Routine Diagnostic Methods Research Articles

Application of 3D printing in bacterial detection

Diseases caused by bacterial infections, especially pathogen variations and drug-resistant bacteria, are a serious threat to human health globally. Accurate and rapid identification of bacterial pathogens is essential for early diagnosis of infections and timely treatment of disease. At present, the routine diagnostic methods for identifying bacterial pathogens in clinic are bacterial culture, immunological detection, genetic analysis, etc. These methods occupy foundational position for bacterial detection that favors for clinical diagnosis of pathogen infection in daily life. Notably, 3D printing technology, together with 3D bioprinting technology, provides more options for bacterial detection due to its personalized design and manufacturing. Compared with traditional methods, 3D printing provides a more convenient, rapid and accurate bacterial detection platform, thus meeting the urgent needs of clinical and scientific research. Here, we have summarized the research progress and given a comprehensive review of 3D printing technology in bacterial detection, including bacterial detection sensors, microfluidic chips, bioprinting microarray technology, AI and spectroscopy technology, providing a scientific reference and filling in gaps in 3D printing-assistance bacterial detection. At the same time, technical advantages, challenges and future development trends will also be discussed in related healthcare fields.

Evaluation of the diagnostic techniques in the detection of hookworm infestation among school children in Ethiopia: Cross-sectional study design

BackgroundHookworm infestation is an important public health concern especially in regions with poor sanitation and limited resources. In healthcare institutions in Ethiopia, wet mount microscopy with low performance has been used as the sole diagnostic technique. Sensitive diagnostic methods are essential for the proper identification of hookworm infection in national strategies for hookworm prevention and management. Thus, the objective of the article was to evaluate the performance of diagnostic techniques in the detection of hookworm infestation among school children in the Gozamin district, Northwest Ethiopia. MethodsA cross-sectional study with 530 school children was conducted from February to April 2022 in Ethiopia. The study participants were selected by using systematic random sampling technique. Direct wet mount (DWM), Richie’s, Kato-Katz (KK), and spontaneous tube sedimentation (STS) diagnostic techniques were utilized to process the stool samples. The data were entered into the Epi-data version 4.2 and the data was analyzed using SPSS version 25.0. The sensitivity, specificity, predictive values and test efficiency of the test were calculated with respect to the Composite Reference Standard (CRS) as the reference method. The degree of agreement with the methods of diagnosis was assessed by the Kappa value. ResultsThe overall prevalence of hookworm was 34.9 %. The detection rate of STS, Richie’s, KK and DWM techniques in hookworm detection was 30.2 %, 27.0 %, 22.3 % and 15.1 %, respectively. The sensitivity and test efficiency of STS to detect hookworm were 86.5 % and 95.3 %, for Richie’s 77.3 % and 92.1 %, for KK 63.8 % and 87.4 %, for DWM method 43.2 % and 80.2 %, respectively. The agreement of STS, Richie’s, KK and DWM techniques with CRS were perfect (κ = 0.893), perfect (κ = 0.816), substantial (κ = 0.696) and moderate (κ = 0.498), respectively in detecting hookworm parasites. ConclusionThe prevalence of hookworm among school children was high. The STS method is superior to other methods for detecting hookworm infections. The Richie’s technique was more successful in detecting the hookworm parasite than the KK and DWM techniques. It is important to implement the STS technique in routine diagnostic methods and in endemic areas of hookworm infection because it cheaper, easy to perform, and identifies a wide range of parasitic species.

Identification methods as a factor affecting the performance of clinical microbiology laboratories participating in an external quality assessment program: a cross-sectional, retrospective analysis.

