Evidence map›Paper›PMID 36228768›Full record

ArticleThe Journal of hospital infection2023

Factors affecting turnaround time of SARS-CoV-2 sequencing for inpatient infection prevention and control decision making: analysis of data from the COG-UK HOCI study.

H Colton, M D Parker, O Stirrup, J Blackstone, M Loose, C P McClure, S Roy, C Williams, J McLeod, D Smith and 12 more

Abstract read

In one paragraph

Article in The Journal of hospital infection, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it

0cells of the map it votes in

3citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

H ColtonDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK; Directorate of Laboratory Medicine, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK. Electronic address: h.colton@sheffield.ac.uk.

M D ParkerSheffield Biomedical Research Centre, University of Sheffield, Sheffield, UK; Sheffield Bioinformatics Core, University of Sheffield, Sheffield, UK.

O StirrupInstitute for Global Health, University College London, London, UK.

J BlackstoneThe Comprehensive Clinical Trials Unit, University College London, London, UK.

M LooseSchool of Life Sciences, University of Nottingham, Nottingham, UK.

C P McClureSchool of Life Sciences, University of Nottingham, Nottingham, UK.

S RoyDepartment of Infection, Immunity and Inflammation, Institute of Child Health, University College London, London, UK.

C WilliamsDepartment of Infection, Immunity and Inflammation, Institute of Child Health, University College London, London, UK.

J McLeodSchool of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK.

D SmithDepartment of Applied Biology, Cellular and Molecular Sciences/Microbiology Group, Northumbria University, Newcastle, UK.

Y TahaDepartment of Infection and Tropical Medicine, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Royal Victoria Infirmary, Newcastle Upon Tyne, UK.

P ZhangDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK.

S N HsuDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK; Sheffield Bioinformatics Core, University of Sheffield, Sheffield, UK.

B KeleVirology Department, East and South East London Pathology Partnership, Royal London Hospital, Barts Health NHS Trust, London, UK.

K HarrisVirology Department, East and South East London Pathology Partnership, Royal London Hospital, Barts Health NHS Trust, London, UK.

F MappInstitute for Global Health, University College London, London, UK.

R WilliamsDepartment of Infection, Immunity and Inflammation, Institute of Child Health, University College London, London, UK.

COG-UK HOCI Investigators, COVID-19 Genomics UK (COG-UK) Consortium

P FlowersSchool of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK.

J BreuerDepartment of Infection, Immunity and Inflammation, Institute of Child Health, University College London, London, UK.

D G PartridgeDirectorate of Laboratory Medicine, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.

T I de SilvaDepartment of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK.

Funding

Medical Research Council MC_PC_19027

6 · The paper itself

Abstract

backgroundBarriers to rapid return of sequencing results can affect the utility of sequence data for infection prevention and control decisions.

aimTo undertake a mixed-methods analysis to identify challenges that sites faced in achieving a rapid turnaround time (TAT) in the COVID-19 Genomics UK Hospital-Onset COVID-19 Infection (COG-UK HOCI) study.

methodsFor the quantitative analysis, timepoints relating to different stages of the sequencing process were extracted from both the COG-UK HOCI study dataset and surveys of study sites. Qualitative data relating to the barriers and facilitators to achieving rapid TATs were included from thematic analysis.

findingsThe overall TAT, from sample collection to receipt of sequence report by infection control teams, varied between sites (median 5.1 days, range 3.0-29.0 days). Most variation was seen between reporting of a positive COVID-19 polymerase chain reaction (PCR) result to sequence report generation (median 4.0 days, range 2.3-27.0 days). On deeper analysis, most of this variability was accounted for by differences in the delay between the COVID-19 PCR result and arrival of the sample at the sequencing laboratory (median 20.8 h, range 16.0-88.7 h). Qualitative analyses suggest that closer proximity of sequencing laboratories to diagnostic laboratories, increased staff flexibility and regular transport times facilitated a shorter TAT.

conclusionIntegration of pathogen sequencing into diagnostic laboratories may help to improve sequencing TAT to allow sequence data to be of tangible value to infection control practice. Adding a quality control step upstream to increase capacity further down the workflow may also optimize TAT if lower quality samples are removed at an earlier stage.

Indexed as

COVID-19SARS-CoV-2Decision MakingHumansInpatientsUnited KingdomInfection controlSARS-CoV-2SequencingTurnaround time

Identifiers

PMID36228768

DOI10.1016/j.jhin.2022.09.022

PMCPMC9550290

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.