A Multi-center Clinical Evaluation of Polymerase chain reaction coupled with quantum dot fluorescence analysis and Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction for diagnosing pathogens in suspected respiratory infection patients

A Multi-center Clinical Evaluation of Polymerase chain reaction coupled with quantum dot fluorescence analysis and Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction for diagnosing pathogens in suspected respiratory infection patients | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 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Data may be preliminary. 25 April 2025 V1 Latest version Share on A Multi-center Clinical Evaluation of Polymerase chain reaction coupled with quantum dot fluorescence analysis and Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction for diagnosing pathogens in suspected respiratory infection patients Authors : Xinghan Huang , Haojie He , Wenjie Yang , Bangxing Lin , Junjie Lao , Guangzhi Du , Shenghai Wu , Yueming Chen , Xueyan Dong , Huiqiang Liang , Xianjun Wang , and Liqian Wang [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174558798.88439298/v1 329 views 198 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Our multi-center clinical study evaluated 19 common pathogens in 1,922 pharyngeal swab samples, comparing the diagnostic performance of PCR-QDFA with clinically routine qRT-PCR, while validating results using Sanger sequencing as the gold standard. Our statistical results showed that among the samples with single - pathogen infections (759 cases, 39.49%), the three most frequently detected pathogen types included 164 cases (8.53%) of severe acute respiratory syndrome coronavirus 2 (SARS - CoV - 2), 92 cases (4.79%) of Mycoplasma pneumoniae, and 71 cases (3.69%) of respiratory adenovirus. Among the samples with co - infections of two or more pathogens (1479 cases, 76.95%), the five most frequently detected pathogen types were 422 cases (21.96%) of influenza A virus infection, 291 cases (15.14%) of influenza A (H1N1) virus, 113 cases (5.88%) of influenza A (H3N2) virus, 107 cases (5.57%) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and 67 cases (3.49%) of Mycoplasma pneumoniae. PCR - QDFA showed extremely high sensitivity (100%) and specificity (greater than 99%) for the 19 respiratory pathogens. The coincidence rate with qRT - PCR detection was greater than 99%, and PCR - QDFA outperformed qRT - PCR in terms of sensitivity and specificity detection. [1]¿p#1 INTRODUCTION Respiratory tract infection (RTI) is one of the most common types of diseases in humans 1 . It can occur in people of any gender, age, and region, and is one of the main causes of morbidity and mortality worldwide 2 . The clinical symptoms and signs caused by respiratory tract infections are rather similar 3 . The main clinical manifestations include symptoms such as rhinitis, pharyngitis, laryngitis, and tonsillitis 4 . In severe cases, it can lead to tracheitis, bronchitis, and pneumonia, etc 5 . However, for infections caused by different pathogens, the treatment methods, curative effects, and disease courses are also not exactly the same 6 . It has been proven that most respiratory diseases are caused by pathogens other than bacteria, among which respiratory viruses are the most common 7 . Respiratory tract infections are divided into upper respiratory tract infections and lower respiratory tract infections 8 . Upper respiratory tract infections can be divided into viral ones (accounting for 70 - 80%) and bacterial ones (accounting for 20 - 25%) 9 . Acute upper respiratory tract infections include the common cold mainly manifested as acute nasopharyngitis, acute sinusitis, tonsillitis, laryngitis, pharyngitis, and epiglottitis, etc 10 . Acute lower respiratory tract infections include acute tracheobronchitis, bronchiolitis, and pneumonia 11 . Among them, pneumonia is the leading cause of death among children under 5 years old 12 . The common cold (commonly known as a cold) is usually caused by rhinoviruses, adenoviruses, respiratory syncytial viruses, etc. and is manifested as sneezing, runny nose, sore throat, and a few patients may have symptoms such as fatigue and low fever 13 . While influenza is caused by influenza viruses, with small epidemics or outbreaks, and symptoms such as high fever, general muscle aches, and conjunctivitis 14 . The statistical data released by the WHO in 2018 showed that lower respiratory tract infections are the fourth leading cause of death globally and the third leading cause of death among children under 5 years old in China, accounting for 19.4% of all causes of death 15 . Pathogenic agents include viruses, bacteria, mycoplasmas, and chlamydias 16 . Among the pathogens infecting children, viruses account for more than 70% 17 . In China, 20 - 60% of community-acquired pneumonia (CAP) cases cannot be diagnosed etiologically 18 . Acute respiratory infections are one of the infectious diseases widely distributed among adults and children, with rather high morbidity and mortality rates 19 . Most acute upper and lower respiratory tract diseases are mainly caused by respiratory viruses 20 . Traditionally, the main viral pathogens causing respiratory diseases include Influenza A virus ( IAV) and Influenza B virus (IBV), Human rhinovirus (HRV), Respiratory syncytial virus types A, B (RSV-A, RSV-B), Parainfluenza virus types 1, 2, 3(PIV-1, PIV-2, PIV-3), Human Adenovirus (HAdV), etc 21 . However, in the past decade, new respiratory viruses have been continuously discovered 22 . Human metapneumovirus (HMPV), Coronavirus (NL63, HKU1, OC43, 229E), Human bocavirus (HBoV), etc. have also become important pathogens of respiratory diseases, posing a great threat to human health 23 . Since December 2019, several cases of pneumonia of unknown cause with a history of exposure to the Huanan Seafood Market have been successively discovered in some hospitals in Wuhan, Hubei Province 24 . It has now been confirmed to be an acute respiratory infectious disease caused by a novel coronavirus infection 25 . Since the infection symptoms and epidemic symptoms caused by these viruses are similar, it is very unreliable to determine the viral pathogens solely based on clinical symptoms and conventional detection methods 26 .Traditional detection methods have many problems, such as being complex, time-consuming, technically difficult, having low sensitivity, and being unable to detect multiple pathogens in a single specimen 27 . Respiratory pathogen coinfections are common, especially in developing countries 28 . Molecular diagnostic methods, especially real-time PCR, have attracted much attention due to their rapidity, sensitivity, and specificity 29 . Molecular diagnostic methods, especially Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (qRT-PCR), are often used for the nucleic acid detection of respiratory pathogens in clinical settings due to their advantages such as rapidity, sensitivity, and specificity 30 . However, qRT-PCR based on fluorescent probes has issues like high costs, complex probe synthesis, and a high false-negative rate 31 . Although qRT-PCR based on fluorescent dyes has a cost advantage, currently, due to the limitations of instrument recognition capabilities, a single reaction can detect at most 2 - 3 pathogens simultaneously 32 . Therefore, there is an urgent need for a method that can simultaneously detect traditional and novel respiratory pathogens, with both high sensitivity and high specificity, so as to provide laboratory evidence for clinical diagnosis and prevent nosocomial infections. [1]¿p#1 METHODS Clinical Samples Figure1 is the flowchart of our clinical trial. This clinical trial is a multi-center clinical trial. The research subjects are patients with suspected respiratory tract infections in Hangzhou First People’s Hospital, Jiangmen Wuyi Traditional Chinese Medicine Hospital and Jiangmen Central Hospital from September 2022 to August 2023. Sample size: 705 in Hangzhou First People’s Hospital, 502 in Jiangmen Central Hospital and 715 in Jiangmen Wuyi Traditional Chinese Medicine Hospital. A total of 1,922 individual throat swab samples were collected.The selected samples are throat swab samples from people with various suspected or confirmed respiratory tract infections in clinical diagnosis and treatment as well as those without relevant clinical symptoms or from healthy people. Generally, it