Need For Additional Testing Research Articles

Bridging Diagnostic Gaps: Utilising HiCrome Agar and Tetrazolium Reduction Medium for the Rapid and Presumptive Identification and Speciation of Candida Species in Vulvovaginal Candidiasis in Low-Resource Environments.

Background Vulvovaginal candidiasis (VVC) is a common fungal infection caused by an overgrowth of Candida species, primarily Candida albicans (C. albicans). Using HiCrome agar and tetrazolium reduction medium offers cost-effectiveness in Candida detection by eliminating the need for additional tests, reducing equipment costs compared to automated systems, and simplifying workflow with direct species identification while maintaining high specificity. They expedite detection by directly identifying Candida species based on colony colour, bypassing the multiple steps of phenotypic methods. This efficiency saves time in the laboratory, providing rapid results without the extended processing times associated with automated systems and facilitating prompt diagnosis and treatment decisions. These diagnostic tools are especially valuable in low-resource environments where a quick and accurate diagnosis of VVC is crucial for effective treatment and management of antifungal resistance. Aims and objectives This study aims to evaluate the efficacy of HiCrome agar and tetrazolium reduction medium's efficacy in speciating Candida species in VVC cases. Materials and methods A cross-sectional observational study was conducted at Saveetha Medical College and Hospitals, Chennai, India, over six months. High vaginal swabs from 126 patients suspected of VVC were collected and plated on Sabouraud dextrose agar (SDA), HiCrome Candida differential agar (Himedia, Mumbai, India), and tetrazolium reduction medium. The results were compared with those obtained from the VITEK2 compact system (bioMérieux, Marcy-l'Étoile, France). Results Of the 126 samples, 74.6% showed single yeast infections, 7.9% displayed mixed yeast infections, and 17.5% showed no growth. A total of 114 Candida isolates were identified. Both HiCrome agar and tetrazolium reduction medium accurately identified all isolates, with complete concordance with the VITEK2 compact system. The most commonly isolated species were C. albicans (55.2%), Candida tropicalis (32.4%), Candida glabrata (8.8%), and Candida parapsilosis (3.6%). Both media provided rapid and accurate presumptive identification in low-resource settings. Conclusions HiCrome agar and tetrazolium reduction medium demonstrated high sensitivity and specificity in identifying Candida species. These methods are reliable for rapid and accurate diagnosis, particularly in resource-limited settings. However, they may require supplementary tests for definitive species identification. The adoption of these diagnostic tools represents a significant advancement in clinical microbiology, improving VVC management and addressing antifungal resistance.

Increasing Risks to the Health of the Invertebrates-Balancing between Harm and Benefit.

The article discusses the issue of extensive use of detergents and sanitizers in the time of new challenges associated with the COVID-19 (SARS-CoV-2) pandemic. These agents could pose threats to the existence of free-living invertebrates as essential components of the ecosystem. The biological effects of the mentioned classes of substances, their metabolites, and combined effects in the mixture have not been studied enough. The main challenges in trying to balance the threats and benefits of using such substances are the lack of knowledge of the biological effects of these products, the gaps in testing invertebrates' responses, and changes in environment-related regulations to minimize risks to animals and humans. Numerous studies in this field still leave research gaps, particularly concerning the combined toxicity of well-known and widely used disinfectants, surfactants, and heavy metals, posing potential future challenges. Additionally, the review identified the need for additional testing of invertebrates for their sensitivity to disinfectants and surfactants of different compositions, including improved (non-invasive) methods, studies for early life stages, and comparative studies of species resilience.

Transthoracic echocardiographic Doppler metrics in evaluating bioprosthetic tricuspid valve dysfunction.

