Turnaround Time For Results Research Articles

Understanding hospital antimicrobial prescribing decisions and determinants of uptake of new local antimicrobial prescribing guidelines in the Laos

Background Antimicrobial use in the Laos is among the highest in the Southeast Asia region. The first Lao comprehensive antimicrobial prescribing guidelines have been available since 2021. This study explored the determinants of antibiotic prescribing decisions and how the new prescribing guidelines were being used. Methods In August 2022, in-depth interviews were conducted with 16 Lao prescribers from two hospitals. Participants were questioned about their prescribing behaviours, attitudes to guidelines, how they learned about the guidelines and factors influencing their uptake. The interviews were audio-recorded, transcribed, and translated into English. Thematic analysis of the transcripts was conducted. Results Lao prescribers considered multiple factors before deciding to prescribe antibiotics to their patients. The most common factor was based on the clinical judgement of the prescribers. Lack of certain antibiotics and turnaround times of laboratory results were the main challenges to prescribing antibiotics appropriately. The majority of participants were satisfied with the guidelines, regarding them as comprehensive, simple and convenient. However, most participants admitted that they did not access the guidelines very often. The main reason was that they could remember the treatment recommendations because they treat similar diseases on a daily basis. Improving antibiotic knowledge was the most common recommendation in order to improve the appropriate use of antibiotics. Raising awareness of the guidelines and promoting their use should also be considered. In addition, heads of the wards, and policy and implementation leaders, should support, monitor and feedback their use to encourage all prescribers to follow the guidelines. Conclusions Several factors contribute to enhancing appropriate antibiotic prescription. Key factors for improving antibiotic prescription include enhancing prescribers' clinical knowledge, ensuring access to essential antibiotics, utilizing point-of-care diagnostics while waiting for culture and susceptibility testing results, and updating guidelines regularly. Health leaders must get involved to promote their use.

The Importance of Biomarker Testing in the Treatment of Advanced Non-Small Cell Lung Cancer: A Podcast.

The identification of actionable biomarkers and development of targeted therapies have revolutionized the field of lung cancer treatment. In patients with advanced non-small cell lung cancer (NSCLC), biomarker testing can inform selection of effective targeted therapies as well as avoid therapies that are less likely to be effective in certain populations. A growing number of actionable targets, including those involving EGFR, ALK, ROS1, BRAF, MET, KRAS, NTRK, RET, HER2, and PD-L1, can be identified with biomarker testing. More than half of patients with advanced NSCLC have tumors that harbor genetic alterations that can be targeted. When these patients are treated with targeted therapy, survival and quality of life may be significantly improved. In addition, broad-based molecular testing may detect alterations identifying patients who are potentially eligible for current or future clinical trials. Comprehensive biomarker testing rates in communities are often low, and turnaround times for results can be unacceptably long. There is an unmet need for widespread, efficient, and routine testing of all biomarkers recommended by clinical guidelines. New testing techniques and technologies can make this an attainable goal. Panel-based sequencing platforms are becoming more accessible, and molecular biomarker analysis of circulating tumor DNA is becoming more common. In this podcast, we discuss the importance of biomarker testing in advanced NSCLC and explore topics such as testing methodologies, effect of biomarker testing on patient outcomes, emerging technologies, and strategies for improving testing rates in the United States. Supplementary file1 (MP4 121301 KB).

Abstract 6474: Real-world assessment of turn-around time for actionable variant testing in NSCLC in the community setting