is required that the number of positive samples should not be less than 30% of the sample size. There should be no fewer than 30 samples that are determined to be positive for influenza virus by the method of virus isolation and culture. Based on the sample size estimation, it is determined that the sample size for this clinical trial is approximately 1,800 cases. The clinical trial will be carried out in at least three clinical institutions, and the number of clinical samples undertaken by each clinical institution needs to be balanced. Experimental procedures This experiment adopted a multi - center, synchronous blinded, comparative trial design. By qualitatively detecting the nucleic acid RNA/DNA of 19 respiratory pathogens in vitro, the detection results of the two groups, PCR - QDFA and qRT - PCR, were statistically analyzed to evaluate the detection accuracy of PCR - QDFA in clinical applications. For samples with inconsistent results between PCR - QDFA and qRT - PCR, the Sanger sequencing method was used for re - examination (Figure 1). qRT-PCR assay qRT - PCR combines reverse transcription and real - time fluorescence quantitative PCR, mainly used for the quantitative detection of RNA. Reverse transcriptase is used to convert the RNA template into complementary DNA. A fluorescent marker is added to the PCR reaction system to monitor the change of the fluorescence signal in real - time during the amplification process. After the probe binds to the target DNA, Taq enzyme hydrolyzes the probe, releasing the fluorescent group and enhancing the fluorescence signal. The fluorescence signal is collected in each round of PCR cycles, and the instrument plots a curve of fluorescence intensity versus the number of cycles. PCR-QDFA assay PCR - QDFA utilize the unique fluorescence characteristics of quantum dots to replace traditional fluorescent dyes or probes. Similar to traditional PCR, the target DNA is exponentially amplified in a thermal cycler using primers, DNA polymerase, and dNTPs. The PCR amplification generates the target DNA. Biotinylated probes bind to the target DNA and undergo a hybridization reaction. Streptavidin - modified quantum dots bind to the probe - target complex through the biotin - streptavidin interaction. The quantum dot signal is read by a fluorescence spectrometer, and the signal intensity is positively correlated with the target concentration. Statistical analysis In this study, we compared the clinical detection performance of the PCR - QDFA method and qRT - PCR using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), coincidence rate, and kappa value. IBM SPSS Statistics 29.0.2 (Z - test) was used for statistical analysis. RESULTS Detection of respiratory pathogens Figure 2 shows the pathogen species of 1922 throat swab samples from clinical trials with suspected respiratory infections. The following is the etiological presentation of all positive results. We detected 759 (39.49%) samples with a single pathogen. The three most frequently detected pathogen types included 164 cases (8.53%) of Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2), 92 cases (4.79%) of Mycoplasma pneumoniae, and 71 cases (3.69%) of Human Adenovirus. Other detection results included 39 cases (2.03%) of Respiratory syncytial virus A, 47 cases (2.45%) of Respiratory syncytial virus B, 19 cases (0.99%) of Influenza A virus, 26 cases (1.35%) of Influenza B virus, 28 cases (1.46%) of Parainfluenza virus types I, 17 cases (0.88%) of Parainfluenza virus types II, 38 cases (1.98%) of Parainfluenza virus types III, 63 cases (3.28%) of Coronavirus, 31 cases (1.61%) of Human rhinovirus, 29 cases (1.51%) of Human bocavirus, 25 cases (1.30%) of Bordetella pertussis, 22 cases (1.14%) of Human metapneumovirus, 35 cases (1.82%) of Legionella pneumophila, and 13 cases (0.68%) of Chlamydia pneumoniae. A total of 1,479 (76.95%) samples were detected with two or more pathogens simultaneously. Among them, the five most frequently detected pathogen types in co - infections were 422 cases (21.96%) of Influenza A virus, 291 cases (15.14%) of Influenza A virus subtype H1N1, 113 cases (5.88%) of Influenza A virus subtype H3N2, 107 cases (5.57%) of severe acute respiratory