There is currently limited information on the utility of transthoracic echocardiography (TTE)-derived Doppler parameters for assessing bioprosthetic tricuspid valve (BTV) dysfunction. Our study aimed to establish the precision and appropriate reference ranges for routinely collected transthoracic Doppler parameters in the assessment of BTV dysfunction. We retrospectively evaluated 100 BTV patients who underwent TTE. Based on redo surgical confirmation or more than 2 repeat TTE or transesophageal echocardiography (TEE) examinations, patients were allocated to normal (n=61), regurgitant (n=24), or stenotic (n=15) BTV group. Univariate and multivariate binary logistic regression were performed to identify TTE Doppler parameters that detected BTV dysfunction. The VTI ratio (VTITV/VTILVOT) was the most accurate Doppler parameter for detecting BTV dysfunction, with a ratio of>2.8 showing 84.6% sensitivity and 90.2% specificity. VTI ratio>3.2, mean gradient (MGTV)>6.2mmHg and pressure half-time>218ms detected significant BTV stenosis, with sensitivities of 100%, 93.3% and 93.3% and specificities of 82.4%, 75.3% and 87.1%, respectively. After multivariate analysis, the VTI ratio>2.8 (OR=9.00, 95% CI=2.13-41.61, p=.003) and MGTV>5.1mmHg (OR=6.50, 95% CI=1.69-27.78, p=.008) were the independent associations of BTV dysfunction. With these cutoff values, 75.0%-92.2% of normal and 62.5%-96.0% of dysfunctional BTV were identified. Doppler parameters from TTE can accurately identify BTV dysfunction, particularly with VTI ratio>2.8 and MGTV>5.1mmHg, to assess the need for additional testing with TEE.

Novel Approach for Detecting Respiratory Syncytial Virus in Pediatric Patients Using Machine Learning Models Based on Patient-Reported Symptoms: Model Development and Validation Study.

Respiratory syncytial virus (RSV) affects children, causing serious infections, particularly in high-risk groups. Given the seasonality of RSV and the importance of rapid isolation of infected individuals, there is an urgent need for more efficient diagnostic methods to expedite this process. This study aimed to investigate the performance of a machine learning model that leverages the temporal diversity of symptom onset for detecting RSV infections and elucidate its discriminatory ability. The study was conducted in pediatric and emergency outpatient settings in Japan. We developed a detection model that remotely confirms RSV infection based on patient-reported symptom information obtained using a structured electronic template incorporating the differential points of skilled pediatricians. An extreme gradient boosting-based machine learning model was developed using the data of 4174 patients aged ≤24 months who underwent RSV rapid antigen testing. These patients visited either the pediatric or emergency department of Yokohama City Municipal Hospital between January 1, 2009, and December 31, 2015. The primary outcome was the diagnostic accuracy of the machine learning model for RSV infection, as determined by rapid antigen testing, measured using the area under the receiver operating characteristic curve. The clinical efficacy was evaluated by calculating the discriminative performance based on the number of days elapsed since the onset of the first symptom and exclusion rates based on thresholds of reasonable sensitivity and specificity. Our model demonstrated an area under the receiver operating characteristic curve of 0.811 (95% CI 0.784-0.833) with good calibration and 0.746 (95% CI 0.694-0.794) for patients within 3 days of onset. It accurately captured the temporal evolution of symptoms; based on adjusted thresholds equivalent to those of a rapid antigen test, our model predicted that 6.9% (95% CI 5.4%-8.5%) of patients in the entire cohort would be positive and 68.7% (95% CI 65.4%-71.9%) would be negative. Our model could eliminate the need for additional testing in approximately three-quarters of all patients. Our model may facilitate the immediate detection of RSV infection in outpatient settings and, potentially, in home environments. This approach could streamline the diagnostic process, reduce discomfort caused by invasive tests in children, and allow rapid implementation of appropriate treatments and isolation at home. The findings underscore the potential of machine learning in augmenting clinical decision-making in the early detection of RSV infection.

