Determination of Ideal Factors for Early Adoption and Standardization of Metagenomic Next-generation Sequencing for Respiratory System Infections


Cite item

Full Text

Abstract

Background:Metagenomic next-generation sequencing (mNGS) demonstrates great promise as a diagnostic tool for determining the cause of pathogenic infections. The standard diagnostic procedures (SDP) include smears and cultures and are typically viewed as less sensitive and more time-consuming when compared to mNGS. There are concerns about the logistics and ease of transition from SDP to mNGS. mNGS lacks standardization of collection processes, databases, and sequencing. Additionally, there is the burden of training clinicians on interpreting mNGS results.

Objective:Until now, few studies have explored factors that could be used as early adoption candidates to ease the transition between SDP and mNGS. This study evaluated 123 patients who had received both SDP and mNGS and compared several variables across a diagnostic test evaluation.

Methods:The diagnostic test evaluation observed metrics such as sensitivity, specificity, positive and negative likelihood ratios (PLR, NLR), positive and negative predictive values (PPV, NPV), and accuracy. Factors included various sample sources such as bronchoalveolar lavage fluid (BALF), lung tissue, and cerebral spinal fluid (CSF). An additional factor observed was the patient's immune status.

Results:Pathogen detection was found to be significantly greater for mNGS for total patients, BALF sample source, CSF sample source, and non-immunocompromised patients (p(<0.05). Pathogen detection was found to be insignificant for lung tissue sample sources and immunocompromised patients. Sensitivity, PLR, NLR, PPV, NPV, and accuracy appeared to be higher with mNGS for the total patients, BALF sample source, and non-immunocompromised patients when compared with SDP (p(<0.05).

Conclusion:With higher metrics in sensitivity, specificity, PLR, NLR, PPV, NPV, and accuracy for overall patients, mNGS may prove a better diagnostic tool than SDP. When addressing sample sources, mNGS for BALF-collected samples appeared to have higher scores than SDP for the same metrics. When patients were in a non-immunocompromised state, mNGS also demonstrated greater diagnostic benefits to BALF and overall patients compared to SDP. This study demonstrates that using BALF as a sample source and selecting non-immunocompromised patients may prove beneficial as early adoption factors for mNGS standard protocol. Such a study may pave the road for mNGS as a routine clinical method for determining the exact pathogenic etiology of lung infections.

About the authors

Lei Zhao

The Department of Respiratory Medicine, the 2nd People’s Hospital of Hefei and Hefei Hospital Affiliated to Anhui Medical University

Email: info@benthamscience.net

Cole Formslag

Department of Microbiology, Immunology & Pathology, Des Moines University

Email: info@benthamscience.net

Qing Zhang

The Department of Respiratory Medicine, the 2nd People’s Hospital of Hefei and Hefei Hospital Affiliated to Anhui Medical University

Email: info@benthamscience.net

Braydon Cowan

Department of Surgery, University of Missouri School of Medicine

Email: info@benthamscience.net

Trenton Mayberry

Department of Surgery, University of Missouri School of Medicine

Email: info@benthamscience.net

Aaron Barnhill

Department of Surgery, University of Missouri School of Medicine

Email: info@benthamscience.net

Yongsheng Wang

The Department of Respiratory Medicine, the 2nd People’s Hospital of Hefei and Hefei Hospital Affiliated to Anhui Medical University