Abstract Introduction: Rapid turnaround times (TAT) is a key parameter when evaluating the performance of cell free (cf) nucleic acid testing in clinical oncology practice. The purpose of this study was to evaluate the impact of the real-world factors on TAT for actionable variants in NSCLC, detected using commercially available molecular diagnostic tests. These test services are run in a single, centralized laboratory site and utilized primarily by practices in the community across the United States. Methods: In this study, de-identified reference data was reviewed for a ddPCR test that evaluates hotspot mutations including Single Nucleotide Variants (SNV), Insertions and Deletions (INDEL), and gene fusions. The NGS panel additionally tests for Copy Number Amplification (CNA) mutations. Specimen processing was initiated when the specimen was entered into the Laboratory Information System (LIS) and ended when the test result was ready for release. The turnaround time evaluation excluded holidays, and weekends unless the start or end-point occurred on a non-business day. Results: In total, 35,441 specimen results were analyzed. Specimens were typically received in the laboratory within 24 hours of being shipped (88% in 24 hours). Tests by ddPCR included 30,490 (86%) results, while NGS testing accounted for 4,951 (14%) of results. The average analytic lab processing TAT for the ddPCR and NGS test ranged between 2 and 3 days (ddPCR median = 24.5 hours; NGS panel median = 69.7 hours). When no information was missing on the specimen test request form, the turn-around time for the ddPCR tests averaged 30.2 hours and NGS panel averaged 66.2 hours. The percentage of missing or inaccurate information was similar when test requests were initially received. The largest impact factor impacting initiation of specimen processing was information related annotation of the stage of cancer, followed by demographic information related to patient and specimen identifiers. Conclusion: The focus on rapid turnaround times from specimen collection to results released is critical in oncology. Site and patient information, shipping methods, technologies and workflows used in the laboratory are all part of the test process and impact the release of potentially actionable results. Our study has highlighted that rapid turnaround of results is highly feasible for molecular tests being sent out from community practices across the US to a centralized reference laboratory. Specifically, actionable variant results related to NSCLC were successfully detected in the laboratory and were ready for delivery in 2 to 3 days. Automated methods for parsing the information necessary for test requests and delivery will continue to be important in maintaining rapid test result turnaround times. Citation Format: Brittany D'Alessio, Adam Stephen, Colin Cochran, Cole Hager, Zachariah Velasco, Amanda Weaver, Leisa Jackson, Janice Riley, Alisa Tubbs, Gary A. Pestano. Real-world assessment of turn-around time for actionable variant testing in NSCLC in the community setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6474.

National Rapid Genome Sequencing in Neonatal Intensive Care

National implementation of rapid trio genome sequencing (rtGS) in a clinical acute setting is essential to ensure advanced and equitable care for ill neonates. To evaluate the feasibility, diagnostic efficacy, and clinical utility of rtGS in neonatal intensive care units (NICUs) throughout Israel. This prospective, public health care-based, multicenter cohort study was conducted from October 2021 to December 2022 with the Community Genetics Department of the Israeli Ministry of Health and all Israeli medical genetics institutes (n = 18) and NICUs (n = 25). Critically ill neonates suspected of having a genetic etiology were offered rtGS. All sequencing, analysis, and interpretation of data were performed in a central genomics center at Tel-Aviv Sourasky Medical Center. Rapid results were expected within 10 days. A secondary analysis report, issued within 60 days, focused mainly on cases with negative rapid results and actionable secondary findings. Pathogenic, likely pathogenic, and highly suspected variants of unknown significance (VUS) were reported. Diagnostic rate, including highly suspected disease-causing VUS, and turnaround time for rapid results. Clinical utility was assessed via questionnaires circulated to treating neonatologists. A total of 130 neonates across Israel (70 [54%] male; 60 [46%] female) met inclusion criteria and were recruited. Mean (SD) age at enrollment was 12 (13) days. Mean (SD) turnaround time for rapid report was 7 (3) days. Diagnostic efficacy was 50% (65 of 130) for disease-causing variants, 11% (14 of 130) for VUS suspected to be causative, and 1 novel gene candidate (1%). Disease-causing variants included 12 chromosomal and 52 monogenic disorders as well as 1 neonate with uniparental disomy. Overall, the response rate for clinical utility questionnaires was 82% (107 of 130). Among respondents, genomic testing led to a change in medical management for 24 neonates (22%). Results led to immediate precision medicine for 6 of 65 diagnosed infants (9%), an additional 2 (3%) received palliative care, and 2 (3%) were transferred to nursing homes. In this national cohort study, rtGS in critically ill neonates was feasible and diagnostically beneficial in a public health care setting. This study is a prerequisite for implementation of rtGS for ill neonates into routine care and may aid in design of similar studies in other public health care systems.

