PneumoniaNCT06566898
Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients
An observational study of Pneumonia and Next-generation Sequencing, run by Shanghai General Hospital, China at 1 site in China.
Trial summary
Monitoring of antimicrobial resistance (AMR) based on metagenomics analyses in pneumonia patients is critical for optimizing clinical diagnosis and treatment and improving clinical prognosis. This study is designed to ask the following key questions: 1. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Pneumonia, Next-generation Sequencing, Microbiome
- How many people
- 800 participants
- Where
- 1 siteChina
- Study dates
- 1 Aug 2024to 30 Sep 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Pneumonia patients from four centers in China during 2022-2025.
Who may be able to join
- Patients clinically diagnosed as severe pneumonia and mild pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA), who meet 1 of the following major criteria or ≥3 minor criteria can be diagnosed. The diagnostic criteria for severe and mild pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011.
- Clinical examination was performed, and there was biospecimen (nasopharyngeal swab, oropharyngeal swab, bronchoalveolar lavage fluid, sputum, blood, hydrothorax, lung tissue) remaining in the clinical microbiological examination.
Who cannot join
- Patients whose biological samples may be contaminated;
- Patients with alveolar lavage fluid or hydrothorax volume less than 200μl.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Mei Kang
Shanghai, Shanghai Municipality, 200080
Mei Kang, MPH, +8618501709576, mei.kang@shgh.cn
Ruilan Wang, PhD
About this study
Official title: Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients: a Genomic Epidemiology Study
Monitoring of antimicrobial resistance (AMR) based on metagenomics analyses in pneumonia patients is critical for optimizing clinical diagnosis and treatment and improving clinical prognosis. This study is designed to ask the following key questions:
- What is the microbiome maps of patients with severe pneumonia and mild pneumonia ?
- How many pathogen resistance genes are carrying in severe pneumonia and mild pneumonia ?
- What is the genetic diversity of key pathogens detected in severe pneumonia and mild pneumonia during 2019-2025?
Read the detailed description
This is a historical prospective obsevational study. Patients diagnosed with severe and mild pneumonia are recruited continously from four hospitals (Shanghai General Hospital, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuhan Union Hospital, and Huanggang Central Hospital) in China during March, 2019 to March, 2025.
Next-generation sequencing: Metagenomics and metatranscriptomic libraries undergo next-generation sequencing using the Illumina Novaseq 6000 platform.
Microbiome analysis: using KneadData (v0.10.0) reference from the human genome (GRCH38 reference database) to filter out the quality control of illumina sequencing data in Virosaurus download virus genome data sets for reference, bowtie2 (v2.3.4.1) (genome coverage >30%, depth >1X) was used to locate and analyze the post-host sequence, and then the "samtools idxstats" command was used to calculate the classification and relative abundance of viruses. Meanwhile, in order to obtain the annotation information of bacteria at the species level, PhyloFlash (v3.4) was used to calculate read counts for 16S rRNA genes in the SILVA database, selecting similarity greater than or equal to 98% as a threshold. Using eukaryotic pathogen genome database EUPATHDB46 as reference, bowtie2 and samtools were used for qualitative and quantitative analysis of fungal pathogens.
The criteria for determining the cause of respiratory infection are: (1) existing species known to be associated with human disease (ICD-10), (2) previously unidentified potential novel pathogens (only DNA and RNA viruses whose genera or families have previously been shown to infect mammals), and (3) possible symbiotic bacteria not included.
Analysis of AMR: by comparing the sequence similarity between the sequencing fragments and known drug resistance genes, the detection content can determine whether drug resistance genes exist, and suggest drug resistance caused by modification, inactivation, repression and other drug resistance genes.
Drug resistance genes detection: genes related to drug resistance recorded in CARD (Comprehensive Antibiotic Resistance Database) and ARG-ANNOT database. In this assay, only functional genes with drug resistance activities such as modification, inactivation, and repression, as well as pathway and target changes caused by some point mutations, were reported.
Genetic diversity was computed as the mean pairwise genetic distance within a group. Maximum likelihood phylogenetic trees were constructed using RaxML with a general time-reversible nucleotide substitution model and 1000 bootstraps. The genetic distance between sequences was calculated using MEGAX, with a bootstrap method for variance estimation.