Online state of health estimation of lithium-ion batteries through subspace system identification methods

When Lithium-ion Batteries (LiBs) reach the end of their first life in electric vehicles (EVs), they can still be used in applications with lower power demands, a process known as second-life. However, to ensure that LiBs – or cells – removed from EVs operate safely, efficiently and reliably in a second application, several tests and procedures must be applied to study their internal conditions. Naturally, one of the most important parameters to be determined is the state of health (SoH). However, the available processes for determining the SoH of lithium-ion cells are limited by high costs, relatively long test times and the need for specific equipment, limiting the second-life market. Hence, this work proposes a methodology to estimate the SoH of lithium-ion cells, based on subspace system identification (SSI) methods, where the parameters estimated for the equivalent circuit model (ECM) of a given cell are associated with its SoH. To validate the proposed methodology, nine cell samples from the same manufacturer were considered, which were removed from heavy-duty EVs at the end of their first life. The obtained results showed that: (a) good approximations between the identified models and the actual cells were achieved, with root mean square error (RMSE) values as small as 1.32 mV; (b) SSI methods can be applied online, while the LiBs are still operating in the EV during their first life, eliminating the need of additional tests; and (c) there is a clear association between ECM parameters and the SoH, so it was possible to estimate the SoH of the samples with RMSE values varying from 2.11% to 3.34%. Therefore, the proposed methodology offers significant improvements when compared to the conventional capacity tests, including the possibility of estimating the SoH relatively fast, online and without the need for specific equipment.

Stochastic modelling of out-of-autoclave epoxy composite cure cycles under uncertainty

Thermoset polymers and composites are subject to several sources of uncertainty which can produce a range of cure outcomes. Recent research into stochastically modelled thermoset cure has indicated that accounting for raw material and process uncertainty can model this range of expected output parameters. However, the uncertainty quantification methods are highly test-intensive, and the results of the simulations have been validated with limited experimental data. This study proposes a simple approach to cure kinetics uncertainty quantification that can be applied to any cure kinetics model without the need for additional testing. Stochastic cure kinetics and temperature conditions for a popular out-of-autoclave carbon fibre/epoxy prepreg were used to produce output distribution functions for key cure events, and the results were validated using data from ten cure replicates. The quantified variation expected from the cure of this prepreg resulted in processing recommendations to ensure quality metrics are met during processing.

Feasibility of diagnosing osteoporosis using routine computed tomography scans for hip fractures: Correlation with histopathological diagnosis of head and neck regions.

The aim of this study was to demonstrate the feasibility of diagnosing osteoporosis through routine computed tomography (CT) by assessing the association between the histopathological assessment of femoral head specimens extracted from patients who underwent surgery for intertrochanteric fractures and the Hounsfield unit (HU) measurements derived from preoperative CT scans. Forty-eight patients who presented to our clinic between November 2019 and May 2020 with hip fractures and underwent partial prosthesis fixation were included in this retrospective study. Hounsfield unit measurements were performed on the head and neck regions using dual-energy x-ray absorptiometry (DEXA) and CT scans, respectively. The trabecular ratio per unit area was calculated using the Nikon Imaging Software (NIS-Elements ) program in the pathology laboratory from digitally captured images of the removed head and neck specimens. The mean HU receiver operating characteristic analysis had a sensitivity of 77% and a specificity of 87%, with a cutoff value of 77.68. There was a moderate correlation between the mean trabecular density and the mean HU of the femoral head (P=0.013, r=0.340). Additionally, there was a significant correlation between the mean HU and the T-score of the head, although this correlation was not found with the maximum-minimum HU. Although there was a significant correlation between trabecular density and mean HU, the correlation coefficient indicated a moderate relationship. This relationship was also observed between the inferior sections of the head and the trabecular density and HU (P=.018). However, no significant correlation was found between the T-score and the trabecular structure of the head (P=.977). The results of the present study suggest that conventional CT has the potential to serve as a diagnostic tool for osteoporosis and may offer a more precise and accurate method for evaluating the success of intraosseous implants when compared to T-scores without the need for additional tests or procedures.

Cardiovascular imaging research and innovation in 2023.