Pneumocystis jirovecii pneumonia: a case report

Introduction and importancePneumocystis jirovecii (PJP) pneumonia is a serious life-threatening condition in immunocompromised individuals and is often associated with human immunodeficiency virus (HIV) + patients. We describe a case of PJP pneumonia which provided a diagnostic challenge in a patient who presented with no known risk factors leading to a delay in initiation of appropriate antibiotic therapy.Case presentationA 71-year-old previously healthy white/Caucasian male presented with subacute hypoxic respiratory failure due to multifocal pneumonia with diffuse bilateral ground glass opacities with consolidations despite prior treatment with antibiotics and steroids. He was admitted and started on intravenous broad-spectrum antibiotics but continued to deteriorate, eventually requiring intubation and transfer to the ICU. Bronchoscopy revealed PJP and treatment was initiated, but the patient developed refractory shock and multiorgan failure, and ultimately died. It was later discovered that he was HIV-1 positive.Clinical discussionPJP, as a potential cause of his presentation, was not considered given that our patient lacked any overt risk factors for PJP pneumonia. He continued to worsen despite broad spectrum antibiotic therapy and hence bronchoscopy was pursued. His clinical profile, in hindsight, was suspicious for PJP pneumonia and early PJP-directed antibiotic therapy may have prevented a fatal outcome, as in this case. There was an element of cognitive bias across multiple providers which may have contributed to the delay in treatment despite his rapid clinical decline while on conventional pneumonia treatment protocol. His diagnosis was later evident when his BAL-DFA grew PJP in addition to his low levels of CD4 and CD8 cells. He was found to be HIV-1 positive five days after his death; there was a delay in this diagnosis since all positive HIV tests from the hospital are reported as ‘pending’ until the presumptive positive sample goes to the Connecticut Department of Public Health State laboratory for the confirmatory test. PJP-targeted therapies were initiated later in our patient’s hospital course when the infection had progressed to refractory septic shock with multiorgan failure and eventual death.ConclusionPJP pneumonia is a fatal disease if not recognized early in the course of illness, and the patient usually undergoes multiple antibiotic regimens before they are diagnosed and receive appropriate clinical care. The gold standard of diagnostic testing for PJP is by obtaining bronchial washings through a flexible bronchoscopy and the turnaround time for such results may take a few days to result. A significant proportion of patients may not have any overt risk factors of immunosuppression and early empiric treatment for PJP may be clinically appropriate as the delay in diagnosis may be associated with significant morbidity and mortality risk.

Differential Diagnosis in the Management of Acute Respiratory Infections through Point-of-Care Rapid Testing in a Post-Pandemic Scenario in Latin America: Special Focus on COVID-19, Influenza, and Respiratory Syncytial Virus

This review provides a comprehensive summary of evidence to explore the role and value of differential diagnosis in the management of Acute Respiratory Infections (ARIs) through point-of-care (POC) rapid testing in a post-pandemic scenario, paying particular attention to coronavirus disease 2019 (COVID-19), influenza, and respiratory syncytial virus (RSV). The document builds on a review of literature and policies and a process of validation and feedback by a group of seven experts from Latin America (LATAM). Evidence was collected to understand scientific and policy perspectives on the differential diagnosis of ARIs and POC rapid testing, with a focus on seven countries: Argentina, Brazil, Chile, Colombia, Costa Rica, Mexico, and Peru. The evidence indicates that POC rapid testing can serve to improve ARI case management, epidemiological surveillance, research and innovation, and evidence-based decision-making. With multiple types of rapid tests available for POC, decisions regarding which tests to use require the consideration of the testing purpose, available resources, and test characteristics regarding accuracy, accessibility, affordability, and results turnaround time. Based on the understanding of the current situation, this document provides a set of recommendations for the implementation of POC rapid testing in LATAM, supporting decision-making and guiding efforts by a broad range of stakeholders.

Cellular Mass Response to Therapy Correlates With Clinical Response for a Range of Malignancies.

Cancer patients with advanced-stage disease have poor prognosis, typically having limited options for efficacious treatment, and genomics-based therapy guidance continues to benefit only a fraction of patients. Next-generation ex vivo approaches, such as cell mass-based response testing (MRT), offer an alternative precision medicine approach for a broader population of patients with cancer, but validation of clinical feasibility and potential impact remain necessary. We evaluated the clinical feasibility and accuracy of using live-cell MRT to predict patient drug sensitivity. Using a unified measurement workflow with a 48-hour result turnaround time, samples were subjected to MRT after treatment with a panel of drugs in vitro. After completion of therapeutic course, clinical response data were correlated with MRT-based predictions of outcome. Specimens were collected from 104 patients with solid (n = 69) and hematologic (n = 35) malignancies, using tissue formats including needle biopsies, malignant fluids, bone marrow aspirates, and blood samples. Of the 81 (78%) specimens qualified for MRT, 41 (51%) patients receiving physician-selected therapies had treatments matched to MRT. MRT demonstrated high concordance with clinical responses with an odds ratio (OR) of 14.80 (P = .0003 [95% CI, 2.83 to 102.9]). This performance held for both solid and hematologic malignances with ORs of 20.67 (P = .0128 [95% CI, 1.45 to 1,375.57]) and 8.20 (P = .045 [95% CI, 0.77 to 133.56]), respectively. Overall, these results had a predictive accuracy of 80% (P = .0026 [95% CI, 65 to 91]). MRT showed highly significant correlation with clinical response to therapy. Routine clinical use is technically feasible and broadly applicable to a wide range of samples and malignancy types, supporting the need for future validation studies.