- Keywords
- Pneumonia, Next-generation sequencing, Microbiome, Antimicrobial Resistance
- Medical subject headings
- Pneumonia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Severe pneumonia | Patients clinically diagnosed as severe pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA), who meet 1 of the following major criteria or ≥3 minor criteria can be diagnosed. The diagnostic criteria for severe pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011. | |
| Mild pneumonia | Patients clinically diagnosed as severe pneumonia and mild pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA). The diagnostic criteria for severe and mild pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011 |
What is being measured
The primary outcome is the main question the study is designed to answer.
Microbiome composition
a collection of microbial communities detected in the biospecimen
Measured: during the study period, 2019-2025
Secondary outcomes (3)
Alpha diversity
the diversity within a particular area or ecosystem
Measured: during the study period, 2019-2025
Prevalence of bacterial resistance genes
the number of bacterial resistance genes divided by the number of biospecimen
Measured: during the study period, 2019-2025
Beta diversity
a comparison of of diversity between ecosystems, usually measured as the amount of species change between the ecosystems
Measured: during the study period, 2019-2025
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Aug 2024
- Study start1 Aug 2024
- Primary completion15 Apr 2026
- Study completion30 Sep 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (19)Papers the sponsor has linked to this study.
- Other trials for PneumoniaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Other
- Enrolment
- 800 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shanghai General Hospital, China
- Sponsor type
- University, hospital or other
- Collaborators
- Wuxi People's Hospital Affiliated to Nanjing Medical University, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, The Central Hospital of Huanggang
- Responsible party
- Principal investigator, Mei Kang, Shanghai General Hospital, China
- Investigators
- Mei Kang, MPH, Principal investigator, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06566898
- Sponsor's protocol ID
- 2023234
- Status last verified
- Apr 2026
- First submitted
- 18 Aug 2024
- Last updated
- 23 Apr 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: The datasets used in this study are available upon request to the principle investigator.
Publications
GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020 Oct 17;396(10258):1204-1222. doi: 10.1016/S0140-6736(20)30925-9.
PubMed 33069326File TM Jr, Ramirez JA. Community-Acquired Pneumonia. N Engl J Med. 2023 Aug 17;389(7):632-641. doi: 10.1056/NEJMcp2303286. No abstract available.
PubMed 37585629Limmathurotsakul D, Dunachie S, Fukuda K, Feasey NA, Okeke IN, Holmes AH, Moore CE, Dolecek C, van Doorn HR, Shetty N, Lopez AD, Peacock SJ; Surveillance and Epidemiology of Drug Resistant Infections Consortium (SEDRIC). Improving the estimation of the global burden of antimicrobial resistant infections. Lancet Infect Dis. 2019 Nov;19(11):e392-e398. doi: 10.1016/S1473-3099(19)30276-2. Epub 2019 Aug 16.
PubMed 31427174Park DE, Higdon MM, Prosperi C, Baggett HC, Brooks WA, Feikin DR, Hammitt LL, Howie SRC, Kotloff KL, Levine OS, Madhi SA, Murdoch DR, O'Brien KL, Scott JAG, Thea DM, Antonio M, Awori JO, Baillie VL, Bunthi C, Kwenda G, Mackenzie GA, Moore DP, Morpeth SC, Mwananyanda L, Paveenkittiporn W, Ziaur Rahman M, Rahman M, Rhodes J, Sow SO, Tapia MD, Deloria Knoll M. Upper Respiratory Tract Co-detection of Human Endemic Coronaviruses and High-density Pneumococcus Associated With Increased Severity Among HIV-Uninfected Children Under 5 Years Old in the PERCH Study. Pediatr Infect Dis J. 2021 Jun 1;40(6):503-512. doi: 10.1097/INF.0000000000003139.
PubMed 33883479Chiu CY, Miller SA. Clinical metagenomics. Nat Rev Genet. 2019 Jun;20(6):341-355. doi: 10.1038/s41576-019-0113-7.
PubMed 30918369Li N, Cai Q, Miao Q, Song Z, Fang Y, Hu B. High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings. Small Methods. 2021 Jan 4;5(1):2000792. doi: 10.1002/smtd.202000792. Epub 2020 Dec 13.
PubMed 33614906Zhang YZ, Chen YM, Wang W, Qin XC, Holmes EC. Expanding the RNA Virosphere by Unbiased Metagenomics. Annu Rev Virol. 2019 Sep 29;6(1):119-139. doi: 10.1146/annurev-virology-092818-015851. Epub 2019 May 17.