In 2023, cardiovascular imaging has made significant advancements, in terms of technology, pathophysiology, and clinical application. In this review, the most recent research findings in the field of cardiovascular imaging are discussed. Artificial intelligence and large population cohorts, together with several technical improvements, have had a crucial impact on the technological advancements of echocardiography, cardiovascular magnetic resonance, computed tomography (CT), and nuclear medicine. In the field of ischaemic heart disease, it has been demonstrated that appropriate non-invasive imaging strategies improve patients' management and reduce invasive procedures and the need for additional testing at follow-up. Moreover, improvements in plaque characterization with CT are an expanding field of research with relevant implications for the prediction of disease severity, evolution, and response to treatment. In the field of valvular heart disease, imaging techniques have advanced alongside improvements in transcatheter treatment for aortic stenosis, mitral, and tricuspid regurgitation. Finally, in the field of heart failure and cardiomyopathies, cardiovascular imaging has reinforced its crucial role in early diagnosis and risk evaluation, showcasing advanced techniques that outperform traditional methods in predicting adverse outcomes.

Advances in Non-Invasive Neuromodulation: Designing Closed-Loop Devices for Respiratory-Controlled Transcutaneous Vagus Nerve Stimulation.

Studies suggest non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) as a potential therapeutic option for various pathological conditions, such as epilepsy and depression. Exhalation-controlled taVNS, which synchronizes stimulation with internal body rhythms, holds promise for enhanced neuromodulation, but there is no closed-loop system in the literature capable of performing such integration in real time. In this context, the objective was to develop real-time signal processing techniques and an integrated closed-loop device with sensors to acquire physiological data. After a conditioning stage, the signal is processed and delivers synchronized electrical stimulation during the patient's expiratory phase. Additional modules were designed for processing, software-controlled selectors, remote and autonomous operation, improved analysis, and graphical visualization. The signal processing method effectively extracted respiratory cycles and successfully attenuated signal noise. Heart rate variability was assessed in real time, using linear statistical evaluation. The prototype feedback stimulator device was physically constructed. Respiratory peak detection achieved an accuracy of 90%, and the real-time processing resulted in a small delay of up to 150 ms in the detection of the expiratory phase. Thus, preliminary results show promising accuracy, indicating the need for additional tests to optimize real-time processing and the application of the prototype in clinical studies.

Validation of an Automated, Scalable Comprehensive Genomic Profiling Assay for Hematologic Malignancies

Introduction: The optimal diagnosis, prognosis, and treatment selection for hematologic disorders requires the assessment of somatic mutations across a subset of clinically relevant genes. Here we present the clinical validation results of a targeted next generation sequencing panel comprising all exons of 141 clinically relevant genes for myeloid and lymphoid malignancies. Methods: The panel was designed to include genes (n=141) based of clinical guidelines for myeloid diseases including acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPN), and lymphoid diseases including acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), and some lymphoma subtypes. The panel was validated to detect single nucleotide variants (SNVs), insertions/deletions (indels), FLT3 internal tandem duplications ( FLT3-ITDs), and sex. Gene level copy number alterations (CNAs) were validated for 11 genes and 5 sub-gene level CNAs in IKZF1, KMT2A, RUNX1, TET2, and TP53, and were selected based on clinical utility and frequency observed in a population of >10,000 microarray samples with confirmed myeloid or lymphoid indications. Custom hybridization probes (Twist Biosciences) were designed to interrogate all coding exons of the 141 genes using genomic libraries created from 250 ng of gDNA extracted from peripheral blood, bone marrow, or flow cytometry cell suspensions, followed by hybrid capture, and sequencing on Illumina DNA sequencers. Data analysis was performed using an in-house analysis pipeline to detect variants and perform rational filtering of technical artifacts. Validation studies were performed in a CAP/CLIA accredited clinical laboratory. Precision and concordance studies were performed using previously characterized clinical samples. SNVs, indels and FLT3-ITDs were orthogonally confirmed by an NGS-based laboratory developed test (ArcherDx) or by Sanger sequencing. CNAs were confirmed by digital multiplexed ligation-dependent probe amplification (dMLPA; MRC Holland). Results: Assay precision was determined using 15 previously characterized clinical samples with 36 SNVs with a variant allele frequency (VAF) range of 5.7-91.4%, 11 indels with a VAF range of 6.2-79.7%, one 24bp FLT3-ITD with a VAF of 30.2%, 17 deletions with a copy number (CN) range of 0.53-0.83, and 7 gains with CN range of 1.32-1.66. Three replicates of each sample were assessed for precision with 100% concordance observed for SNVs (36/36), indels (11/11), FLT3-ITD (1/1), CNAs (24/24), and gender (15/15). Inter-assay precision was assessed using multiple operators, instruments, reagent lots, and sample barcodes with the clinical samples. Interim analysis of concordance performed on 130 clinical samples demonstrated a positive percent agreement (PPA) of 99.7% for SNVs (334/335 in 114 clinical samples), 97.7% for indels (146/151 in 85 clinical samples), 98.7% for CNAs (30/30 in 17 clinical samples), and 96.7% for sex (127/130 in 130 clinical samples). Dilution series of both cell lines and clinical samples that will be used to determine analytical sensitivity are underway. Conclusions: This study highlights the clinical validation of a 141 gene NGS assay for the detection of clinically informative genomic alterations in hematologic malignancies. The detection of CNAs by NGS may be used to additionally confirm or monitor abnormalities previously detected by cytogenetics/microarray or inform the need for additional testing. Results from this validation study, when complete, will include at least 480 samples plus orthogonal testing. These data describe the performance of an assay to enable a comprehensive evaluation of genomic alterations using a single sample, further facilitating the use of broad NGS assays in hematologic malignancies.