Introduction. Laboratory participation in external quality assessment (EQA) programmes including proficiency testing (PT) is a requirement of clinical laboratory conformance to ISO 15189:2022 Medical laboratories - Requirements for quality and competence. PT is one EQA method whereby laboratories are sent blinded samples for characterization by routine laboratory diagnostic methods. Importantly, PT enables a laboratory's performance to be evaluated in comparison to the standard reference methods and to the performance of other peer laboratories using similar diagnostic methods.Gap statement. The desired outcome of participating in PT is to help laboratories identify possible sources of error in each step of the total testing process and particularly in their test methods during the analytical phase.Aim. This cross-sectional study investigated the impact of using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) compared to conventional phenotypic biochemical testing on laboratory performance in a clinical bacteriology PT scheme.Methodology. During a 6-year period from 2017-2022, the Canadian Microbiology Proficiency Testing implemented 112 PT challenges comprising 22 different sample types and included 61 different bacterial species. This was translated into 5883 graded test events for analysis. Multiple logistic regression techniques were employed to explore the association between the test method employed and laboratory performance. The sample type and aerobic classification of challenge organisms were included as confounding variables.Results. Laboratories using MALDI-TOF MS performed significantly better in characterizing microorganisms than laboratories using phenotypic biochemical testing alone [odds ratio OR = 5.68, confidence interval (CI): 3.92, 8.22] regardless of the sample type and aerobic classification. Notably, our analysis identified a significant association between anaerobic organisms and laboratory performance (OR: 0.24, CI: 0.17-0.35), suggesting that culturing and identifying fastidious organisms remains a significant obstacle for many clinical microbiology laboratories.Conclusions. Although no method is infallible and its performance will depend on the validation and quality assurance procedures, this finding may help the management in the decision for implementing MALDI-TOF MS in the microbiology laboratory. This study highlights the important role PT providers play in the objective assessment of laboratory performance and how it can provide evidence for quality improvement.

CystNet: An AI driven model for PCOS detection using multilevel thresholding of ultrasound images

Polycystic Ovary Syndrome (PCOS) is a widespread endocrinological dysfunction impacting women of reproductive age, categorized by excess androgens and a variety of associated syndromes, consisting of acne, alopecia, and hirsutism. It involves the presence of multiple immature follicles in the ovaries, which can disrupt normal ovulation and lead to hormonal imbalances and associated health complications. Routine diagnostic methods rely on manual interpretation of ultrasound (US) images and clinical assessments, which are time-consuming and prone to errors. Therefore, implementing an automated system is essential for streamlining the diagnostic process and enhancing accuracy. By automatically analyzing follicle characteristics and other relevant features, this research aims to facilitate timely intervention and reduce the burden on healthcare professionals. The present study proposes an advanced automated system for detecting and classifying PCOS from ultrasound images. Leveraging Artificial Intelligence (AI) based techniques, the system examines affected and unaffected cases to enhance diagnostic accuracy. The pre-processing of input images incorporates techniques such as image resizing, normalization, augmentation, Watershed technique, multilevel thresholding, etc. approaches for precise image segmentation. Feature extraction is facilitated by the proposed CystNet technique, followed by PCOS classification utilizing both fully connected layers with 5-fold cross-validation and traditional machine learning classifiers. The performance of the model is rigorously evaluated using a comprehensive range of metrics, incorporating AUC score, accuracy, specificity, precision, F1-score, recall, and loss, along with a detailed confusion matrix analysis. The model demonstrated a commendable accuracy of \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$96.54\\%$$\\end{document} when utilizing a fully connected classification layer, as determined by a thorough 5-fold cross-validation process. Additionally, it has achieved an accuracy of \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$97.75\\%$$\\end{document} when employing an ensemble ML classifier. This proposed approach could be suggested for predicting PCOS or similar diseases using datasets that exhibit multimodal characteristics.

Comparison of morphological and molecular Strongylus spp. identification in equine larval cultures and first report of a patent Strongylus asini infection in a horse.

Surveillance of Strongylus vulgaris and other Strongylus spp. in equids is important for targeted intervention in parasite control, requiring reliable routine diagnostic methods. Comparing morphological examination and PCR analyses of larval cultures to identify Strongylus spp. species based on German diagnostic samples from 2018. Method comparison. During the routine diagnostic investigations, in total 712 strongyle-egg positive equine faecal samples were cultured. Third-stage larvae (L3) were morphologically differentiated. For molecular validation, samples were examined using S. vulgaris real-time PCR and Strongylus edentatus/Strongylus equinus/Strongylus asini high-resolution melting PCRs. Based on 28S rRNA PCR, 594 samples positive for nematode DNA were included in the study. The inter-rater reliability to compare morphological and molecular species identification was fair for Strongylus spp. without species identification and for S. edentatus, slight for S. equinus and poor for S. vulgaris. The frequency based on morphological and molecular data in this study were for S. vulgaris 0% and 0.8%, respectively, for S. edentatus 0.3% and 1.5%, respectively, and for S. equinus 2.0% and 0.2%, respectively. Based on molecular analyses, one sample obtained from a domestic horse contained S. asini DNA, which was confirmed by sequencing. For many samples, no or only incomplete data regarding clinical history, the exact geographical location and whether samples were obtained on individual or farm level, were available. Results of morphological and molecular examination methods of strongyle L3 from equine samples can differ substantially. Further evaluation of these methods is required to provide reliable and cost-effective methods of screening equine parasites. Further studies using approaches suitable to detect S. asini are needed to evaluate its clinical and epidemiological relevance.

