Ontology type: schema:ScholarlyArticle Open Access: True
2022-05-04
AUTHORSPengtao Liu, Yinghui You, Lingjie Liao, Yi Feng, Yiming Shao, Hui Xing, Guanghua Lan, Jianjun Li, Yuhua Ruan, Dan Li
ABSTRACTBackgroundMaintaining plasma HIV RNA suppression below the limit of quantification is the goal of antiretroviral therapy (ART). When viral loads (VL) remain in low-level viremia (LLV), or between 201 and 999 copies/mL, the clinical consequences are still not clear. We investigated the occurrence of LLV with drug resistance and its effect on CD4 cell counts in a large Chinese cohort.MethodsWe analysed data of 6,530 ART-experienced patients (42.1 ± 10.9 years; 37.3% female) from the China’s national HIV drug resistance (HIVDR) surveillance database. Participants were followed up for 32.9 (IQR 16.7–50.5) months. LLV was defined as the occurrence of at least one viral load (VL) measurement of 50–200 copies/mL during ART. Outcomes were drug resistance associated mutations (DRAM) and CD4 cell counts levels.ResultsAmong 6530 patients, 58.0% patients achieved VL less than 50 copies/mL, 27.8% with VL between 50 and 999 copies/mL (8.6% experienced LLV), and 14.2% had a VL ≥ 1000 copies/mL. Of 1818 patients with VL 50–999 copies/mL, 182 (10.0%) experienced HIVDR, the most common DRAM were M184I/V 28.6%, K103N 19.2%, and V181C/I/V 10.4% (multidrug resistance: 27.5%), and patients with HIVDR had a higher risk of CD4 cell counts < 200 cells/μL (AOR 3.8, 95% CI 2.6–5.5, p < 0.01) comparing with those without HIVDR. Of 925 patients with VL ≥ 1000 copies/mL, 495 (53.5%) acquired HIVDR, the most common DRAM were K103N 43.8%, M184I/V 43.2%, M41L 19.0%, D67N/G 16.4%, V181C/I/V 14.5%, G190A/S 13.9% and K101E 13.7% (multidrug resistance: 75.8%), and patients with HIVDR had a higher risk of CD4 cell counts < 200 cells/μL (AOR 5.8, 95% CI 4.6–7.4, p < 0.01) comparing with those without HIVDR.ConclusionPersistent with VL 50–999 copies/mL on ART is associated with emerging DRAM for all drug classes, and patients in this setting were at increased risk of CD4 cell counts < 200 cells/μL, which suggest resistance monitoring and ART optimization be earlier considered. More... »
PAGES426
http://scigraph.springernature.com/pub.10.1186/s12879-022-07417-z
DOIhttp://dx.doi.org/10.1186/s12879-022-07417-z
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1147615249
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/35509014
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Medical and Health Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Clinical Sciences",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Anti-HIV Agents",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Anti-Retroviral Agents",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "CD4 Lymphocyte Count",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Drug Resistance, Viral",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Female",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "HIV Infections",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "HIV-1",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Male",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Viral Load",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Viremia",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Weifang Medical University, Weifang, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.268079.2",
"name": [
"Weifang Medical University, Weifang, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Liu",
"givenName": "Pengtao",
"id": "sg:person.010746447243.99",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010746447243.99"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Weifang Medical University, Weifang, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.268079.2",
"name": [
"Weifang Medical University, Weifang, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "You",
"givenName": "Yinghui",
"id": "sg:person.07421621443.23",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07421621443.23"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.508379.0",
"name": [
"State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Liao",
"givenName": "Lingjie",
"id": "sg:person.0717555076.16",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0717555076.16"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.508379.0",
"name": [
"State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Feng",
"givenName": "Yi",
"type": "Person"
},
{
"affiliation": {
"alternateName": "State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.508379.0",
"name": [
"State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Shao",
"givenName": "Yiming",
"id": "sg:person.016605554207.92",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016605554207.92"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.508379.0",
"name": [
"State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Xing",
"givenName": "Hui",
"id": "sg:person.01271251630.73",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01271251630.73"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.418332.f",
"name": [
"Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Lan",
"givenName": "Guanghua",
"id": "sg:person.01066022370.01",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066022370.01"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.418332.f",
"name": [
"Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Li",
"givenName": "Jianjun",
"id": "sg:person.01147607260.37",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01147607260.37"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.418332.f",
"name": [
"State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China",
"Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Ruan",
"givenName": "Yuhua",
"id": "sg:person.010415350557.64",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010415350557.64"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China",
"id": "http://www.grid.ac/institutes/grid.508379.0",
"name": [
"State Key Laboratory for Infectious Disease Prevention and Control (SKLID), National Center for AIDS/STD Control and Prevention (NCAIDS), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 155 Changbai Road, Changping District, 102206, Beijing, People\u2019s Republic of China"
],
"type": "Organization"
},
"familyName": "Li",
"givenName": "Dan",
"id": "sg:person.01210407715.54",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01210407715.54"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s11904-020-00523-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1130126021",