Novel Approach to Proficiency Testing Highlights Key Practice Variations in Cancer Biomarker Delivery

Biomarkers are fundamental to modern oncology practice, forming a close link to pathology practice. Pathology results must be accurate, timely, comprehensive, and comprehendible. External proficiency testing is a key tool in maintaining biomarker quality. Here, we demonstrate the feasibility and utility of a novel end-to-end proficiency testing exercise exploring accuracy, turnaround time, and communication. Challenge specimens were made using resected colon cancer tissue, each paired with a fictional clinical vignette, and distributed to participants who were asked to provide all molecular testing required and return a final report for each case upon completion. Reports were redistributed to an assessor team including medical oncologists, each of whom was asked to recommend a systemic therapy based on each lab’s biomarker report. Participants were graded based on their ability to guide oncologists to the correct treatment. Eight laboratories participated. Three laboratories were found to have suboptimal results, two leading oncologists to incorrect therapeutic prescriptions, and one withdrawn. Turnaround time ranged from 6 to 86 days (median 24). Substantial qualitative reporting differences were identified. This study demonstrates the feasibility of end-to-end proficiency testing. The approach provides considerable value beyond analytic accuracy, including specimen management, turnaround time, and communication of results. Results suggest that reporting differences may lead to treatment disparities. This style of quality assurance will help reinforce good practices critical to the delivery of precision cancer care.

Auto-detection of the coronavirus disease by using deep convolutional neural networks and X-ray photographs

The most widely used method for detecting Coronavirus Disease 2019 (COVID-19) is real-time polymerase chain reaction. However, this method has several drawbacks, including high cost, lengthy turnaround time for results, and the potential for false-negative results due to limited sensitivity. To address these issues, additional technologies such as computed tomography (CT) or X-rays have been employed for diagnosing the disease. Chest X-rays are more commonly used than CT scans due to the widespread availability of X-ray machines, lower ionizing radiation, and lower cost of equipment. COVID-19 presents certain radiological biomarkers that can be observed through chest X-rays, making it necessary for radiologists to manually search for these biomarkers. However, this process is time-consuming and prone to errors. Therefore, there is a critical need to develop an automated system for evaluating chest X-rays. Deep learning techniques can be employed to expedite this process. In this study, a deep learning-based method called Custom Convolutional Neural Network (Custom-CNN) is proposed for identifying COVID-19 infection in chest X-rays. The Custom-CNN model consists of eight weighted layers and utilizes strategies like dropout and batch normalization to enhance performance and reduce overfitting. The proposed approach achieved a classification accuracy of 98.19% and aims to accurately classify COVID-19, normal, and pneumonia samples.

Compliance with measures among actors and lessons learnt in the management of COVID-19 institutional quarantine in Uganda

IntroductionTo support COVID-19 containment measures, several countries implemented quarantine protocols. This study determined the level of compliance to COVID-19 quarantine measures, associated factors, and lessons learnt in institutional quarantine management in Uganda. MethodsThis concurrent mixed methods study involved a cross-sectional survey among individuals who were in institutional quarantine and interviews with key informants, who were reached mostly through phone calls. Univariate, bivariate, and multivariable analysis were conducted to analyse quantitative data while qualitative data were analysed thematically with the aid of Atlas ti 7. ResultsCompliance with quarantine measures at the individual level was moderate at 65.4 %. Factors associated with high compliance with measures were: older age (above 40 years) [APR = 1.30 (95 % CI: 1.04–1.63)], spending 14–15 days in quarantine [APR = 1.39 (95 % CI: 1.00–1.92)] and reporting a high Ministry of Health compliance [APR = 1.33 (CI: 1.11–1.58)]. The positive factors included the availability of guidelines, inspection of facilities and training of personnel. The challenges were related to long turnaround time for results and provision of personal protective equipment (PPE). ConclusionEfforts to improve training, supervision and inspection of facilities, and provision of adequate PPE would improve compliance with quarantine measures.

Feasibility for rapid on-site screening of pesticide residues in fresh produce using machine learning-assisted diffuse reflectance spectroscopy