syndrome SARS-CoV-2, and 67 cases (3.49%) of Mycoplasma pneumoniae. Other detection results included 58 cases (3.02%) of Human Adenovirus, 38 cases (1.98%) of Coronavirus, 58 cases (3.02%) of Respiratory syncytial virus A, 49 cases (2.55%) of Respiratory syncytial virus B, 39 cases (2.03%) of Human rhinovirus, 28 cases (1.46%) of Parainfluenza virus types III, 30 cases (1.56%) of Human bocavirus, 32 cases (1.66%) of Bordetella pertussis, 30 cases (1.56%) of Influenza B virus, 38 cases (1.98%) of Human metapneumovirus, 31 cases (1.61%) of Parainfluenza virus types II, 17 cases (0.88%) of Parainfluenza virus types I, 10 cases (0.52%) of Legionella pneumophila, and 21 cases (1.09%) of Chlamydia pneumoniae.It should be noted that the samples of H1N1 (2009) and H3N2 were double - counted with those of Influenza A virus. Performance of PCR-QDFA for the identification of pathogens compared with qRT-PCR Table1 shows the overall performance of PCR-QDFA and qRT-PCR in the detection of 19 pathogens. For Influenza A virus, the sensitivity of PCR - QDFA is 100.00%, the specificity is 99.93%, and the coincidence rate with the detection results of qRT - PCR is 99.74%. For Influenza B virus, the sensitivity of PCR - QDFA is 100.00%, the specificity is 100%, and the coincidence rate is 99.95%. For H1N1, the sensitivity of PCR - QDFA is 100.00%, the specificity is 99.94%, and the coincidence rate is 99.74%. For H3N2, the sensitivity of PCR - QDFA is 100%, and the specificity is 100%. For Parainfluenza virus types 1, the sensitivity of PCR - QDFA is 100%, the specificity is 99.95%, and the coincidence rate is 99.95%. For Parainfluenza virus types 2, the sensitivity of PCR - QDFA is 100%, the specificity is 100%, and the coincidence rate is 100%. For Parainfluenza virus types 3, the sensitivity of PCR - QDFA is 100.00%, the specificity is 99.89%, and the coincidence rate is 99.84%. For Respiratory syncytial virus types A, the sensitivity of PCR - QDFA is 100.00%, the specificity is 99.95%, and the coincidence rate is 99.79%. For Respiratory syncytial virus types B, the sensitivity of PCR - QDFA is 100%, the specificity is 99.95%, and the coincidence rate is 99.84%. For Human bocavirus, the sensitivity of PCR - QDFA is 100%, the specificity is 100%, and the coincidence rate is 99.95%. For Human metapneumovirus, the sensitivity of PCR - QDFA is 100.00%, the specificity is 99.95%, and the coincidence rate is 99.90%. For Human rhinovirus, the sensitivity of PCR - QDFA is 100%, the specificity is 99.89%, and the coincidence rate is 99.84%. For Human Adenovirus, the sensitivity of PCR - QDFA is 100.00%, the specificity is 99.78%, and the coincidence rate is 99.69%. For SARS - COV2 virus, the sensitivity of PCR - QDFA is 100.00%, the specificity is 99.95%, and the coincidence rate is 99.95%. For Coronavirus, the sensitivity of PCR - QDFA is 100%, and the specificity is 100%. For Mycoplasma pneumoniae, the sensitivity of PCR - QDFA is 100.00%, the specificity is 99.77%, and the coincidence rate is 99.74%. For Chlamydia pneumoniae, the sensitivity of PCR - QDFA is 100%, the specificity is 99.95%, and the coincidence rate is 99.95%. For Bordetella pertussis, the sensitivity of PCR - QDFA is 100%, the specificity is 99.95%, and the coincidence rate is 99.84%. For Legionella pneumophila, the sensitivity of PCR - QDFA is 100%, and the specificity is 100% (Table 1). The kappa value is an important indicator for measuring the consistency between two diagnostic methods[38]. We compared the diagnostic performance of the PCR - QDFA and the qRT - PCR, and calculated that the kappa value is between 0.97 - 1.0, which means that the diagnostic performance of the two is almost completely consistent. The detection rate of respiratory pathogens and odds ratios (ORs) in patients with PCR-QDFA and qRT-PCR Figure 3 shows The detection rate of respiratory pathogens and odds ratios (ORs) in patients with PCR-QDFA and qRT-PCR. There were no significant statistical differences in the detection rates of the 16 viruses between PCR - QDFA and qRT - PCR (Z - test, all P - values > 0.05). The odds ratio (OR value) fluctuated between 1.0 and 1.02 (and all 95% confidence intervals included 1). Except for influenza A