reserve University, and the proposed method achieved an average diagnostic accuracy of 99.6%. (4) Conclusions: Experimental comparisons were made with other models to verify the effectiveness of the proposed model. The experimental results show that the proposed model based on an improved DBO algorithm optimized VMD-CNN-BiLSTM can effectively be used for rolling bearing fault diagnosis, with high diagnostic accuracy, and can provide a theoretical reference for other related fault diagnosis problems.

Understanding the value of monocyte distribution width (MDW) in acutely ill medical patients presenting to the emergency department: a prospective single center evaluation

The monocyte distribution width (MDW) has emerged as a promising biomarker for accurate and early identification of patients with potentially life-threatening infections. Here we tested the diagnostic performance of MDW in adult patients requiring hospital admission for community-acquired infections and sepsis, evaluated sources of heterogeneity in the estimates of diagnostic accuracy, and assessed the meaning of MDW in a patient population presenting to the emergency department (ED) for acute non-infectious conditions. 1925 consecutive patients were categorized into three groups: non-infection (n = 1507), infection (n = 316), and sepsis/septic shock (n = 102). Diagnostic performance for infection or sepsis of MDW alone or in combination with components of SOFA was tested using AUC of ROC curves, sensitivity, and specificity. The relationship between MDW and different pathogens as well as the impact of non-infectious conditions on MDW values were explored. For the prediction of infection, the AUC/ROC of MDW (0.84) was nearly overlapping that of procalcitonin (0.83), and C-reactive protein (0.89). Statistical optimal cut-off value for MDW was 21 for predicting infection (sensitivity 73%, specificity 82%) and 22 for predicting sepsis (sensitivity 79%, specificity 83%). The best threshold to rule out infection was MDW ≤ 17 (NPV 96.9, 95% CI 88.3–100.0), and ≤ 18 (NPV 99.5, 95% CI 98.3–100.0) to rule out sepsis. The combination of MDW with markers of organ dysfunction (creatinine, bilirubin, platelets) substantially improved the AUC (0.96 (95% CI 0.94–0.97); specificity and sensitivity of 88% and 94%, respectively). In conclusion, MDW has a good diagnostic performance in diagnosing infection and sepsis in patients presenting in ED. Its use as an infection marker even increases when combined with other markers of organ dysfunction. Understanding the impact of interactions of non-infectious conditions and comorbidities on MDW and its diagnostic accuracy requires further elucidation.

A combined technique for power transformer fault diagnosis based on k‐means clustering and support vector machine

AbstractThis contribution presents a two‐step hybrid diagnostic approach, combining k‐means clustering for subset formation, followed by subset analysis conducted by human experts. As the feature input vector has a significant influence on the performance of unsupervised machine learning algorithms, seven feature input vectors derived from traditional methods, including Duval pentagon method, Rogers ratio method, three ratios technique, Denkyoken method, ensemble gas characteristics method, Duval triangle method, and Gouda triangle method were explored for the subset formation stage. The seven proposed individual methods, corresponding to the seven feature input vectors, were implemented using a dataset of 595 DGA samples and tested on an additional 254 DGA samples. Furthermore, a combined technique based on a support vector machine was introduced, utilising the diagnostic results of the individual methods as input features. From training and testing, with diagnostic outcomes of 91.09% and 90.94%, the combined technique demonstrated the highest overall diagnostic accuracies. Using the IEC TC10 database, the diagnosis accuracies of the proposed diagnostic methods were compared to existing methods of literature. From the results obtained, the combined technique outperformed the proposed individual methods and existing methods used for comparison.

Validation of the IOTA ADNEX Model Among Japanese Women Performed by Gynecology Trainees and Ultrasound Specialists: A Retrospective Diagnostic Accuracy Study.

This study aimed to validate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) Assessment of Different NEoplasias in the adneXa (ADNEX) model in Japanese women, population with a distinct adnexal mass distribution compared with European women, and to evaluate the model's utility by gynecology trainees and ultrasound specialists. This single-center, retrospective study analyzed ultrasound data from January 2017 to March 2020 of 206 women with adnexal masses. Patients who underwent ultrasonography and serum CA-125 measurement and received postsurgery histological diagnosis were included. The ADNEX model's diagnostic performance was evaluated by two trainees and two specialists using the area under the receiver operating characteristic curve (AUC) and measures of accuracy, sensitivity, specificity, and predictive values for overall performance and each examiner. Of the 206 included Japanese women, the prevalence of malignancy was 30.1%, including borderline cases. The overall AUC for distinguishing malignancy was 0.848 (95% confidence interval [CI]: 0.817-0.880). The AUC for each examiner ranged from 0.791 to 0.898, with Specialist 2 showing the highest accuracy and sensitivity varying between 0.677 and 0.839. A moderate degree of agreement was noted among the four examiners (Fleiss' kappa was 0.586). The performance of trainees and specialists differed significantly in evaluating the solid tissue and the papillary projections in both malignant and benign groups (P < .001). The IOTA ADNEX model effectively differentiates benign and malignant adnexal masses in Japanese women. Although the accuracy matched up moderately among the four examiners, better accuracy is expected with training in evaluating solid tissue and papillary projections.