Ensuring food safety by minimizing pesticide residues in crops is crucial to safeguarding human health. However, farmers often fail to follow the minimal time interval known as the Pre-Harvest Interval (PHI) between pesticide application and crop harvest. This lapse leads to high pesticide residue levels, often exceeding the recommended maximum residue levels (MRLs). Conventional methods for detecting pesticide residues are laboratory-based and rely on complex wet chemistry procedures. Although highly accurate, these techniques are destructive, expensive, and time-consuming. In addition, they take several hours before establishing results, making them unsuitable for analyzing large volumes of perishable fresh produce, particularly in resource-constrained settings. In this study, we investigated the feasibility of utilizing machine learning-assisted diffuse reflectance spectroscopy (DRS), a direct, rapid, and cost-effective approach for conducting an on-site preliminary assessment of pesticide residue levels in fresh produce, referred to as “screening.” This method facilitates the validation of fresh produce compliance with crop-specific PHI requirements after pesticide application, indicating adherence to MRLs. We used a portable Vis/NIR spectrometer to acquire DRS measurements from tamarillo fruits that had just been sprayed with mancozeb at the cultivation site. In total, 646 measurements were collected from treated and control (untreated) fruits over five alternating days, covering the duration between pesticide application and PHI lapse. We used spectral data pre-processing techniques and principal component analysis (PCA) to differentiate the fruits as the residue levels decreased, approaching the recommended PHI and demonstrating their suitability for harvesting. Furthermore, using two principal components that explained 88% of the total variance, we developed a support vector machine (SVM) classification model. The model successfully classified both the treated and control samples, as well as the samples based on their PHI status, distinguishing between ‘before PHI’ (days 1 - 7), ‘after PHI’ (day 9), and ‘Control’ (no residues), all with 100% accuracy. Given the quick turnaround time for results, typically within five minutes, we conclude that DRS combined with machine learning holds the potential for rapid and cost-effective on-site screening of large volumes of fresh produce in a market setting. This approach allows for the rapid identification of samples that require additional investigation in a food safety laboratory, thereby improving the efficient use of laboratory resources.

Staphylococcus epidermidis is a safer surrogate of Staphylococcus aureus in testing bacterial filtration efficiency of face masks

Face masks play a role in reducing the spread of airborne pathogens, providing that they have a good filtration performance, are correctly fitted and maintained. Bacterial Filtration Efficiency (BFE) is a key indicator for evaluating filtration performance according to both European and US standards, requiring the use of Staphylococcus aureus loaded aerosol. However, the generation and handling of a Biohazard group 2 bacterium aerosol require a careful management of the biological risk and pose limitations to the accessibility to this method. To mitigate these drawbacks, we investigated the use of S. epidermidis ATCC 12228, a Biohazard group 1 bacterium, as surrogate in BFE test. To this end, tests with the surrogate strain were performed to tune the method. Then, three face mask models, representative for both surgical and community masks, were tested according to the standard method and then using an aerosolized suspension of S. epidermidis. BFE% values were calculated for each mask model and tested microorganisms. Results showed that BFE test can be performed using the S. epidermidis instead of S. aureus, preserving results validity and turnaround time, but reducing residual risk for laboratory operators.

814. Impact of Testing Turnaround Times on Clinical Outcome in Hospitalized Patients with Histoplasmosis and Blastomycosis

Abstract Background Patients (pt) with histoplasmosis (histo) and blastomycosis (blasto) requiring hospitalization have unacceptably high mortality rates. In part, this is due to a delay in diagnosis. Serum (S) and urine (U) antigen (Ag) testing are often crucial for timely antifungal therapy. Clinical observations suggested delays in ordering samples to be sent to reference labs upon admission and prolonged turnaround time (TAT) for test results can lead to delays in starting therapy and poor outcomes. We sought to determine the impact of TAT for histo and blasto Ag testing on clinical outcomes of hospitalized patients (pt) at our institution. Methods Retrospective evaluation of all adult inpatients with histo or blasto diagnosed by positive U or S Ag tests from 1/1/15-12/31/22 was conducted. TAT from admission to result (TAT-AR) and from sample collection to result (TAT-CR) for the earliest positive test were calculated. Clinical data, including treatment & outcomes were collected. Only pt who received antifungal therapy or had a postmortem diagnosis were included. The relationship between TAT-AR and TAT-CR and outcome was evaluated. Results Of 39 pt (mean age 47±19 yr), 26 (67%) were men and 33 (85%) were immunocompromised: solid organ transplant recipients, 15; hematologic malignancy, 3; autoimmune/inflammatory disease on treatment, 12; others, 3. Thirty-five pt had pulmonary (8) or disseminated histo (27); 4 had disseminated blasto. Nine pt (23%) died within 4 months of diagnosis, including 8 pt with histo and 1 with blasto. Mean TAT-AR for these 9 deceased pt was 14.7± 19.5 days (d) vs 6.1±3.1 d for 30 survivors (p=.02). Mean TAT-CR for these 9 deceased pt was 5.4±1.5 d vs 3.9±1.3 d for 30 survivors (p=.003). Of the 32 pt who required IV amphotericin B (29) or died before any antifungal therapy was given (3), mean TAT-CR was 5.4±1.5 d for those who died vs 3.7±1.1 d for those who survived (p=.0013). ICU transfers, 30-d readmissions, and length of stay were not impacted by TAT-AR or TAT-CR. Conclusion Delays in TAT for initiating testing and obtaining results were associated with increased mortality of hospitalized pt with newly diagnosed histo or blasto. These findings highlight the importance of early testing and timely test results to guide treatment for hospitalized pt with these diseases. Disclosures Marisa H. Miceli, MD, Astellas: Advisor/Consultant|F2G: Grant/Research Support|Scynexis: Advisor/Consultant|Scynexis: Grant/Research Support