PubMed 31100994Wu F, Zhao S, Yu B, Chen YM, Wang W, Song ZG, Hu Y, Tao ZW, Tian JH, Pei YY, Yuan ML, Zhang YL, Dai FH, Liu Y, Wang QM, Zheng JJ, Xu L, Holmes EC, Zhang YZ. A new coronavirus associated with human respiratory disease in China. Nature. 2020 Mar;579(7798):265-269. doi: 10.1038/s41586-020-2008-3. Epub 2020 Feb 3.
PubMed 32015508Boolchandani M, D'Souza AW, Dantas G. Sequencing-based methods and resources to study antimicrobial resistance. Nat Rev Genet. 2019 Jun;20(6):356-370. doi: 10.1038/s41576-019-0108-4.
PubMed 30886350Suzuki S, Horinouchi T, Furusawa C. Prediction of antibiotic resistance by gene expression profiles. Nat Commun. 2014 Dec 17;5:5792. doi: 10.1038/ncomms6792.
PubMed 25517437Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022 Feb 12;399(10325):629-655. doi: 10.1016/S0140-6736(21)02724-0. Epub 2022 Jan 19.
PubMed 35065702Howard A, Reza N, Aston S, Woods B, Gerada A, Buchan I, Hope W, Martson AG. Antimicrobial treatment imprecision: an outcome-based model to close the data-to-action loop. Lancet Infect Dis. 2024 Jan;24(1):e47-e58. doi: 10.1016/S1473-3099(23)00367-5. Epub 2023 Aug 31.
PubMed 37660712Serpa PH, Deng X, Abdelghany M, Crawford E, Malcolm K, Caldera S, Fung M, McGeever A, Kalantar KL, Lyden A, Ghale R, Deiss T, Neff N, Miller SA, Doernberg SB, Chiu CY, DeRisi JL, Calfee CS, Langelier CR. Metagenomic prediction of antimicrobial resistance in critically ill patients with lower respiratory tract infections. Genome Med. 2022 Jul 12;14(1):74. doi: 10.1186/s13073-022-01072-4.
PubMed 35818068Shi M, Zhao S, Yu B, Wu WC, Hu Y, Tian JH, Yin W, Ni F, Hu HL, Geng S, Tan L, Peng Y, Song ZG, Wang W, Chen YM, Holmes EC, Zhang YZ. Total infectome characterization of respiratory infections in pre-COVID-19 Wuhan, China. PLoS Pathog. 2022 Feb 17;18(2):e1010259. doi: 10.1371/journal.ppat.1010259. eCollection 2022 Feb.
PubMed 35176118Charalampous T, Alcolea-Medina A, Snell LB, Williams TGS, Batra R, Alder C, Telatin A, Camporota L, Meadows CIS, Wyncoll D, Barrett NA, Hemsley CJ, Bryan L, Newsholme W, Boyd SE, Green A, Mahadeva U, Patel A, Cliff PR, Page AJ, O'Grady J, Edgeworth JD. Evaluating the potential for respiratory metagenomics to improve treatment of secondary infection and detection of nosocomial transmission on expanded COVID-19 intensive care units. Genome Med. 2021 Nov 17;13(1):182. doi: 10.1186/s13073-021-00991-y.
PubMed 34784976
Study at a glance
From the registry record, last updated by the sponsor on 23 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients: a Genomic Epidemiology Study
- ClinicalTrials.gov ID
- NCT06566898
- Acronym / sponsor ID
- 2023234
- Keywords
- Pneumonia, Next-generation sequencing, Microbiome, Antimicrobial Resistance
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 800 participants (estimated)
- Lead sponsor
- Shanghai General Hospital, ChinaUniversity, hospital or other
- Collaborators
- Wuxi People's Hospital Affiliated to Nanjing Medical University, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, The Central Hospital of Huanggang
- Study start
- 1 Aug 2024 (actual)
- Primary completion
- 15 Apr 2026 (actual)
- Study completion
- 30 Sep 2026 (estimated)
- First posted
- 22 Aug 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Monitoring of antimicrobial resistance (AMR) based on metagenomics analyses in pneumonia patients is critical for optimizing clinical diagnosis and treatment and improving clinical prognosis. This study is designed to ask the following key questions:
- What is the microbiome maps of patients with severe pneumonia and mild pneumonia ?
- How many pathogen resistance genes are carrying in severe pneumonia and mild pneumonia ?