virus and respiratory syncytial virus type A, the detection rates of the PCR - QDFA group and the qRT - PCR group for the remaining viruses were completely identical. This indicates that the experimental group and the control group showed similar performance in the detection rates of these 16 viruses, and may have similar detection effects in practical applications. DISCUSSION In this study, we used the blood pathogens nucleic acid detection kit (PCR - QDFA) (Qianji Biotech), which can be used for the qualitative detection of the nucleic acids of 19 respiratory infection pathogens in human pharyngeal swab samples. The specific pathogens to be detected are as follows: Influenza A virus, Influenza A virus subtype H1N1 (2009), Influenza A virus subtype H3N2, Influenza B virus, Parainfluenza virus (types 1, 2, 3), Human metapneumovirus, Respiratory syncytial virus (types A, B), Coronavirus (229E, NL63, HKU1, OC43), Human rhinovirus, Human bocavirus, Human Adenovirus (types B, C, E), Mycoplasma pneumoniae, Chlamydia pneumoniae, Legionella pneumophila, Bordetella pertussis, Severe acute respiratory syndrome coronavirus 2. In this study, we collected a total of 1,922 pharyngeal swab samples from 3 centers. By comparing the detection performance of PCR - QDFA and qRT - PCR for these 19 respiratory pathogens, we found that PCR - QDFA showed excellent diagnostic performance. Its sensitivity for the pathogens within the detection range exceeded 99%, the specificity was over 99%, and the detection coincidence rate with the control reagent was above 99% (the kappa value is between 0.97 - 1.0). The sensitivity of PCR - QDFA for Influenza A virus and Respiratory syncytial virus types A was higher than that of qRT - PCR, and its specificity for Influenza A virus, Influenza B virus, Influenza A virus subtype H1N1 (2009), Respiratory syncytial virus types B, Human bocavirus, SARS - CoV - 2, and Bordetella pertussis was higher than that of qRT - PCR. The specificity of qRT - PCR for Parainfluenza virus types 1, Parainfluenza virus types 3, Human rhinovirus, Human Adenovirus, Mycoplasma pneumoniae, and Chlamydia pneumoniae was higher than that of PCR - QDFA. It is worth noting that for Legionella pneumophila, Coronavirus, and Influenza A virus subtype H3N2, we used PCR - QDFA and Sanger sequencing methods for detection. When detecting respiratory pathogens in human pharyngeal swab samples, PCR - QDFA supports the simultaneous detection of multiple pathogens 33 . The multicolor fluorescence of different quantum dots enables the simultaneous detection of multiple targets. It has ultra - high sensitivity and is suitable for samples with low pathogen loads. The fluorescence intensity of quantum dots is 10 - 100 times that of traditional dyes, making it suitable for trace detection, that is, the detection of target substances at extremely low concentrations in samples. Usually, it refers to the situation where the target concentration is close to or lower than the detection limit of conventional methods. It can be used for the early diagnosis of infections, such as the early stage of viral infections with extremely low pathogen loads or the screening of asymptomatic carriers, that is, when the host harbors the pathogen but has not developed symptoms and the target concentration in the sample is extremely low 34 . PCR - QDFA has strong anti - interference ability 35 . Pharyngeal swab samples contain a large amount of interfering substances such as host cells, mucus, and enzyme inhibitors, which can easily interfere with the reverse transcription process of qRT - PCR. In contrast, PCR - QDFA uses an end - point detection method. After PCR amplification is completed, quantum dot probe hybridization is carried out, and the probe directly binds to the target sequence, resulting in fewer interfering factors in this process. In terms of the operation process, PCR - QDFA has more advantages 36 . It does not require real - time monitoring equipment and can process a large number of samples simultaneously. Combined with an automated platform, high - throughput screening can be achieved. qRT - PCR requires a real - time fluorescent PCR instrument, and each round of experiments needs to be