A Novel and Simple Method for a Differentiation of Alcohol Types.

Alcohol poisoning is a significant global problem that has become an epidemic. The determination of the alcohol type is hereby essential as it may affect the course of the treatment; however, there is no routine laboratory diagnostic method for alcohol types other than for ethanol. In this study, we aimed to define a simple method for alcohol type differentiation by utilizing a combination of breathalyzer and spectrophotometrically measured serum ethanol results. A breathalyzer and spectrophotometry were used to measure four different types of alcohol: ethanol, isopropanol, methanol, and ethylene glycol. To conduct serum alcohol analysis, four serum pools were created, each containing a different type of alcohol. The pools were analyzed using the spectrophotometric method with an enzymatic ethanol test kit. An experiment was conducted to measure the different types of alcohol using impreg-nated cotton and a balloon, simulating a breathalyzer test. An algorithm was created based on the measurements. Based on the results, the substance consumed could be methanol or isopropanol if the breathalyzer test indicates a positive reading and if the blood ethanol measurement is negative. If both the breathalyzer and the blood measurements are negative, the substance in question may be ethylene glycol. This simple method may determine methanol or isopropanol intake. This straightforward and innovative approach could assist healthcare professionals in different fields with diagnosing alcohol intoxication and, more precisely, help reducing related morbidity and mortality.

Comparison of film array pneumonia panel to routine diagnostic methods and its potential impact in an adult intensive care unit in Hong Kong and the potential role of emergency departments

Comparison of film array pneumonia panel to routine diagnostic methods and its potential impact in an adult intensive care unit in Hong Kong and the potential role of emergency departments

Pulmonary hemorrhage in oncologic patients – a diagnostic algorithm

The OBJECTIVE was to develop a diagnostic algorithm in oncologic patients with pulmonary hemorrhage.METHODS AND MATERIAL. A retrospective single-center study of the medical records of 258 patients who met the inclusion criteria was conducted. Inclusion criteria: age over 18 years, oncologic disease of the chest organs complicated by pulmonary hemorrhage. Inclusion criteria: age over 18 years, oncologic disease of the chest organs complicated by pulmonary hemorrhage. Exclusion criteria: age under 18 years, pulmonary hemorrhage of non-oncologic etiology. Pulmonary hemorrhage was considered to be the discharge of any volume of fresh blood or clots from the tracheobronchial tree, which was determined on the basis of anamnesis, clinical manifestations in the hospital, endoscopic examination. Routine diagnostic methods of investigation, such as chest radiography, chest computed tomography (including with contrast enhancement), fibrotracheobronchoscopy, bronchial arteriography were evaluated.RESULTS. The sensitivity for diagnosing the oncologic process in chest radiography, computed tomography, and fibrotracheobronchoscopy, was 84.7 %, 98.4 %, and 94.4 %, respectively. The sensitivity of fibrotracheobronchoscopy to detect the bleeding itself in oncologic patients reached 31.3 %, and the sensitivity of bronchial arteriography to diagnose the source of bleeding was 87.7 %.CONCLUSION. In pulmonary hemorrhage of oncologic genesis, the combination of fibrotracheobronchoscopy with computed tomography has sensitivity in 100 % of cases in determining the source and localization of the pathological process. Bronchial arteriography allows to perform endovascular hemostasis. It is necessary to conduct multicenter studies in order to develop and implement a unified algorithm assessing all etiopathogenetic features of pulmonary hemorrhage in oncologic patients.

Chronic diarrhea secondary to intestinal spirochetosis, should we think about it?