Evaluation of RapidChek® SELECT™ for the detection of Salmonella spp. in environmental samples from a veterinary hospital

Nosocomial salmonellosis in hospitalized animals is a recognized hazard, especially in large animal clinics. A standardized culture protocol (SCP) for detecting Salmonella spp. in environmental samples using a 48-h enrichment step results in a 5-day turnaround time for negative results. The RapidChek® SELECT™ Salmonella (RCSS) test system offers detection of organisms in 22–44 h through double enrichment followed by a lateral flow immunoassay. Negative results are reported within 48 h. To determine the most sensitive and rapid method for detecting Salmonella spp. from environmental samples collected at the large animal Purdue Veterinary Hospital (LA-PVH), a preliminary study compared the performance of RCSS and a SCP when testing artificially spiked and naturally contaminated samples. An expanded study analyzed results obtained using the RCSS method to test 872 environmental samples over a 12-month period. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry was chosen as the confirmation method for RCSS-presumptive positive samples. A randomly selected subset of samples received additional confirmation by real-time PCR. Here, we reported the performance data of RCSS in terms of sensitivity, specificity, and positive predictive value using MALDI-TOF results as reference for comparison. We also provide guidelines for reporting results obtained using this system.

A-135 Improving Cell Count Turnaround Times With the GloCyte® Automated Cell Counter for CSF: A Retrospective Study at MercyOne Des Moines Medical Center

Abstract Background Accurate, STAT cerebrospinal fluid (CSF) cell counts are critical in the diagnosis of meningitis, malignancy, demyelinating disease, and hemorrhage. Due to historical limitations with the linearity of automated analyzers, CSF cell counts have traditionally been performed manually with a hemocytometer and the aid of a brightfield optical microscope. Manual cell counting is time-consuming, subjective due to reliance on human interpretation, and requires a high degree of skill. This poses significant challenges for clinical laboratories of all sizes facing unprecedented med tech shortages. The purpose of this study was to evaluate the impact of implementing the GloCyte Automated Cell Counter for CSF, an FDA-cleared device with linearity down to 0 cells/µL, on result turnaround times. Methods Result turnaround time data for CSF specimens processed in the hematology lab at MercyOne Des Moines Medical Center, a 600-bed hospital in Des Moines, Iowa, was analyzed in a retrospective study of two cell counting methods- (1) manual cell counting using a Neubauer-Improved hemocytometer and (2) GloCyte, a benchtop cell counting device that uses fluorescence technology and highly specific reagents to automate RBC and TNC cell counts in less than 5 min. Turnaround times for 227 CSF specimens counted manually during an approximately six-month period prior to the implementation of GloCyte (January 2, 2017 to June 29, 2017) were compared to those for 133 specimens analyzed on GloCyte over a similar duration (January 4, 2021 to June 30, 2021). In this study, turnaround times were defined as the time between specimen arrival in the lab and result verification. Correlation between the methods was previously established in the MercyOne Des Moines Medical Center laboratory. Results The data demonstrated a significant, 16–30-minute improvement in turnaround times with GloCyte compared to the manual hemocytometer method. Median turnaround times, analyzed to adjust for add-ons that resulted in longer turnaround times pre- and post-GloCyte implementation, were 1:38h for specimens counted manually vs 1:08 h for specimens analyzed on GloCyte. The average turnaround time for the 227 CSF specimens counted manually was 2:03 h compared to 1:46 h for the 133 samples analyzed on GloCyte. The MercyOne Des Moines Medical Center laboratory processed 456 CSF cell counts in 2022, equating to a reduction in turnaround time of 122–228 h annually with the implementation of GloCyte. Conclusion This study demonstrates that GloCyte can be implemented to significantly improve turnaround times for CSF cell counts. The MercyOne Des Moines Medical Center laboratory realized several benefits from the reduction in turnaround times- GloCyte has (1) freed up significant tech time for other tasks, (2) standardized CSF cell counting to mitigate tech to tech variability, (3) increased lab staff satisfaction and decreased stress levels, and (3) increased physician satisfaction. For MercyOne Des Moines Medical Center’s sister site, MercyOne West Des Moines Medical Center, a 146-bed hospital that infrequently performs CSF cell counts, GloCyte has provided peace of mind in performing cell counts accurately with techs of all skill levels.

