bioRxiv Science⌕ Search

Biology subjects

Neoh, H.-m.

Publications and source records attributed to Neoh, H.-m..

4 recordsLinked to original sources
bioRxiv2024

hAMRonization: Enhancing antimicrobial resistance prediction using the PHA4GE AMR detection specification and tooling

The detection of antimicrobial resistance (AMR) markers directly from genomic or metagenomic data is becoming a standard clinical and public health procedure. This has resulted in the development of a number of different bioinformatic AMR prediction tools. Although many may implement similar principles, these tools differ significantly in their supported inputs, search algorithms, parameterisation, and underlying reference databases. Each of these tools generates a report of detected AMR genes or variants in a distinct, non-standard, format. This presents a huge barrier to the comparison of results and to the modularity of tools for AMR gene prediction within bioinformatic workflows. In collaboration with 17 public health laboratories across 10 countries, the Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) data structures working group has developed and piloted a standardized output specification for the bioinformatic detection of AMR from microbial genomes. In this report, we discuss hAMRonization, a python package and command-line utility, which implements PHA4GEs AMR specification to combine the outputs of disparate antimicrobial resistance gene detection tools into a single unified format. hAMRonization can be easily extended and currently supports 18 different tools (both species-agnostic and species-specific) for the detection of genes and/or variants conferring AMR. The harmonized reports are available in tabular form, JSON format or through an interactive HTML file (e.g., https://maguire-lab.github.io/assets/interactive_report_demo.html) that can be opened within the browser for navigable data exploration. As of 2024-03-07 hAMRonization has been downloaded [~]12,500 times, incorporated into >9 public bioinformatic tools and workflows, and been internally adopted by several national and international public health groups. The hAMRonization tool and underlying specification are open-source and freely available through PyPI, conda and GitHub (https://github.com/pha4ge/hAMRonization).

bioinformatics↗
bioRxiv2018

Comparison of Prognostic Accuracy of the quick Sepsis-Related Organ Failure Assessment between Short- & Long-term Mortality in Patients Presenting Outside of The Intensive Care Unit - A Systematic Review & Meta-analysis

ObjectiveIn year 2016, quick Sepsis-Related Organ Failure Assessment (qSOFA) was introduced as a better sepsis screening tool compared to systemic inflammatory response syndrome (SIRS). The purpose of this systematic review and meta-analysis is to evaluate the ability of the qSOFA in predicting short- and long-term mortality among patients outside the intensive care unit setting.\n\nMethodStudies reporting on the qSOFA and mortality from MEDLINE (published between 1946 and 15th December 2017) and SCOPUS (published before 15th December 2017). Hand-checking of the references of relevant articles was carried out. Studies were included if they involved inclusion of patients presenting to the ED; usage of Sepsis-3 definition with suspected infection; usage of qSOFA score for mortality prognostication; and written in English. Study details, patient demographics, qSOFA scores, short-term (<30 days) and long-term ([&ge;]30 days) mortality were extracted. Two reviewers conducted all reviews and data extraction independently.\n\nResults and DiscussionA total of 39 studies met the selection criteria for full text review and only 36 studies were included. Data on qSOFA scores and mortality rate were extracted from 36 studies from 15 countries. The pooled odds ratio was 5.5 and 4.7 for short-term and long-term mortality respectively. The overall pooled sensitivity and specificity for the qSOFA was 48% and 85% for short-term mortality and 32% and 92% for long-term mortality, respectively. Studies reporting on short-term mortality were heterogeneous (Tau=24%, I2=94%, P<0.001), while long-term mortality studies were homogenous (Tau=0%, I2<0.001, P=0.52). The factors contributing to heterogeneity may be wide age group, various clinical settings, variation in the timing of qSOFA scoring, and broad range of clinical diagnosis and criteria. There was no publication bias for short-term mortality analysis.\n\nConclusionqSOFA score showed a poor sensitivity but moderate specificity for both short and long-term mortality prediction in patients with suspected infection. qSOFA score may be a cost-effective tool for sepsis prognostication outside of the ICU setting.

epidemiology↗
bioRxiv2017

Rapid Detection of Sepsis using CESDA: the Caenorabditis elegans Sepsis Detection Assay

Sepsis is a life-threatening condition which could be alleviated by rapid diagnosis and appropriate antibiotic administration. However, currently available laboratory tests for sepsis diagnosis lacks sensitivity and specificity; they also have long turn-around times. In this proof-of-concept study, the nematode Caenorhabditis elegans was used as a biological sensor to detect urine of sepsis patients in an assay designated as the C. elegans Sepsis Detection Assay (CESDA). From January to June 2016, 45 patients who were admitted to the Emergency Department of a university hospital due to suspected sepsis were included into the study. Urine samples were obtained from these patients and healthy controls and spotted onto CESDA assay plates. Subsequently, C. elegans were aliquoted onto the centre of the plates and allowed to migrate freely. Number of worms found in either spots or quadrants of the plates containing control or suspected sepsis samples were scored in 10 minute intervals in a 60-minute duration. The CESDA index was then calculated for each sample, where an index near +1 represented attraction of the worms towards the sample, while an index near -1 signified repulsion. Confirmatory diagnosis for suspected sepsis samples was determined using a combination of clinical criteria assessment and standard laboratory protocols. All patients who were positive for sepsis were found to have a CESDA index of > 0.1 (positive predictive value, PPV [&ge;]87%). In addition, the worms were able to differentiate urine of sepsis patients from control as early as 20 minutes (p=0.012). Interestingly, the assay was also able to identify infection within 40 minutes of the test (AUROC = 0.80, p= 0.016). The rapidity of CESDA in sepsis and infection identification as well as the usability of urine samples which are non-invasive towards the patient in this method makes it an interesting protocol to be further explored for sepsis diagnosis.

microbiology↗