Abstract Human intestinal spirochetosis (HIS) is defined as a colonization of the apical membrane of the colonic mucosa and the appendix by spirochetes. It is a very rare finding, being more common in some populations (individuals living in villages and peri-urban environments in developing countries, recent immigrants from developing countries, men who have sex with other men and HIV positive patients), but the spirochete rarely is investigated as human enteric potential microorganism. It is a slow-growing microorganism and has specialized growth requirements, which is why it is not detectable in human fecal samples using routine diagnostic methods. However, it has been histologically identified attached to the colon and rectum in patients with conditions such as chronic diarrhea, rectal bleeding, and/or nonspecific abdominal discomfort. In this article we present the case of a patient with chronic diarrhea secondary to intestinal spirochetosis, highlighting the importance of considering this etiology in the differential diagnosis.

Potential application of body fluids autofluorescence in the non-invasive diagnosis of endometrial cancer.

Endometrial carcinoma (EC) is the most common cancer of the female reproductive tract in developed countries. The prognosis and 5-year survival rates are closely tied to the stage diagnosis. Current routine diagnostic methods of EC are either lacking specificity or are uncomfortable, invasive and painful for the patient. As of now, the gold diagnostic standard is endometrial biopsy. Early and non-invasive diagnosis of EC requires the identification of new biomarkers of disease and a screening test applicable to routine laboratory diagnostics. The application of untargeted metabolomics combined with artificial intelligence and biostatistics tools has the potential to qualitatively and quantitatively represent the metabolome, but its introduction into routine diagnostics is currently unrealistic due to the financial, time and interpretation challenges. Fluorescence spectral analysis of body fluids utilizes autofluorescence of certain metabolites to define the composition of the metabolome under physiological conditions. This review highlights the potential of fluorescence spectroscopy in the early detection of EC. Data obtained by three-dimensional fluorescence spectroscopy define the quantitative and qualitative composition of the complex fluorescent metabolome and are useful for identifying biochemical metabolic changes associated with endometrial carcinogenesis. Autofluorescence of biological fluids has the prospect of providing new molecular markers of EC. By integrating machine learning and artificial intelligence algorithms in the data analysis of the fluorescent metabolome, this technique has great potential to be implemented in routine laboratory diagnostics.

Peripheral T-cell lymphomas expressing CD30 and CD15 expand the spectrum of anaplastic large cell lymphoma, ALK-negative.

Peripheral T-cell lymphomas (PTCL) are morphologically and biologically heterogeneous and a subset expresses CD30, including anaplastic large cell lymphomas (ALCL) and a minority of PTCL, not otherwise specified (PTCL, NOS). ALCL with ALK translocations (ALCL, ALK+) are readily identified by routine diagnostic methods, but differentiating ALCL without ALK translocation (ALCL, ALK-) and PTCL, NOS expressing CD30 (PTCL CD30+) can be challenging. Furthermore, rare PTCL co-express CD30 and CD15 (PTCL CD30+CD15+); some resemble ALCL, ALK- while others resemble classic Hodgkin lymphoma. To explore the relationship between PTCL CD30+CD15+ and ALCL, ALK-, we analysed 19 cases of PTCL with CD30 expression, previously diagnosed as ALCL, ALK- (nine cases) and PTCL CD30+CD15+ (10 cases) for DUSP22/IRF4 rearrangements, coding RNA expression and selected transcriptome analysis using the NanoString nCounter gene expression analysis platform. Unsupervised clustering showed no clear segregation between ALCL, ALK- and PTCL CD30+CD15+. Three cases previously classified as PTCL CD30+CD15+ showed DUSP22/IRF4 rearrangements, favouring a diagnosis of ALCL, ALK-. Our results suggest that cases previously designated PTCL CD30+CD15+, likely fall within the spectrum of ALCL, ALK-; additionally, a subset of ALCL, ALK- with DUSP22/IRF4 rearrangement expresses CD15, consistent with previous reports and expands the immunophenotypic spectrum of this lymphoma subgroup.

Allergic bronchopulmonary mycosis due to Schizophyllum commune in a patient with chronic hepatitis B.