- What is the genetic diversity of key pathogens detected in severe pneumonia and mild pneumonia during 2019-2025?
Detailed description
This is a historical prospective obsevational study. Patients diagnosed with severe and mild pneumonia are recruited continously from four hospitals (Shanghai General Hospital, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuhan Union Hospital, and Huanggang Central Hospital) in China during March, 2019 to March, 2025.
Next-generation sequencing: Metagenomics and metatranscriptomic libraries undergo next-generation sequencing using the Illumina Novaseq 6000 platform.
Microbiome analysis: using KneadData (v0.10.0) reference from the human genome (GRCH38 reference database) to filter out the quality control of illumina sequencing data in Virosaurus download virus genome data sets for reference, bowtie2 (v2.3.4.1) (genome coverage >30%, depth >1X) was used to locate and analyze the post-host sequence, and then the "samtools idxstats" command was used to calculate the classification and relative abundance of viruses. Meanwhile, in order to obtain the annotation information of bacteria at the species level, PhyloFlash (v3.4) was used to calculate read counts for 16S rRNA genes in the SILVA database, selecting similarity greater than or equal to 98% as a threshold. Using eukaryotic pathogen genome database EUPATHDB46 as reference, bowtie2 and samtools were used for qualitative and quantitative analysis of fungal pathogens.
The criteria for determining the cause of respiratory infection are: (1) existing species known to be associated with human disease (ICD-10), (2) previously unidentified potential novel pathogens (only DNA and RNA viruses whose genera or families have previously been shown to infect mammals), and (3) possible symbiotic bacteria not included.
Analysis of AMR: by comparing the sequence similarity between the sequencing fragments and known drug resistance genes, the detection content can determine whether drug resistance genes exist, and suggest drug resistance caused by modification, inactivation, repression and other drug resistance genes.
Drug resistance genes detection: genes related to drug resistance recorded in CARD (Comprehensive Antibiotic Resistance Database) and ARG-ANNOT database. In this assay, only functional genes with drug resistance activities such as modification, inactivation, and repression, as well as pathway and target changes caused by some point mutations, were reported.
Genetic diversity was computed as the mean pairwise genetic distance within a group. Maximum likelihood phylogenetic trees were constructed using RaxML with a general time-reversible nucleotide substitution model and 1000 bootstraps. The genetic distance between sequences was calculated using MEGAX, with a bootstrap method for variance estimation.
Study design
- Observational model
- Case-control
- Time perspective
- Other
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Severe pneumonia | – | –Patients clinically diagnosed as severe pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA), who meet 1 of the following major criteria or ≥3 minor criteria can be diagnosed. The diagnostic criteria for severe pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011. |
| Mild pneumonia | – | –Patients clinically diagnosed as severe pneumonia and mild pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA). The diagnostic criteria for severe and mild pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011 |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Pneumonia patients from four centers in China during 2022-2025.
Key inclusion criteria (2 listed)
- Patients clinically diagnosed as severe pneumonia and mild pneumonia are diagnosed according to the Guidelines for the diagnosis and Treatment of community-acquired pneumonia in Adults (2019 edition) formulated by the American Thoracic Society (ATS) and the Infectious Diseases Society of America (IDSA), who meet 1 of the following major criteria or ≥3 minor criteria can be diagnosed. The diagnostic criteria for severe and mild pneumonia in children were adopted by the British Thoracic Society (BTS) in 2011.
- Clinical examination was performed, and there was biospecimen (nasopharyngeal swab, oropharyngeal swab, bronchoalveolar lavage fluid, sputum, blood, hydrothorax, lung tissue) remaining in the clinical microbiological examination.
Key exclusion criteria (2 listed)
- Patients whose biological samples may be contaminated;
- Patients with alveolar lavage fluid or hydrothorax volume less than 200μl.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Microbiome composition
Time frame: during the study period, 2019-2025
a collection of microbial communities detected in the biospecimen
3 secondary outcomes
Alpha diversity
Time frame: during the study period, 2019-2025
Prevalence of bacterial resistance genes
Time frame: during the study period, 2019-2025
Beta diversity
Time frame: during the study period, 2019-2025
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Apr 2026.
- Background: PubMed 33069326GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020 Oct 17;396(10258):1204-1222. doi: 10.1016/S0140-6736(20)30925-9.
- Background: PubMed 37585629File TM Jr, Ramirez JA. Community-Acquired Pneumonia. N Engl J Med. 2023 Aug 17;389(7):632-641. doi: 10.1056/NEJMcp2303286. No abstract available.