Dynamic CT Myocardial Perfusion: The Role of Functional Evaluation in the Diagnosis of Coronary Artery Disease.

Coronary computed tomography angiography (CTA) is a widely accepted, non-invasive diagnostic modality for the evaluation of patients with suspected coronary artery disease (CAD). However, a limitation of CTA is its inability to provide information on the hemodynamic significance of the coronary lesion. The recently developed stress dynamic CT perfusion technique has emerged as a potential solution to this diagnostic challenge. Dynamic CT myocardial perfusion provides information on the hemodynamic consequences of coronary stenosis and is used to detect myocardial ischemia. The combination of stress dynamic CT myocardial perfusion with CTA provides a comprehensive assessment that integrates anatomical and functional information. CT myocardial perfusion has been validated in several clinical studies and has shown comparable accuracy to Positron Emission Tomography (PET) and stress magnetic resonance imaging (MRI) in the diagnosis of hemodynamically significant coronary stenosis and superior performance to Single Photon Emission Computed Tomography (SPECT). More importantly, CTP-derived myocardial perfusion has been shown to have a strong correlation with FFR, and the use of CTP results in a reduction of negative catheterizations. In the context of suspected stable coronary artery disease, the CT protocol with dynamic perfusion imaging combined with CTA eliminates the need for additional testing, making it a convenient "one-stop-shop" method and an effective gatekeeper to an invasive approach.

Thoracic-Worn Accelerometers Detect Fatigue-Related Changes in Vertical Stiffness During Sprinting.

Horsley, BJ, Tofari, PJ, Halson, SL, Kemp, JG, Johnston, RD, and Cormack, SJ. Thoracic-worn accelerometers detect fatigue-related changes in vertical stiffness during sprinting. J Strength Cond Res 38(2): 283-289, 2024-Thoracic-mounted accelerometers are valid and reliable for analyzing gait characteristics and may provide the opportunity to assess running-related neuromuscular fatigue (NMF) during training and competition without the need for additional tests, such as a countermovement jump (CMJ). However, their sensitivity for detecting fatigue-related changes in gait across different speeds is unclear. We, therefore, assessed the changes in accelerometer-derived gait characteristics, including vertical stiffness (K vert ), following a repeated sprint protocol (RSP). Sixteen recreationally active subjects performed single and repeated CMJs on a force plate and 40 m run throughs overground at 3-4, 5-6, and 7-8 m·s -1 pre-post a 12 × 40 m RSP. Gait characteristics (contact time, step frequency, step length, K vert , etc.) were derived from an accelerometer contained within a global navigation satellite system unit on the thoracic spine using a validated algorithm. Changes in running gait and CMJ performance were assessed using a linear mixed-effects model (95% confidence interval [95% CI]; effect size [ES]). Significance was set at p < 0.05. A significant reduction in K vert occurred at 7-8 m·s -1 following the RSP (-8.51 kN·m -1 [-13.9, -3.11]; p = 0.007; ES [95% CI] = -0.39 [-0.62, -0.15]) which coincided with a decreased jump height (-0.03 m [-0.04, -0.01]; p = 0.002; ES [95% CI] = -0.87 [-1.41, -0.30]). However, all other gait characteristics were not significantly different irrespective of speed. Thoracic-worn accelerometers can detect changes in K vert at 7-8 m·s -1 which may be useful for monitoring NMF during sprinting. However, a RSP does not result in altered gait mechanics in subsequent running at lower speeds.