Schizophyllum commune (S. commune) is an opportunistic pathogenic fungus and can cause infection of the respiratory system in immunocompromised hosts. Allergic bronchopulmonary mycosis (ABPM) is the major disease caused by S. commune. However, identification of S. commune using routine mycological diagnostic methods is difficult. It is easy to make mistakes in diagnosis and treatment, resulting in deterioration of the disease. We report the first case of ABPM due to S. commune in a Chinese patient with chronic hepatitis B. The patient presented cough, sputum and dyspnea for six months. The pathogen was missed during routine laboratory workup. We performed bronchoscopy examination and bronchoalveolar lavage. S. commune was identified by metagenomic next-generation sequencing (mNGS) of bronchial alveolar lavage fluid (BALF). Hence, the patient was immediately treated with 200 mg voriconazole twice daily (intravenous infusion) and 20 mg prednisone once a day (oral therapy), along with oral entecavir for hepatitis B. There was no recurrence of infection after the medication was discontinued. S. commune infection should be considered in the diagnosis of patients with refractory cough, sputum and dyspnea, especially in immunocompromised individuals. The mNGS technique is an effective supplementary technique for the diagnosis of S. commune infection, enabling precise clinical decision-making and appropriate treatment. Most patients have good prognosis with a combination of proper antifungal therapy and hormonal therapy.

Panel Comparative Analysis Tool: An Open-Source Comparative Analysis Tool for Next-Generation Sequencing Panel Target Regions

Multi-gene next-generation sequencing (NGS) panels have become a routine diagnostic method in the contemporary practice of personalized medicine. To avoid inadequate test choice or interpretation, a detailed understanding of the precise panel target regions is required. However, the necessary bioinformatic expertise is not always available, and publicly accessible and easily interpretable analyses of target regions are scarce. To address this critical knowledge gap, we present the Panel Comparative Analysis Tool (PanelCAT) an open-source application to analyze, visualize and compare NGS panel DNA target regions. PanelCAT uses RefSeq, ClinVar and COSMIC cancer mutation census databases to quantify the exon and mutation coverage of target regions and provides interactive graphical representations and search functions to inspect the results. We demonstrate the utility of PanelCAT by analyzing two large NGS panels (Illumina TruSight Oncology 500, and Qiagen Human Pan Cancer Panel) to validate the advertised target genes, quantify targeted exons and mutations, and identify differences between panels. PanelCAT will enable institutions and researchers to catalogue and visualize NGS panel target regions independent of the manufacturer, promote transparency of panel limitations, and share this information with employees and requisitioners.

Optical Genome Mapping as a Potential Routine Clinical Diagnostic Method.

Chromosome analysis (CA) and chromosomal microarray analysis (CMA) have been successfully used to diagnose genetic disorders. However, many conditions remain undiagnosed due to limitations in resolution (CA) and detection of only unbalanced events (CMA). Optical genome mapping (OGM) has the potential to address these limitations by capturing both structural variants (SVs) resulting in copy number changes and balanced rearrangements with high resolution. In this study, we investigated OGM's concordance using 87 SVs previously identified by CA, CMA, or Southern blot. Overall, OGM was 98% concordant with only three discordant cases: (1) uncalled translocation with one breakpoint in a centromere; (2) uncalled duplication with breakpoints in the pseudoautosomal region 1; and (3) uncalled mosaic triplication originating from a marker chromosome. OGM provided diagnosis for three previously unsolved cases: (1) disruption of the SON gene due to a balanced reciprocal translocation; (2) disruption of the NBEA gene due to an inverted insertion; (3) disruption of the TSC2 gene due to a mosaic deletion. We show that OGM is a valid method for the detection of many types of SVs in a single assay and is highly concordant with legacy cytogenomic methods; however, it has limited SV detection capabilities in centromeric and pseudoautosomal regions.

Spectrum and management of rare Candida/yeast infections in Kuwait in the Middle East.

Invasive fungal infections (IFIs) are associated with high mortality rates and mostly affect patients with compromised immunity. The incidence of IFIs is increasing worldwide with the expanding population of susceptible patients. Candida and other yeast infections represent a major component of IFIs. Rare Candida/yeast infections have also increased in recent years and pose considerable diagnostic and management challenges as they are not easily recognized by routine phenotypic characteristic-based diagnostic methods and/or by the automated yeast identification systems. Rare Candida/yeasts also exhibit reduced susceptibility to antifungal drugs making proper management of invasive infections challenging. Here, we review the diagnosis and management of 60 cases of rare Candida/yeast IFIs described so far in Kuwait, an Arabian Gulf country in the Middle East. Interestingly, majority (34 of 60, 56.7%) of these rare Candida/yeast invasive infections occurred among neonates or premature, very-low-birth-weight neonates, usually following prior bacteremia episodes. The clinical details, treatment given, and outcome were available for 28 of 34 neonates. The crude mortality rate among these neonates was 32.2% as 19 of 28 (67.8%) survived the infection and were discharged in healthy condition, likely due to accurate diagnosis and frequent use of combination therapy. Physicians treating patients with extended stay under intensive care, on mechanical ventilation, receiving broad spectrum antibiotics and with gastrointestinal surgery/complications should proactively investigate IFIs. Timely diagnosis and early antifungal treatment are essential to decrease mortality. Understanding the epidemiology and spectrum of rare Candida/yeast invasive infections in different geographical regions, their susceptibility profiles and management will help to devise novel diagnostic and treatment approaches and formulate guidelines for improved patient outcome.