B-014 Impact of Centrifugation Time Reduction in Laboratory Automation System

Abstract Background The centrifugation of specimens is an important preanalytical process which will be impact the most on turnaround time of the laboratory results. To verify the automation systems, we tested different combinations of tube and centrifugation settings to determine the most efficient for routine chemistry procedure. The outcomes of each combination were then compared to the benchmark to find out the best setting to reduce turnaround time for laboratory results. Methods In this study, we evaluated a total of 40 leftover blood samples that were collected on 4 mL plastic Vacutainer® (Becton Dickinson) lithium heparin tubes and 2 mL plastic Vacuette® (Greiner bio-one) lithium heparin tubes. All tubes were centrifuged on Abbott Automation GLP systems. The first set of samples was centrifuged according to the manufacturer’s guideline (10 min at 1300 × g, room temperature for Vacutainer® tubes and 10 min at 2200 × g, room temperature for Vacuette® tubes). The second set was centrifuged 7 min at 2700 × g, room temperature. And the third set was centrifuged 5 min at 2700 × g, room temperature. Then, analyzed all samples with 22 routine chemistry parameters on Alinity ci analyzers. The allowable total error and correlation coefficient (R) were used to determine the significance of the differences between 3 protocols of the centrifugation time. Results The study showed that the centrifugation times of 7 min and 5 min were not significantly different from the manufacturer’s protocol (10 min) after testing with 22 routine chemistry parameters (albumin, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, direct bilirubin, total bilirubin, calcium, chloride, cholesterol, creatinine, low-density lipoprotein-cholesterol, iron, potassium, lactate dehydrogenase, sodium, phosphorus, total protein, triglycerides, unsaturated iron-binding capacity, high-density lipoprotein-cholesterol, urea nitrogen and uric acid) in both 4 mL plastic Vacutainer® lithium heparin tubes and 2 mL plastic Vacuette® lithium heparin tubes. Overall, the results of the study indicate that shorter centrifugation times of 7 min and 5 min at 2700 × g able to use for routine chemistry. Conclusion The study concluded that the centrifugation time did not affect the analytical results of 22 routine chemistry parameters. This suggests that shorter centrifugation times able to use with no impact on accuracy or reliability. The results of the study will support laboratory to have efficiency improvements by shorten the turnaround time on the results release.

Machine Learning Approach for Rapid, Accurate Point-of-Care Prediction of M-Spike Values in Multiple Myeloma.

The gold standard for monitoring response status in patients with multiple myeloma (MM) is serum and urine protein electrophoresis which quantify M-spike proteins; however, the turnaround time for results is 3-7 days which delays treatment decisions. We hypothesized that machine learning (ML) could integrate readily available clinical and laboratory data to rapidly and accurately predict patient M-spike values. A retrospective chart review was performed using the deidentified, electronic medical records of 171 patients with MM. Random forest (RF) analysis identified the weighted value of each independent variable (N = 43) integrated into the ML algorithm. Pearson and Spearman coefficients indicated that the ML-predicted M-spike values correlated highly with laboratory-measured serum protein electrophoresis values. Feature selected RF modeling revealed that only two variables-the first lagged M-spike and serum total protein-accurately predicted the M-spike. Taken together, our results demonstrate the feasibility and prognostic potential of ML tools that integrate electronic data to longitudinally monitor disease burden. ML tools support the seamless, secure exchange of patient information to expedite and personalize clinical decision making and overcome geographic, financial, and social barriers that currently limit the access of underserved populations to cancer care specialists so that the benefits of medical progress are not limited to selected groups.

High-Speed On-Site Deep Learning-Based FFR-CT Algorithm: Evaluation Using Invasive Angiography as the Reference Standard.