Прогнозирование значений предела прочности при растяжении и модуля упругости композитной арматуры большого диаметра по косвенным признакам

Purpose: To consider the problems of experimental determination of elastic and strength properties of largediameter composite polymer glass fiber reinforced plastic rebar (FRP-rebar). To analyze the state of the issue, to make an overview of existing methods for determining elastic and strength properties of FRP-rebar. To show the necessity of developing methods of predicting the large-diameter FBR-rebar elastic and strength properties by means of indirect measurement methods. To carry out a series of tensile tests of FRP-rebar and to calculate the elastic-strength characteristics values using the rule of mixtures for composite materials. To make a comparative study of data obtained by experimental and analytical methods. Methods: Comparative analysis of the FRP-rebar elastic-strength characteristics calculated values with experimental data. Results: The need to improve the existing regulatory method for determining the elastic-strength characteristics of composite reinforcement bars is indicated. Calculation formulas of analytical prediction of the ultimate tensile strength and elastic modulus of FRP-rebar have been established. The calculated values obtained have been verified. The need of additional tests to build a statistical database has been identified. Practical significance: The proposed method for indirect measurement of FBR-rebar properties can be recommended for further experimental testing to reduce the risk of obtaining error values of elastic and strength characteristics of largediameter FRP-rebar when conducting direct experiments.

Urinary Incontinence: evidence on conservative management

Urinary incontinence in women is a condition of high incidence and is associated with an impact on quality of life. Conservative treatment modalities are an important resource in the management of this condition, since they can be prescribed based on the clinical diagnosis without the need for additional tests. The present study aims to gather current evidence on conservative treatment modalities available for female incontinence published in the last 5 years. Conducting the search in the Medline and LILACS databases, 28 articles were identified, categorized with level of evidence 1b and 2b by the Oxford classification, which present original results on physical therapy, medication and behavioral modalities in the non-community treatment of female incontinence. The current state of the art demonstrates a domain of studies with a high degree of evidence involving the treatment modalities associated with the physical therapy practice of pelvic floor muscle training. Evidence from 5 analyzed studies statistically demonstrated the superiority of this method in relation to control groups, or to groups submitted to other interventions. Positive evidence related to transcutaneous electrical stimulation therapies, intravaginal electrical stimulation, duloxetine, noradrenaline receptor inhibitors, continence pessaries, and lifestyle changes was also observed.

Evidence-based guideline: unexplained infertility†.

Evidence-based guideline: unexplained infertility†.

Guidance document on the impact of water treatment processes on residues of active substances or their metabolites in water abstracted for the production of drinking water.

This guidance document provides a tiered framework for risk assessors and facilitates risk managers in making decisions concerning the approval of active substances (AS) that are chemicals in plant protection products (PPPs) and biocidal products, and authorisation of the products. Based on the approaches presented in this document, a conclusion can be drawn on the impact of water treatment processes on residues of the AS or its metabolites in surface water and/or groundwater abstracted for the production of drinking water, i.e. the formation of transformation products (TPs). This guidance enables the identification of actual public health concerns from exposure to harmful compounds generated during the processing of water for the production of drinking water, and it focuses on water treatment methods commonly used in the European Union (EU). The tiered framework determines whether residues from PPP use or residues from biocidal product use can be present in water at water abstraction locations. Approaches, including experimental methods, are described that can be used to assess whether harmful TPs may form during water treatment and, if so, how to assess the impact of exposure to these water treatment TPs (tTPs) and other residues including environmental TPs (eTPs) on human and domesticated animal health through the consumption of TPs via drinking water. The types of studies or information that would be required are described while avoiding vertebrate testing as much as possible. The framework integrates the use of weight-of-evidence and, when possible alternative (new approach) methods to avoid as far as possible the need for additional testing.