Predicting brain age using partition modeling strategy and atlas-based attentional enhancement in the Chinese population.

As a biomarker of human brain health during development, brain age is estimated based on subtle differences in brain structure from those under typical developmental. Magnetic resonance imaging (MRI) is a routine diagnostic method in neuroimaging. Brain age prediction based on MRI has been widely studied. However, few studies based on Chinese population have been reported. This study aimed to construct a brain age predictive model for the Chinese population across its lifespan. We developed a partition prediction method based on transfer learning and atlas attention enhancement. The participants were separated into four age groups, and a deep learning model was trained for each group to identify the brain regions most critical for brain age prediction. The Atlas attention-enhancement method was also used to help the models focus only on critical brain regions. The proposed method was validated using 354 participants from domestic datasets. For prediction performance in the testing sets, the mean absolute error was 2.218 ± 1.801years, and the Pearson correlation coefficient (r) was 0.969, exceeding previous results for wide-range brain age prediction. In conclusion, the proposed method could provide brain age estimation to assist in assessing the status of brain health.

Analysis and predictability of technologists' perception of MR exam complexity

IntroductionAs MRI becomes a routine clinical diagnostic method, its complexity of techniques, protocols and scanning is growing. On the other hand, aggravated by the ubiquitous shortage of workforce, technologists' stress level and burnout rates are increasing. In this context, our study aims to shed light on technologists’ perceived complexity of MR exams, by analyzing a multidimensional dataset composed of workflow, patient, and operational details, and further predicting perceived exam complexity. MethodsIn this IRB-approved study, data about imaging workflow, exam context, and patient characteristics were collected over one year from MR modality logfiles and from technologist questionnaires, including the perceived exam complexity. The association of individual factors with complexity was analyzed via Fisher's exact tests and Cramér's V values. Predictability of exam complexity was further evaluated via ROC analysis of three different multivariate classifiers. ResultsRetakes, delays, and extended exam duration are associated with perceived complexity (V ≥ 0.2). From the set of possible predictors, patient mobility and communication ability have the most influence on perceived complexity (V > 0.2), followed by special equipment needs (pulse oximetry, intubation, or ECG), protocol details and other patient characteristics. Feasibility of predicting the perceived exam complexity from a multivariate set of exam and patient details known at the time of scheduling has been demonstrated (AUC = 0.73), and suitable classification algorithms have been identified. ConclusionPerceived exam complexity is associated with various factors. Our results suggest that it can be predicted sufficiently well to support early operational decision making. Some factors, however, may not be readily available in hospital IT systems and must be obtained before scheduling. Implications for practiceResults and observations of this study could be utilized to assist operational scheduling in the radiology department and reduce MR technologists’ stress levels.

562. Diagnostic accuracy comparison of the Biofire Filmarray pneumonia panel versus routine diagnostic methods for diagnosis of ventilator associated pneumonia: a real life study