The value of 68Ga-PSMA PET/CT in the diagnosis of intracapsular prostate cancer with a poor prognosis

ObjectiveTo evaluate the diagnostic value of 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) for intracapsular prostate cancer with a poor prognosis (PPC) and no extracapsular invasion or distant metastasis.MethodsThe PET/CT images and clinical data of 221 patients were retrospectively analyzed. These patients all had clear pathological results. The maximum standard uptake value (SUVmax) of the main lesions was measured at the postprocessing workstation and was tested for correlation with the pathological score. The diagnostic accuracy was calculated using the receiver operating characteristic (ROC) curve, and the best diagnostic threshold was calculated. The correlation between SUVmax and the International Society of Urological Pathology Grade Group (GG) was also analyzed.ResultsThe pathological results of the 221 patients were 48 benign lesions and 173 malignant lesions, including 81 PPC. Low-, intermediate-, and high-risk prostate cancers made up 21.97% (38/173), 54.33% (94/173), and 23.70% (41/173) of the malignant lesions, respectively. SUVmax and GG were positively correlated (r = 0.54, P < 0.01). The best SUVmax thresholds for 68Ga-PSMA PET/CT for the diagnosis of intracapsular PC and PPC were 7.95 and 13.94, respectively; the specificities were 0.83 and 0.85, the negative predictive values were 0.55 and 0.87, and the areas under the ROC curves were 0.88 and 0.88, respectively.Conclusion68Ga-PSMA PET/CT has high specificity and NPV in the diagnosis of intracapsular PPC, but the sensitivity for the diagnosis of intracapsular low-risk PC is low, which may cause some cases to be undetected.

Cutaneous Adverse Drug Reactions to Antidiabetic Medications and Medical Devices Used in Management of Diabetes Mellitus

Context: Approximately 537 million adults (20 - 79 years) worldwide suffer from diabetes, a number that is estimated to reach 643 million by 2030. With the rising prevalence of diabetes, pharmacological therapy has become a cornerstone for its management. The advent of newer devices and drug categories has led to a multitude of adverse drug reactions, with a significant portion being cutaneous side effects. Given that the majority of patients are on multiple other medications, such as oral hypoglycemic agents, antihypertensives, and drugs for coronary artery disease and dyslipidemia, establishing the specific cause of adverse reactions can be challenging. Since the major step in management depends on avoiding or regulating the dose of the culprit drug, it is crucial for the treating clinician to be aware of the common adverse drug reactions associated with these medications. Objective: The article aims to review the reported cutaneous adverse events of oral hypoglycemic agents, insulin, and newer devices in the management of diabetes mellitus. Evidence Acquisition: A PubMed search was conducted using the keywords 'diabetes,' 'cutaneous side effects,' 'insulin,' 'OHA,' 'sulfonylureas,' 'metformin,' and 'antidiabetic drugs.' Results: New adverse events for each category of drugs are continually being identified and reported. These adverse events range from mild rash/pruritus to severe, life-threatening allergies. Conclusions: The management of any adverse reaction includes identifying and avoiding the causative agent. However, with limited literature on the cutaneous side effects of antidiabetic therapeutics, and many being case reports, it can be difficult for clinicians to diagnose these reactions. Our article provides a concise review of the vast spectrum of cutaneous side effects that these drugs and devices can cause, along with diagnostic tests and management strategies.

A cluster-randomized trial of client and provider directed financial interventions to align incentives with appropriate case management in private medicine retailers: Results of the TESTsmART trial in Lagos, Nigeria.