- Background: PubMed 31427174Limmathurotsakul D, Dunachie S, Fukuda K, Feasey NA, Okeke IN, Holmes AH, Moore CE, Dolecek C, van Doorn HR, Shetty N, Lopez AD, Peacock SJ; Surveillance and Epidemiology of Drug Resistant Infections Consortium (SEDRIC). Improving the estimation of the global burden of antimicrobial resistant infections. Lancet Infect Dis. 2019 Nov;19(11):e392-e398. doi: 10.1016/S1473-3099(19)30276-2. Epub 2019 Aug 16.
- Background: PubMed 33883479Park DE, Higdon MM, Prosperi C, Baggett HC, Brooks WA, Feikin DR, Hammitt LL, Howie SRC, Kotloff KL, Levine OS, Madhi SA, Murdoch DR, O'Brien KL, Scott JAG, Thea DM, Antonio M, Awori JO, Baillie VL, Bunthi C, Kwenda G, Mackenzie GA, Moore DP, Morpeth SC, Mwananyanda L, Paveenkittiporn W, Ziaur Rahman M, Rahman M, Rhodes J, Sow SO, Tapia MD, Deloria Knoll M. Upper Respiratory Tract Co-detection of Human Endemic Coronaviruses and High-density Pneumococcus Associated With Increased Severity Among HIV-Uninfected Children Under 5 Years Old in the PERCH Study. Pediatr Infect Dis J. 2021 Jun 1;40(6):503-512. doi: 10.1097/INF.0000000000003139.
- Background: PubMed 30918369Chiu CY, Miller SA. Clinical metagenomics. Nat Rev Genet. 2019 Jun;20(6):341-355. doi: 10.1038/s41576-019-0113-7.
- Background: PubMed 33614906Li N, Cai Q, Miao Q, Song Z, Fang Y, Hu B. High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings. Small Methods. 2021 Jan 4;5(1):2000792. doi: 10.1002/smtd.202000792. Epub 2020 Dec 13.
- Background: PubMed 31100994Zhang YZ, Chen YM, Wang W, Qin XC, Holmes EC. Expanding the RNA Virosphere by Unbiased Metagenomics. Annu Rev Virol. 2019 Sep 29;6(1):119-139. doi: 10.1146/annurev-virology-092818-015851. Epub 2019 May 17.
- Background: PubMed 32015508Wu F, Zhao S, Yu B, Chen YM, Wang W, Song ZG, Hu Y, Tao ZW, Tian JH, Pei YY, Yuan ML, Zhang YL, Dai FH, Liu Y, Wang QM, Zheng JJ, Xu L, Holmes EC, Zhang YZ. A new coronavirus associated with human respiratory disease in China. Nature. 2020 Mar;579(7798):265-269. doi: 10.1038/s41586-020-2008-3. Epub 2020 Feb 3.
- Background: PubMed 30886350Boolchandani M, D'Souza AW, Dantas G. Sequencing-based methods and resources to study antimicrobial resistance. Nat Rev Genet. 2019 Jun;20(6):356-370. doi: 10.1038/s41576-019-0108-4.
- Background: PubMed 25517437Suzuki S, Horinouchi T, Furusawa C. Prediction of antibiotic resistance by gene expression profiles. Nat Commun. 2014 Dec 17;5:5792. doi: 10.1038/ncomms6792.
- Background: PubMed 35065702Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022 Feb 12;399(10325):629-655. doi: 10.1016/S0140-6736(21)02724-0. Epub 2022 Jan 19.
- Background: PubMed 37660712Howard A, Reza N, Aston S, Woods B, Gerada A, Buchan I, Hope W, Martson AG. Antimicrobial treatment imprecision: an outcome-based model to close the data-to-action loop. Lancet Infect Dis. 2024 Jan;24(1):e47-e58. doi: 10.1016/S1473-3099(23)00367-5. Epub 2023 Aug 31.
- Individual participant dataSharing planned: Undecided. The datasets used in this study are available upon request to the principle investigator.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Mei Kang, MPH principal investigator
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pneumonia and Next-generation Sequencing, run by Shanghai General Hospital, China at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 23 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Mei Kang, MPH (18501709576, mei.kang@shgh.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Microbiome composition (time frame: during the study period, 2019-2025). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06566898, which also lists 19 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Apr 2026.