"https://doi.org/10.1007/s11904-020-00523-0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/sj.cr.7290362",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1043970791",
"https://doi.org/10.1038/sj.cr.7290362"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12879-020-05124-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1128670372",
"https://doi.org/10.1186/s12879-020-05124-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12981-020-00264-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1125396977",
"https://doi.org/10.1186/s12981-020-00264-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12879-021-05854-w",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1135228864",
"https://doi.org/10.1186/s12879-021-05854-w"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/s41598-018-21791-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1101059644",
"https://doi.org/10.1038/s41598-018-21791-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00430-017-0494-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1083851975",
"https://doi.org/10.1007/s00430-017-0494-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12879-019-3781-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1112168777",
"https://doi.org/10.1186/s12879-019-3781-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12889-015-1489-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046331281",
"https://doi.org/10.1186/s12889-015-1489-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/1471-2334-10-318",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1047274642",
"https://doi.org/10.1186/1471-2334-10-318"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12879-020-4837-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1124937929",
"https://doi.org/10.1186/s12879-020-4837-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s12879-021-05794-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1134757967",
"https://doi.org/10.1186/s12879-021-05794-5"
],
"type": "CreativeWork"
}
],
"datePublished": "2022-05-04",
"datePublishedReg": "2022-05-04",
"description": "BackgroundMaintaining plasma HIV RNA suppression below the limit of quantification is the goal of antiretroviral therapy (ART). When viral loads (VL) remain in low-level viremia (LLV), or between 201 and 999 copies/mL, the clinical consequences are still not clear. We investigated the occurrence of LLV with drug resistance and its effect on CD4 cell counts in a large Chinese cohort.MethodsWe analysed data of 6,530 ART-experienced patients (42.1\u2009\u00b1\u200910.9\u00a0years; 37.3% female) from the China\u2019s national HIV drug resistance (HIVDR) surveillance database. Participants were followed up for 32.9 (IQR 16.7\u201350.5) months. LLV was defined as the occurrence of at least one viral load (VL) measurement of 50\u2013200 copies/mL during ART. Outcomes were drug resistance associated mutations (DRAM) and CD4 cell counts levels.ResultsAmong 6530 patients, 58.0% patients achieved VL less than 50 copies/mL, 27.8% with VL between 50 and 999 copies/mL (8.6% experienced LLV), and 14.2% had a VL\u2009\u2265\u20091000 copies/mL. Of 1818 patients with VL 50\u2013999 copies/mL, 182 (10.0%) experienced HIVDR, the most common DRAM were M184I/V 28.6%, K103N 19.2%, and V181C/I/V 10.4% (multidrug resistance: 27.5%), and patients with HIVDR had a higher risk of CD4 cell counts\u2009<\u2009200 cells/\u03bcL (AOR 3.8, 95% CI 2.6\u20135.5, p\u2009<\u20090.01) comparing with those without HIVDR. Of 925 patients with VL\u2009\u2265\u20091000 copies/mL, 495 (53.5%) acquired HIVDR, the most common DRAM were K103N 43.8%, M184I/V 43.2%, M41L 19.0%, D67N/G 16.4%, V181C/I/V 14.5%, G190A/S 13.9% and K101E 13.7% (multidrug resistance: 75.8%), and patients with HIVDR had a higher risk of CD4 cell counts\u2009<\u2009200 cells/\u03bcL (AOR 5.8, 95% CI 4.6\u20137.4, p\u2009<\u20090.01) comparing with those without HIVDR.ConclusionPersistent with VL 50\u2013999 copies/mL on ART is associated with emerging DRAM for all drug classes, and patients in this setting were at increased risk of CD4 cell counts\u2009<\u2009200 cells/\u03bcL, which suggest resistance monitoring and ART optimization be earlier considered.",
"genre": "article",
"id": "sg:pub.10.1186/s12879-022-07417-z",
"inLanguage": "en",
"isAccessibleForFree": true,
"isFundedItemOf": [
{
"id": "sg:grant.8898621",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1024946",
"issn": [
"1471-2334"
],
"name": "BMC Infectious Diseases",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "22"
}
],
"keywords": [
"CD4 cell count",
"low-level viremia",
"copies/mL",
"viral load",
"antiretroviral therapy",
"cell count",
"drug resistance",
"copies/",
"high risk",
"VL 50",
"plasma HIV RNA suppression",
"HIV RNA suppression",
"ART-experienced patients",
"cells/\u03bcL",
"cells/",
"large Chinese cohort",
"viral load measurements",
"CD4 cells",
"antiretroviral treatment",
"drug classes",
"HIVDR",
"clinical consequences",
"Chinese cohort",
"patients",
"RNA suppression",
"surveillance database",
"viremia",
"risk",
"count",
"mL",
"HIV",
"therapy",
"cohort",
"MethodsWe",
"load measurements",
"months",
"outcomes",
"resistance monitoring",
"treatment",
"resistance",
"occurrence",
"participants",
"cells",
"suppression",
"mutations",
"setting",
"\u03bcL",
"levels",
"database",
"effect",
"limit of quantification",
"people",
"monitoring",
"data",
"consequences",
"quantification",
"impact",
"goal",
"measurements",
"load",
"China",
"class",
"limit",
"art optimization",
"optimization",
"DRAM"
],
"name": "Impact of low-level viremia with drug resistance on CD4 cell counts among people living with HIV on antiretroviral treatment in China",
"pagination": "426",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1147615249"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1186/s12879-022-07417-z"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"35509014"
]
}
],
"sameAs": [
"https://doi.org/10.1186/s12879-022-07417-z",
"https://app.dimensions.ai/details/publication/pub.1147615249"
],
"sdDataset": "articles",
"sdDatePublished": "2022-06-01T22:25",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/article/article_941.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1186/s12879-022-07417-z"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s12879-022-07417-z'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12879-022-07417-z'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12879-022-07417-z'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12879-022-07417-z'
This table displays all metadata directly associated to this object as RDF triples.
290 TRIPLES
22 PREDICATES
115 URIs
95 LITERALS
18 BLANK NODES