monitored, which limits the throughput 37 . PCR - QDFA also has potential cost advantages. Its quantum dot probes can be reused, and the long - term use cost is lower than that of TaqMan probes 38 . Moreover, it does not require a real - time PCR instrument. PCR - QDFA also has several limitations. In our study, PCR - QDFA can only detect 19 types of respiratory pathogens, falling short of covering all species of respiratory pathogens. It is unable to detect pathogens beyond its detection scope, nor can it identify viruses with gene mutations. Secondly, PCR - QDFA has a minimum detection limit of copies/ml for pathogenic bacteria, rendering it incapable of detecting samples with concentrations below this limit. According to our statistical results, among the 1922 samples, PCR - QDFA detected 15 false - positive results, while qRT - PCR detected 24 false - positive and 1 false - negative result. The small number of false - positive results detected by PCR - QDFA may stem from the fact that its high sensitivity amplifies the risk of contamination 39 . Even trace amounts of residual amplification products, such as those from aerosol contamination or operational contamination, may be misjudged as positive. For instance, if there is contamination from previous amplification products in the laboratory environment, the high sensitivity of quantum dots will significantly increase the probability of false - positives. It could also be due to sample cross - contamination. In the detection of multiple pathogens, the complex sample - processing steps may lead to cross - contamination among samples. The small number of false - positive results of qRT - PCR may also occur during the reverse - transcription process 40 . We believe that false - positive results can be reduced by optimizing the experimental design and strengthening contamination control, thus making the results more reliable. Digital PCR (dPCR) is a novel PCR technology that achieves absolute quantification through microdroplet partitioning, with sensitivity reaching the single-copy level, making it ideal for detecting trace pathogens, such as low-abundance pathogens in asymptomatic individuals or early-stage infections in throat swab samples. The partitioning feature of dPCR minimizes the impact of inhibitors on amplification efficiency and enables precise quantification of pathogen load without requiring a standard curve 41 . For respiratory pathogen detection in throat swabs, PCR-QDFA leverages the multicolor labeling capability of quantum dot fluorescent probes to simultaneously screen multiple pathogens, such as influenza viruses and Mycoplasma, offering high-throughput and low-cost advantages. In contrast, dPCR effectively reduces interference from sample inhibitors through microdroplet partitioning, achieving ultra-high sensitivity and absolute quantification, albeit with higher costs and lower throughput 42 . Looking ahead, PCR-QDFA could serve as a rapid initial screening tool for common pathogens, while dPCR could be applied to validate positive samples or detect rare mutant strains, forming a hierarchical diagnostic system of ”broad-spectrum screening + precise confirmation.” Future advancements, such as integrating quantum dot fluorescence detection modules into microfluidic chips, developing automated integrated devices, or optimizing signal analysis with AI algorithms, hold promise for improving detection efficiency while reducing costs 43,44 . These innovations could drive the field of respiratory infection diagnostics toward high sensitivity, multi-target capability, and full automation. Abbreviations: PCR-QDFA: Polymerase chain reaction coupled with quantum dot fluorescence analysis; qRT-PCR: Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction; RTI: Respiratory tract infection; IAV: Influenza A virus; H1N1 2009: Influenza A virus subtype H1N1 (2009 pandemic strain); H3N2: Influenza A virus subtype H3N2; IBV: Influenza B virus; PIV-1, PIV-2, PIV-3: Parainfluenza virus (types 1, 2, 3); HMPV: Human metapneumovirus; RSV-A, RSV-B: Respiratory syncytial virus (types A, B); CoV: Coronavirus; HRV: Human rhinovirus; HBoV: Human bocavirus; HAdV-B, HAdV-C, HAdV-E: Human Adenovirus (types B, C, E); M. pneumoniae: Mycoplasma pneumoniae; C. pneumoniae: Chlamydia pneumoniae; L. pneumophila: Legionella pneumophila; B. pertussis: Bordetella pertussis; SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2. Figure 1 Flowchart of Clinical trial [1]¿p#1 Figure 2 Pathogen detection of throat swab samples from individuals suspected or diagnosed with respiratory tract infections in clinic. The dark shade represents single detection, while the light shade represents co-detection. IAV, Influenza A virus; IBV, Influenza B virus; H1N1 (2009), Influenza A virus subtype H1N1 (2009 pandemic strain); H3N2, Influenza A virus subtype H3N2; PIV-1, PIV-2, PIV-3, Parainfluenza virus (types 1, 2, 3); RSV-A, RSV-B, Respiratory syncytial virus (types A, B); CoV, Coronavirus; SARS-CoV-2, Severe acute respiratory syndrome coronavirus 2; HMPV, Human metapneumovirus; HRV, Human rhinovirus; HBoV, Human bocavirus; HAdV, Human Adenovirus; M. pneumoniae, Mycoplasma pneumoniae; C. pneumoniae, Chlamydia pneumoniae; L. pneumophila, Legionella pneumophila; B. pertussis, Bordetella pertussis. Table 1 PPV, positive predictive value; NPV, negative predictive value; NA, not applicable. +/+ represents the number of episodes in which both Sanger sequencing or qRT-PCR and PCR-QDFA were positive. +/− represents the number of episodes in which Sanger sequencing or qRT-PCR was positive, but PCR-QDFA was negative. −/+ represents the number of episodes in which Sanger sequencing or qRT-PCR was negative, but PCR-QDFA was positive. −/− represents the number of episodes in which both Sanger sequencing or qRT-PCR and PCR-QDFA were negative. Figure 3 The detection rate of respiratory pathogens and odds ratios (ORs) in patients with PCR-QDFA and qRT-PCR. Author Contributions Wang, Liqian and Wang, Xianjun designed the study and directed the database; Huang, Xinghan collected the data related to this manuscript, analyzed the data and wrote the manuscript; He, Haojie analyzed the data and designed the figure; Wang, Liqian and Wang, Xianjun is the corresponding author and responsible for the content of this article. All authors have approved the final manuscript. [1]¿p#1 Funding This study was supported by Zhejiang Medicine and Health Project (2023KY168). Competing interests All authors have no conflicts of interest to declare. [1]¿p#1 Patient consent Waiver of informed consent. Ethics approval This study was conducted in accordance with the Declaration of Helsinki and was reviewed and approved by the Research Ethics Committee of the Hangzhou First People’s Hospital (2022-016-01), Jiangmen Wuyi Hospital of Traditional Chinese Medicine (GCP 2021-60) and Jiangmen Central Hospital (202213A). 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Front Bioeng Biotechnol . 2022;10:947895. doi:10.3389/fbioe.2022.947895 Information & Authors Information Version history V1 Version 1 25 April 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Journal of Medical Virology Keywords epidemiology pathogenesis respiratory tract sars coronavirus virus classification Authors Affiliations Xinghan Huang Fourth School of Clinical Medicine View all articles by this author Haojie He Fourth School of Clinical Medicine View all articles by this author Wenjie Yang Fourth School of Clinical Medicine View all articles by this author Bangxing Lin Fourth School of Clinical Medicine View all articles by this author Junjie Lao Hangzhou First People's Hospital View all articles by this author Guangzhi Du Fourth School of Clinical Medicine View all articles by this author Shenghai Wu Hangzhou First People's Hospital View all articles by this author Yueming Chen Hangzhou First People's Hospital View all articles by this author Xueyan Dong Hangzhou First People's Hospital View all articles by this author Huiqiang Liang Jiangmen Central Hospital View all articles by this author Xianjun Wang Hangzhou First People's Hospital View all articles by this author Liqian Wang [email protected] Hangzhou First People's Hospital View all articles by this author Metrics & Citations Metrics Article Usage 329 views 198 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Xinghan Huang, Haojie He, Wenjie Yang, et al. 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