BACKGROUND. Estimation of fractional flow reserve from coronary CTA (FFR-CT) is an established method of assessing the hemodynamic significance of coronary lesions. However, clinical implementation has progressed slowly, partly because of off-site data transfer with long turnaround times for results. OBJECTIVE. The purpose of this study was to evaluate the diagnostic performance of FFR-CT computed on-site with a high-speed deep learning-based algorithm with invasive hemodynamic indexes as the reference standard. METHODS. This retrospective study included 59 patients (46 men, 13 women; mean age, 66.5 ± 10.2 years) who underwent coronary CTA (including calcium scoring) followed within 90 days by invasive angiography with invasive fractional flow reserve (FFR) and/or instantaneous wave-free ratio measurements from December 2014 to October 2021. Coronary artery lesions were considered to have hemodynamically significant stenosis in the presence of invasive FFR of 0.80 or less and/or instantaneous wave-free ratio of 0.89 or less. A single cardiologist evaluated the CTA images using an on-site deep learning-based semiautomated algorithm entailing a 3D computational flow dynamics model to determine FFR-CT for coronary artery lesions detected with invasive angiography. Time for FFR-CT analysis was recorded. FFR-CT analysis was repeated by the same cardiologist in 26 randomly selected examinations and by a different cardiologist in 45 randomly selected examinations. Diagnostic performance and agreement were assessed. RESULTS. A total of 74 lesions were identified with invasive angiography. FFR-CT and invasive FFR had strong correlation (r = 0.81) and, in Bland-Altman analysis, bias of 0.01 and 95% limits of agreement of -0.13 to 0.15. FFR-CT had AUC for hemodynamically significant stenosis of 0.975. At a cutoff of 0.80 or less, FFR-CT had 95.9% accuracy, 93.5% sensitivity, and 97.7% specificity. In 39 lesions with severe calcifications (≥ 400 Agatston units), FFR-CT had AUC of 0.991 and at a cutoff of 0.80, 94.7% sensitivity, 95.0% specificity, and 94.9% accuracy. Mean analysis time per patient was 7 minutes 54 seconds. Intraobserver agreement (intraclass correlation coefficient, 0.85; bias, -0.01; 95% limits of agreement, -0.12 and 0.10) and interobserver agreement (intraclass correlation coefficient, 0.94; bias, -0.01; 95% limits of agreement, -0.08 and 0.07) were good to excellent. CONCLUSION. A high-speed on-site deep learning-based FFR-CT algorithm had excellent diagnostic performance for hemodynamically significant stenosis with high reproducibility. CLINICAL IMPACT. The algorithm should facilitate implementation of FFR-CT technology into routine clinical practice.

Multiplexed Biosensing of Proteins and Virions with Disposable Plasmonic Assays.

Our growing ability to tailor healthcare to the needs of individuals has the potential to transform clinical treatment. However, the measurement of multiple biomarkers to inform clinical decisions requires rapid, effective, and affordable diagnostics. Chronic diseases and rapidly evolving pathogens in a larger population have also escalated the need for improved diagnostic capabilities. Current chemical diagnostics are often performed in centralized facilities and are still dependent on multiple steps, molecular labeling, and detailed analysis, causing the result turnaround time to be over hours and days. Rapid diagnostic kits based on lateral flow devices can return results quickly but are only capable of detecting a handful of pathogens or markers. Herein, we present the use of disposable plasmonics with chiroptical nanostructures as a platform for low-cost, label-free optical biosensing with multiplexing and without the need for flow systems often required in current optical biosensors. We showcase the detection of SARS-CoV-2 in complex media as well as an assay for the Norovirus and Zika virus as an early developmental milestone toward high-throughput, single-step diagnostic kits for differential diagnosis of multiple respiratory viruses and any other emerging diagnostic needs. Diagnostics based on this platform, which we term "disposable plasmonics assays," would be suitable for low-cost screening of multiple pathogens or biomarkers in a near-point-of-care setting.

Operationalising targeted next-generation sequencing for routine diagnosis of drug-resistant TB.

Phenotypic drug susceptibility testing (pDST) for Mycobacterium tuberculosis can take up to 8 weeks, while conventional molecular tests identify a limited set of resistance mutations. Targeted next-generation sequencing (tNGS) offers rapid results for predicting comprehensive drug resistance, and this study sought to explore its operational feasibility within a public health laboratory in Mumbai, India. Pulmonary samples from consenting patients testing Xpert MTB-positive were tested for drug resistance by conventional methods and using tNGS. Laboratory operational and logistical implementation experiences from study team members are shared below. Of the total number of patients tested, 70% (113/161) had no history of previous TB or treatment; however, 88.2% (n = 142) had rifampicin-resistant/multidrug-resistant TB (RR/MDR-TB). There was a high concordance between resistance predictions of tNGS and pDST for most drugs, with tNGS more accurately identifying resistance overall. tNGS was integrated and adapted into the laboratory workflow; however, batching samples caused significantly longer result turnaround time, fastest at 24 days. Manual DNA extraction caused inefficiencies; thus protocol optimisations were performed. Technical expertise was required for analysis of uncharacterised mutations and interpretation of report templates. tNGS cost per sample was US$230, while for pDST this was US$119. Implementation of tNGS is feasible in reference laboratories. It can rapidly identify drug resistance and should be considered as a potential alternative to pDST.