Author for correspondence.
Email: info@benthamscience.net

Yujiang Fang

Department of Microbiology, Immunology & Pathology, Des Moines University

Author for correspondence.
Email: info@benthamscience.net

References

  1. Lozano, R.; Naghavi, M.; Foreman, K.; Lim, S.; Shibuya, K.; Aboyans, V.; Abraham, J.; Adair, T.; Aggarwal, R.; Ahn, S.Y.; AlMazroa, M.A.; Alvarado, M.; Anderson, H.R.; Anderson, L.M.; Andrews, K.G.; Atkinson, C.; Baddour, L.M.; Barker-Collo, S.; Bartels, D.H.; Bell, M.L.; Benjamin, E.J.; Bennett, D.; Bhalla, K.; Bikbov, B.; Abdulhak, A.B.; Birbeck, G.; Blyth, F.; Bolliger, I.; Boufous, S.; Bucello, C.; Burch, M.; Burney, P.; Carapetis, J.; Chen, H.; Chou, D.; Chugh, S.S.; Coffeng, L.E.; Colan, S.D.; Colquhoun, S.; Colson, K.E.; Condon, J.; Connor, M.D.; Cooper, L.T.; Corriere, M.; Cortinovis, M.; de Vaccaro, K.C.; Couser, W.; Cowie, B.C.; Criqui, M.H.; Cross, M.; Dabhadkar, K.C.; Dahodwala, N.; De Leo, D.; Degenhardt, L.; Delossantos, A.; Denenberg, J.; Des Jarlais, D.C.; Dharmaratne, S.D.; Dorsey, E.R.; Driscoll, T.; Duber, H.; Ebel, B.; Erwin, P.J.; Espindola, P.; Ezzati, M.; Feigin, V.; Flaxman, A.D.; Forouzanfar, M.H.; Fowkes, F.G.R.; Franklin, R.; Fransen, M.; Freeman, M.K.; Gabriel, S.E.; Gakidou, E.; Gaspari, F.; Gillum, R.F.; Gonzalez-Medina, D.; Halasa, Y.A.; Haring, D.; Harrison, J.E.; Havmoeller, R.; Hay, R.J.; Hoen, B.; Hotez, P.J.; Hoy, D.; Jacobsen, K.H.; James, S.L.; Jasrasaria, R.; Jayaraman, S.; Johns, N.; Karthikeyan, G.; Kassebaum, N.; Keren, A.; Khoo, J-P.; Knowlton, L.M.; Kobusingye, O.; Koranteng, A.; Krishnamurthi, R.; Lipnick, M.; Lipshultz, S.E.; Ohno, S.L.; Mabweijano, J.; MacIntyre, M.F.; Mallinger, L.; March, L.; Marks, G.B.; Marks, R.; Matsumori, A.; Matzopoulos, R.; Mayosi, B.M.; McAnulty, J.H.; McDermott, M.M.; McGrath, J.; Memish, Z.A.; Mensah, G.A.; Merriman, T.R.; Michaud, C.; Miller, M.; Miller, T.R.; Mock, C.; Mocumbi, A.O.; Mokdad, A.A.; Moran, A.; Mulholland, K.; Nair, M.N.; Naldi, L.; Narayan, K.M.V.; Nasseri, K.; Norman, P.; O’Donnell, M.; Omer, S.B.; Ortblad, K.; Osborne, R.; Ozgediz, D.; Pahari, B.; Pandian, J.D.; Rivero, A.P.; Padilla, R.P.; Perez-Ruiz, F.; Perico, N.; Phillips, D.; Pierce, K.; Pope, C.A., III; Porrini, E.; Pourmalek, F.; Raju, M.; Ranganathan, D.; Rehm, J.T.; Rein, D.B.; Remuzzi, G.; Rivara, F.P.; Roberts, T.; De León, F.R.; Rosenfeld, L.C.; Rushton, L.; Sacco, R.L.; Salomon, J.A.; Sampson, U.; Sanman, E.; Schwebel, D.C.; Segui-Gomez, M.; Shepard, D.S.; Singh, D.; Singleton, J.; Sliwa, K.; Smith, E.; Steer, A.; Taylor, J.A.; Thomas, B.; Tleyjeh, I.M.; Towbin, J.A.; Truelsen, T.; Undurraga, E.A.; Venketasubramanian, N.; Vijayakumar, L.; Vos, T.; Wagner, G.R.; Wang, M.; Wang, W.; Watt, K.; Weinstock, M.A.; Weintraub, R.; Wilkinson, J.D.; Woolf, A.D.; Wulf, S.; Yeh, P-H.; Yip, P.; Zabetian, A.; Zheng, Z-J.; Lopez, A.D.; Murray, C.J.L. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet, 2012, 380(9859), 2095-2128. doi: 10.1016/S0140-6736(12)61728-0 PMID: 23245604