Return to Performance Protocols and Criteria Specific to Aerobic Capacity for Aerobic Athletes Who Sustain Lower Extremity Injuries: A Narrative Review

ABSTRACT Return to performance (RTP) protocols vary greatly between sports due to energy system involvement, physical and biomechanical skills, injury type and severity, and varied recommendations from members of the interprofessional care team. Return decisions are guided by clinical reasoning, expert opinion, experience, and sport-specific frameworks. Lower extremity injuries that prevent athletes from continuous aerobic training lead to decreased aerobic capacity upon return, which is linked to increased risk of injury or reinjury. This narrative review compares documented rehabilitation programs and RTP protocols and criteria specific to aerobic capacity for athletes who sustain lower extremity injuries in highly aerobic sports. Databases were searched from 2010 to 2022, yielding 9 primary articles and 11 review articles. No RTP protocol specific to aerobic capacity was identified. Considering the lack of evidence regarding aerobic capacity testing and prescription in RTP protocols, research is necessary to determine the significance of aerobic capacity recommended for RTP. Strength and conditioning coaches should be aware of the decreased aerobic capacity at the time of return, thus the need for additional testing, and implement individualized aerobic conditioning programs to optimize return. .

Anecdotes Drive Attitudes, Data Drives Decisions: Optimizing the Emergency Department Workup Prior to Surgical Consultations

Emergency department (ED) wait times and ED length of stay (LOS) have a significant impact on patient morbidity and mortality and patient satisfaction. Consultation-to-decision time can contribute to increased wait times and LOS in the ED. Up to 40% of patients presenting to the ED require consultation from subspecialty services. We hypothesize that in surgical patients, completion of workup prior to consultation will decrease consultation-to-decision time, ED wait times, and LOS in the ED. A retrospective review was conducted at a single site including all overnight general surgery consultations from the ED over 2-months. Data collected included wait times, LOS, and workup completed prior to consultation. Summary statistics were calculated and bivariate tests were performed using t-tests for continuous variables. Time to final surgical plan and LOS in ED were evaluated for 137 patients comparing "complete" and "incomplete" workups at time of consultation. It was considered a "complete" workup if labs and imaging were resulted prior to time of consult. If any baseline tests were not ordered prior to time of consult, it was considered an "incomplete" workup. Analysis demonstrated an average time of 4.9 and 2.5 hours for consultation-to-decision time for "incomplete" and "complete" workups respectively (p < 0.0001). For LOS in ED, there was an average of 11.4 and 7.9 hours for "incomplete" and "complete" workups respectively (p < 0.0001). There is a significant difference in consultation-to-decision time and LOS in the ED when consultation is performed following a complete versus incomplete workup for surgical patients independent of inherent wait times for testing to result and the need for additional testing requested from consulting services. Developing strategies to optimize workups from the ED prior to surgical consultation, including the development of care pathways, could significantly decrease patient wait times and LOS in the ED.

P-279 Comparison of AI model performance in predicting blastulation in old and young mice groups

