FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4226479440> ?p ?o ?g. }

• W4226479440 endingPage "e714" @default.
• W4226479440 startingPage "e704" @default.
• W4226479440 abstract "An optimised standard experimental setup across different hospitals is urgently needed to ensure consistency in nucleic acid test results for SARS-CoV-2 detection. A standard comparison across different nucleic acid tests and their optimal experimental setups is not present. We assessed the performance of three common nucleic acid tests, namely digital PCR (dPCR), quantitative PCR (qPCR), and loop-mediated isothermal amplification (LAMP), to detect SARS-CoV-2 in clinical settings.In this systematic review and meta-analysis we compared sensitivity and specificity of qPCR, dPCR, and LAMP and their performances when different experimental setups (namely specimen type used, use of RNA extraction, primer-probe sets, and RNA extraction methods) are applied. We searched PubMed, BioRxiv, MedRxiv, SciFinder, and ScienceDirect for studies and preprints published between Feb 29 and Dec 15, 2020. Included dPCR, qPCR, and LAMP studies using any type of human specimens should report the number of true-positive, true-negative, false-positive, and false-negative cases with Emergency Use Authorization (EUA)-approved PCR assays as the comparator. Studies with a sample size of less than ten, descriptive studies, case studies, reviews, and duplicated studies were excluded. Pooled sensitivity and specificity were computed from the true and false positive and negative cases using Reitsma's bivariate random-effects and bivariate latent class models. Test performance reported in area under the curve (AUC) of the three nucleic acid tests was further compared by pooling studies with similar experimental setups (eg, tests that used RNA extracted pharyngeal swabs but with either the open reading frame 1ab or the N primer). Heterogeneity was assessed and reported in I2 and τ2.Our search identified 1277 studies of which we included 66 studies (11 dPCR, 32 qPCR, and 23 LAMP) with 15 017 clinical samples in total in our systematic review and 52 studies in our meta-analysis. dPCR had the highest pooled diagnostic sensitivity (94·1%, 95% CI 88·9-96·6, by Reitsma's model and 95·8%, 54·9-100·0, by latent class model), followed by qPCR (92·7%, 88·3-95·6, and 93·4%, 60·9-99·9) and LAMP (83·3%, 76·9-88·2, and 86·2%, 20·7-99·9), using EUA-approved PCR kits as the reference standard. LAMP was the most specific with a pooled estimate of 96·3% (93·8-97·8) by Reitsma's model and 94·3% (49·1-100·0) by latent class model, followed by qPCR (92·9%, 87·2-96·2, and 93·1%, 47·1-100·0) and dPCR (78·5%, 57·4-90·8, and 73·8%, 0·9-100·0). The overall heterogeneity was I2 0·5% (τ2 2·79) for dPCR studies, 0% (4·60) for qPCR studies, and 0% (3·96) for LAMP studies. AUCs of the three nucleic acid tests were the highest and differed the least between tests (ie, AUC>0·98 for all tests) when performed with RNA extracted pharyngeal swabs using SARS-CoV-2 open reading frame 1ab primer.All three nucleic acid tests consistently perform better with pharyngeal swabs using SARS-CoV-2 open reading frame 1ab primer with RNA extraction. dPCR was shown to be the most sensitive, followed by qPCR and LAMP. However, their accuracy does not differ significantly. Instead, accuracy depends on specific experimental conditions, implying that more efforts should be directed to optimising the experimental setups for the nucleic acid tests. Hence, our results could be a reference for optimising and establishing a standard nucleic acid test protocol that is applicable in laboratories worldwide.University Grants Committee and The Chinese University of Hong Kong." @default.
• W4226479440 created "2022-05-05" @default.
• W4226479440 creator A5012869923 @default.
• W4226479440 creator A5052115555 @default.
• W4226479440 date "2021-12-01" @default.
• W4226479440 modified "2023-10-03" @default.
• W4226479440 title "Diagnostic performances of common nucleic acid tests for SARS-CoV-2 in hospitals and clinics: a systematic review and meta-analysis" @default.
• W4226479440 cites W2023529456 @default.
• W4226479440 cites W2107328434 @default.
• W4226479440 cites W2126727011 @default.
• W4226479440 cites W2151047141 @default.
• W4226479440 cites W2236188897 @default.