Malaria remains a major health priority in Nigeria. Among children with fever who seek care, less than a quarter gets tested for malaria, leading to inappropriate use of the recommended treatment for malaria; Artemisinin-based Combination Therapy (ACT). Here we test an innovative strategy to target ACT subsidies to clients seeking care in Nigeria's private retail health sector who have a confirmed malaria diagnosis. We supported point-of-care malaria testing (mRDTs) in 48 Private Medicine Retailers (PMRs) in the city of Lagos, Nigeria and randomized them to two study arms; a control arm offering subsidized mRDT testing for USD $0.66, and an intervention arm where, in addition to access to subsidized testing as in the control arm, clients who received a positive mRDT at the PMR were eligible for a free (fully subsidized) first-line ACT and PMRs received USD $0.2 for every mRDT performed. Our primary outcome was the proportion of ACTs dispensed to individuals with a positive diagnostic test. Secondary outcomes included proportion of clients who were tested at the PMR and adherence to diagnostic test results. Overall, 23% of clients chose to test at the PMR. Test results seemed to inform treatment decisions and resulted in enhanced targeting of ACTs to confirmed malaria cases with only 26% of test-negative clients purchasing an ACT compared to 58% of untested clients. However, the intervention did not offer further improvements, compared to the control arm, in testing rates or dispensing of ACTs to test-positive clients. We found that ACT subsidies were not passed on to clients testing positive in the intervention arm. We conclude that mRDTs could reduce ACT overconsumption in Nigeria's private retail health sector, but PMR-oriented incentive structures are difficult to implement and may need to be complemented with interventions targeting clients of PMRs to increase test uptake and adherence. Trials registration: Clinical Trials Registration Number: NCT04428307. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7816435/ Correction: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476591/.

Rapid detection of lung cancer based on serum Raman spectroscopy and a support vector machine: a case-control study

BackgroundEarly screening and detection of lung cancer is essential for the diagnosis and prognosis of the disease. In this paper, we investigated the feasibility of serum Raman spectroscopy for rapid lung cancer screening.MethodsRaman spectra were collected from 45 patients with lung cancer, 45 with benign lung lesions, and 45 healthy volunteers. And then the support vector machine (SVM) algorithm was applied to build a diagnostic model for lung cancer. Furthermore, 15 independent individuals were sampled for external validation, including 5 lung cancer patients, 5 benign lung lesion patients, and 5 healthy controls.ResultsThe diagnostic sensitivity, specificity, and accuracy were 91.67%, 92.22%, 90.56% (lung cancer vs. healthy control), 92.22%,95.56%,93.33% (benign lung lesion vs. healthy) and 80.00%, 83.33%, 80.83% (lung cancer vs. benign lung lesion), repectively. In the independent validation cohort, our model showed that all the samples were classified correctly.ConclusionTherefore, this study demonstrates that the serum Raman spectroscopy analysis technique combined with the SVM algorithm has great potential for the noninvasive detection of lung cancer.

Efficacy of an Artificial Intelligence App (Aysa) in Dermatological Diagnosis: Cross-Sectional Analysis.

Dermatology is an ideal specialty for artificial intelligence (AI)-driven image recognition to improve diagnostic accuracy and patient care. Lack of dermatologists in many parts of the world and the high frequency of cutaneous disorders and malignancies highlight the increasing need for AI-aided diagnosis. Although AI-based applications for the identification of dermatological conditions are widely available, research assessing their reliability and accuracy is lacking. The aim of this study was to analyze the efficacy of the Aysa AI app as a preliminary diagnostic tool for various dermatological conditions in a semiurban town in India. This observational cross-sectional study included patients over the age of 2 years who visited the dermatology clinic. Images of lesions from individuals with various skin disorders were uploaded to the app after obtaining informed consent. The app was used to make a patient profile, identify lesion morphology, plot the location on a human model, and answer questions regarding duration and symptoms. The app presented eight differential diagnoses, which were compared with the clinical diagnosis. The model's performance was evaluated using sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1-score. Comparison of categorical variables was performed with the χ2 test and statistical significance was considered at P<.05. A total of 700 patients were part of the study. A wide variety of skin conditions were grouped into 12 categories. The AI model had a mean top-1 sensitivity of 71% (95% CI 61.5%-74.3%), top-3 sensitivity of 86.1% (95% CI 83.4%-88.6%), and all-8 sensitivity of 95.1% (95% CI 93.3%-96.6%). The top-1 sensitivities for diagnosis of skin infestations, disorders of keratinization, other inflammatory conditions, and bacterial infections were 85.7%, 85.7%, 82.7%, and 81.8%, respectively. In the case of photodermatoses and malignant tumors, the top-1 sensitivities were 33.3% and 10%, respectively. Each category had a strong correlation between the clinical diagnosis and the probable diagnoses (P<.001). The Aysa app showed promising results in identifying most dermatoses.