Abstract Study question Is there a difference in AI performance in predicting blastulation between young and old mice? Summary answer AI performance in predicting blastulation is higher in young mice than in old mice. What is known already Previous studies have demonstrated AI's ability to predict oocyte development using oocyte or embryo images, but there has been no study to determine if AI performance varies with the age of the female. Maternal age influences oocyte quality and development, but other factors such as diet and environment also play a role. Using mouse experiments can minimize these confounding factors. The study aims to determine if there is a difference in AI performance for predicting blastulation using oocyte images from old and young mice. Study design, size, duration We collected oocyte images from 673 B6D2F1 (BDF1) mice at a single research center between July 2022 and January 2023. The samples were separated into two groups based on maternal age, 386 from young mice and 287 from old mice. The development stages including fertilization and blastulation were recorded through daily observation, and the data was divided into a training set of 3 batches and a test set of 2 batches. Participants/materials, setting, methods The mice were divided into two groups: young mice (7-9 weeks old) and old mice (62-68 weeks old). The study used images of MII oocytes collected after superovulation, taken with a 200x inverted microscope, and cultured in a single drop. A CNN was trained to predict blastulation and compared for accuracy between the young and old mouse groups. Blastulation was determined by observing the presence of expanded blastocysts or above on day 4. Main results and the role of chance The study used 203 and 182 oocyte images of young and old mice respectively for training, and 183 and 105 images for testing. Three convolutional neural network models (VGG16, ResNet50, and DenseNet121) were used to predict blastulation, and ResNet50 was selected as the final model. Without considering age, the accuracy, sensitivity, and specificity of the AI for predicting blastulation were 0.75, 0.74, and 0.76, respectively. The AI model used in the study had accuracy of 0.77, sensitivity of 0.75, and specificity of 0.79 in the young mice group. In the old mice group, the model had accuracy of 0.72, sensitivity of 0.70, and specificity of 0.74. When a t-test was performed, there was a statistically significant difference in accuracy (p = 0.014) with better accuracy in young mice. On the contrary, the sensitivity in the old mice group was the lowest, making it difficult to predict blastulation. As oocyte morphology does not always represent aneuploidy, the AI model using oocyte images may not perform well in the old mice group due to increased aneuploidy. Limitations, reasons for caution The limitations of this study include its retrospective design using oocyte images from only one research center. A larger, multicenter study would be beneficial. Wider implications of the findings The study found that AI accurately predicted blastulation using mice oocyte images, with higher accuracy for both positive and negative outcomes in young mice. However, accuracy was lower in old mice, particularly for positive outcome, suggesting the need for additional tests like genetic testing for predicting blastulation in old mice. Trial registration number not applicable

Hemoglobin A1c as a Substitute for Oral Glucose Testing in Early Pregnancy Screening.

Current recommendations for individuals with risk factors for gestational diabetes mellitus (GDM) call for screening in early pregnancy. However, there is currently no clear consensus on a specific screening modality. This study evaluates whether a hemoglobin A1c (HbA1c) screening in individuals with risk factors for gestational diabetes (GDM) could be used instead of an early 1-hour glucose challenge test (GCT). We hypothesized that the HbA1c could replace 1-hour GCT in early pregnancy evaluation STUDY DESIGN: This is a prospective observational trial at a single tertiary referral center of women with at least one risk factor for GDM who were screened at <16 weeks of gestation with both 1-hour GCT or HbA1c. Exclusion criteria include: previous diagnosis of diabetes mellitus, multiple gestation, miscarriage, or missing delivery information. The diagnosis of GDM was made by a 3-hour 100-g glucose tolerance test, using the Carpenter-Coustan criteria (at least two results >94, 179, 154, and 139 mg/dL for fasting, 1-, 2-, and 3-hour values, respectively), 1-hour GCT > 200 mg/dL, or HbA1c > 6.5%. A total of 758 patients met inclusion criteria. A total of 566 completed a 1-hour GCT and 729 had an HbA1c collected. The median gestational age at testing was 91/7 weeks (range: 40/7-156/7 weeks]. Twenty-one participants were diagnosed with GDM at <16 weeks' GA. The receiver operating characteristic (ROC) curves identified the optimal valves for a positive screen for an HbA1c > 5.6%. The HbA1c had a sensitivity of 84.2%, a specificity of 83.3%, and a false positive rate of 16.7% (p < 0.001). The area under the ROC curve for the HbA1c was 0.898. Gestational age of delivery was slightly earlier with individuals with an elevated HbA1c but no other changes in delivery or neonatal outcomes. Contingent screening improved specificity (97.7%) and decreased false positive rate to 4.4%. HbA1c may be a good assessment in early pregnancy for gestational diabetes. · HbA1c is a rational assessment in early pregnancy.. · An HbA1c > 5.6% is associated with gestational diabetes.. · Contingent screening limits the need for additional testing..