• W4226479440 cites W3000486277 @default.
• W4226479440 cites W3004824173 @default.
• W4226479440 cites W3009219040 @default.
• W4226479440 cites W3009423849 @default.
• W4226479440 cites W3013776441 @default.
• W4226479440 cites W3014222358 @default.
• W4226479440 cites W3015883707 @default.
• W4226479440 cites W3016615900 @default.
• W4226479440 cites W3017281110 @default.
• W4226479440 cites W3017669300 @default.
• W4226479440 cites W3021724367 @default.
• W4226479440 cites W3022126134 @default.
• W4226479440 cites W3024144282 @default.
• W4226479440 cites W3024499544 @default.
• W4226479440 cites W3024623392 @default.
• W4226479440 cites W3027129147 @default.
• W4226479440 cites W3027289442 @default.
• W4226479440 cites W3027501461 @default.
• W4226479440 cites W3027866910 @default.
• W4226479440 cites W3033206795 @default.
• W4226479440 cites W3034434235 @default.
• W4226479440 cites W3034747739 @default.
• W4226479440 cites W3038651075 @default.
• W4226479440 cites W3038707046 @default.
• W4226479440 cites W3041626911 @default.
• W4226479440 cites W3043087985 @default.
• W4226479440 cites W3044120595 @default.
• W4226479440 cites W3045178645 @default.
• W4226479440 cites W3045371889 @default.
• W4226479440 cites W3046093459 @default.
• W4226479440 cites W3046143956 @default.
• W4226479440 cites W3047013814 @default.
• W4226479440 cites W3047151171 @default.
• W4226479440 cites W3047678284 @default.
• W4226479440 cites W3048140003 @default.
• W4226479440 cites W3048290924 @default.
• W4226479440 cites W3060075221 @default.
• W4226479440 cites W3080514314 @default.
• W4226479440 cites W3081499269 @default.
• W4226479440 cites W3081517366 @default.
• W4226479440 cites W3081660999 @default.
• W4226479440 cites W3082512647 @default.
• W4226479440 cites W3084113028 @default.
• W4226479440 cites W3085854736 @default.
• W4226479440 cites W3087658644 @default.
• W4226479440 cites W3090133157 @default.
• W4226479440 cites W3090756214 @default.
• W4226479440 cites W3092062136 @default.
• W4226479440 cites W3092609341 @default.
• W4226479440 cites W3093690976 @default.
• W4226479440 cites W3093925601 @default.
• W4226479440 cites W3094860797 @default.
• W4226479440 cites W3096640152 @default.
• W4226479440 cites W3097495840 @default.
• W4226479440 cites W3097561864 @default.
• W4226479440 cites W3097669511 @default.
• W4226479440 cites W3101614547 @default.
• W4226479440 cites W3108001574 @default.
• W4226479440 cites W3110296654 @default.
• W4226479440 cites W3113716702 @default.
• W4226479440 cites W3117339477 @default.
• W4226479440 cites W3117757472 @default.
• W4226479440 cites W3119343341 @default.
• W4226479440 cites W3125805574 @default.
• W4226479440 cites W3129287485 @default.
• W4226479440 cites W3134669941 @default.
• W4226479440 cites W3151098594 @default.
• W4226479440 cites W3171036251 @default.
• W4226479440 doi "https://doi.org/10.1016/s2666-5247(21)00214-7" @default.
• W4226479440 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34661181" @default.
• W4226479440 hasPublicationYear "2021" @default.
• W4226479440 type Work @default.
• W4226479440 citedByCount "22" @default.
• W4226479440 countsByYear W42264794402021 @default.
• W4226479440 countsByYear W42264794402022 @default.
• W4226479440 countsByYear W42264794402023 @default.
• W4226479440 crossrefType "journal-article" @default.
• W4226479440 hasAuthorship W4226479440A5012869923 @default.
• W4226479440 hasAuthorship W4226479440A5052115555 @default.
• W4226479440 hasBestOaLocation W42264794401 @default.
• W4226479440 hasConcept C104317684 @default.
• W4226479440 hasConcept C105795698 @default.
• W4226479440 hasConcept C142724271 @default.
• W4226479440 hasConcept C159047783 @default.
• W4226479440 hasConcept C24107716 @default.
• W4226479440 hasConcept C2777391075 @default.

• next