Abstract Background In Mexico, the Hospital Epidemiological Surveillance Network previously the COVID-19 pandemic, reported a total of 61,969 health care associated infections with an incidence rate of 4.7 per 100 discharges, 20.7% of which were categorized as ventilator associated pneumonia. Biofire Filmarray pneumonia panel has been accepted as a tool for early and rapid diagnostic of pneumonia with recognition of several hospital acquired pathogens including resistant genes. However, there are some mismatch in the multiplex PCR detection and the culture isolation. Methods An observational, comparative, retrospective, non-randomized, cross-sectional, open study was performed using files from patients diagnosed with ventilator associated pneumonia who underwent diagnostic testing on culture and PCR multiplex FilmArray pneumonia panel to determine diagnostic accuracy. Intensive care unit files from August 2021 to February 2022 with ventilator associated pneumonia with airway samples for Filmarray pneumonia panel and cultures. Evaluation of the used diagnostic tests was carried out using: sensitivity, specificity, positive predictive value and negative predictive value. Results 55 patients were included, each of them with both test. 72% of the study population were males, with a mean age of 61 years. 76% of the population had severe COVID-19. E.Coli had 100% sentitivity and 96% specificity , P. aeruginosa 100% sentitivity and 88% specificity, E.Cloacae 100% sentitivity and 91% specificity, and S. aureus had 100% sentitivity and 89% specificity on Biofire Filmarray pneumonia panel. While K. pneumoniae had 50% sensitivity and 89% specificity. NPV was 98% for K. pneumoniae, and 100% for E. coli, P. aeruginosa, E. cloacae, and S. aureus. S.maltophilia was isolated in 3 culture samples and the Filmarray pneumonia panel was reported negative because lacking of testing this microorganism, as well as 1 A. fumigatus isolation. Samples for cultures and Biofire FilmArray pneumonia panel The different samples that were included from 55 patients in this study correlated with pneumonia panel and conventional cultures. PCR Biofire FilmArray pneumonia panel diagnostic study evaluation Each of the microorganism that had correlation between Filmarray pneumonia panel compared with conventional cultures Conclusion Biofire Filmarray pneumonia panel provides early and accurate information on pathogens causing ventilator associated pneumonia. However it cannot replace conventional culture because of lacking of some microorganism detection. It provides a useful tool for early decision-making in treatment. Disclosures All Authors: No reported disclosures

Application of metagenomics for diagnosis of broilers displaying neurological symptoms

BackgroundThirty-two-day-old broiler chickens at a farm located in northwestern South Korea displayed adverse neurological symptoms including limping, lying down, and head shaking. Approximately 2.1% of chickens died or were culled due to severe symptoms. Five carcasses were submitted to the Avian Disease Division of the Animal and Plant Quarantine Agency (APQA) for disease diagnosis.ResultsBroilers displayed severe pericarditis and perihepatitis associated with gross lesions. Broilers also displayed microscopic lesions in the cerebrum and in the granular layer of the cerebellum, which were associated with multifocal perivascular cuffing and purulent necrosis in the cerebrum, and severe meningitis with heterophil and lymphocyte infiltration. Staphylococcus spp. were identified in the liver and heart using bacteriological culture. PCR/RT-PCR assays revealed that broilers were negative for avian Clostridium botulinum, Newcastle disease virus, and avian encephalomyelitis virus. Bacterial and viral metagenomic analysis of brain sample further revealed the presence of Pseudomonas spp. and Marek’s disease virus, which are known etiological agents of chicken meningoencephalitis.ConclusionsThis study reports a diagnostic analysis of gross and histopathological lesions from 32-day-old broilers displaying unique neurological symptoms that revealed the presence of the several neurological diseases including meningoencephalitis. The causative agents associated with meningoencephalitis of broilers that had not been identified by routine diagnostic methods could be diagnosed by metagenomics, which proves the usefulness of metagenomics as a diagnostic tool for unknown neurological diseases in broilers.

Virus discovery in dogs with non-suppurative encephalitis reveals a high incidence of tick-borne encephalitis virus infections in Switzerland.

Viral infections are a frequent cause of disseminated non-suppurative encephalitis in dogs. However, using routine diagnostic methods, the specific virus may remain unknown due to extensive or complete viral clearance or because the virus is unexpected or new. A metatranscriptomics-based approach of combining high-throughput sequencing (HTS) and bioinformatics analysis was used to investigate the viral etiology in archival cases of dogs with non-suppurative encephalitis. In formalin-fixed paraffin embedded (FFPE) brain material from the years 1976 to 2021 a high incidence of tick-borne encephalitis virus (TBEV) was detected. Moreover, canine distemper virus (CDV) was identified without typical demyelinating lesions and canine vesivirus (CaVV) was detected as an unexpected virus associated with non-suppurative encephalitis. We demonstrated the viral presence in brain tissues at the sites of inflammation by immunohistochemistry (IHC) and in situ hybridization (ISH). These results highlight the value of emerging sequencing technologies in veterinary diagnostics and expand our knowledge on the etiologies of encephalitis in dogs.