  2. Gu, W.; Deng, X.; Lee, M.; Sucu, Y.D.; Arevalo, S.; Stryke, D.; Federman, S.; Gopez, A.; Reyes, K.; Zorn, K.; Sample, H.; Yu, G.; Ishpuniani, G.; Briggs, B.; Chow, E.D.; Berger, A.; Wilson, M.R.; Wang, C.; Hsu, E.; Miller, S.; DeRisi, J.L.; Chiu, C.Y. Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids. Nat. Med., 2021, 27(1), 115-124. doi: 10.1038/s41591-020-1105-z PMID: 33169017
  3. Li, H.; Gao, H.; Meng, H.; Wang, Q.; Li, S.; Chen, H.; Li, Y.; Wang, H. Detection of Pulmonary Infectious Pathogens From Lung Biopsy Tissues by Metagenomic Next-Generation Sequencing. Front. Cell. Infect. Microbiol., 2018, 8(205), 205. doi: 10.3389/fcimb.2018.00205 PMID: 29988504
  4. Lanks, C.W.; Musani, A.I.; Hsia, D.W. Community-acquired Pneumonia and Hospital-acquired Pneumonia. Med. Clin. North Am., 2019, 103(3), 487-501. doi: 10.1016/j.mcna.2018.12.008 PMID: 30955516
  5. Bohmwald, K.; Gálvez, N.M.S.; Ríos, M.; Kalergis, A.M. Neurologic Alterations Due to Respiratory Virus Infections. Front. Cell. Neurosci., 2018, 12, 386. doi: 10.3389/fncel.2018.00386 PMID: 30416428
  6. Gu, X.; Zhou, F.; Wang, Y.; Fan, G.; Cao, B. Respiratory viral sepsis: Epidemiology, pathophysiology, diagnosis and treatment. Eur. Respir. Rev., 2020, 29(157), 200038. doi: 10.1183/16000617.0038-2020 PMID: 32699026
  7. Berube, B.J.; Rangel, S.M.; Hauser, A.R. Pseudomonas aeruginosa: Breaking down barriers. Curr. Genet., 2016, 62(1), 109-113. doi: 10.1007/s00294-015-0522-x PMID: 26407972
  8. McCray, P.B., Jr; Pewe, L.; Wohlford-Lenane, C.; Hickey, M.; Manzel, L.; Shi, L.; Netland, J.; Jia, H.P.; Halabi, C.; Sigmund, C.D.; Meyerholz, D.K.; Kirby, P.; Look, D.C.; Perlman, S. Lethal infection of K18-hACE2 mice infected with severe acute respiratory syndrome coronavirus. J. Virol., 2007, 81(2), 813-821. doi: 10.1128/JVI.02012-06 PMID: 17079315
  9. Riccobono, E.; Bussini, L.; Giannella, M.; Viale, P.; Rossolini, G.M. Rapid diagnostic tests in the management of pneumonia. Expert Rev. Mol. Diagn., 2022, 22(1), 49-60. doi: 10.1080/14737159.2022.2018302 PMID: 34894965
  10. Ahmad, F.B.; Anderson, R.N. The Leading Causes of Death in the US for 2020. JAMA, 2021, 325(18), 1829-1830. doi: 10.1001/jama.2021.5469 PMID: 33787821
  11. Lyons, P.G.; Kollef, M.H. Prevention of hospital-acquired pneumonia. Curr. Opin. Crit. Care, 2018, 24(5), 370-378. doi: 10.1097/MCC.0000000000000523 PMID: 30015635
  12. Liu, J.Y.; Dickter, J.K. Nosocomial Infections. Gastrointest. Endosc. Clin. N. Am., 2020, 30(4), 637-652. doi: 10.1016/j.giec.2020.06.001 PMID: 32891222
  13. Arevalo-Rodriguez, I.; Buitrago-Garcia, D.; Simancas-Racines, D.; Zambrano-Achig, P.; Del Campo, R.; Ciapponi, A.; Sued, O.; Martinez-García, L.; Rutjes, A.W.; Low, N.; Bossuyt, P.M.; Perez-Molina, J.A.; Zamora, J. False-negative results of initial RT-PCR assays for COVID-19: A systematic review. PLoS One, 2020, 15(12), e0242958. doi: 10.1371/journal.pone.0242958 PMID: 33301459
  14. Wormanns, D.; Diederich, S. Characterization of small pulmonary nodules by CT. Eur. Radiol., 2004, 14(8), 1380-1391. doi: 10.1007/s00330-004-2335-z PMID: 15148623
  15. Miller, F.G.; Joffe, S.; Kesselheim, A.S. Evidence, errors, and ethics. Perspect. Biol. Med., 2014, 57(3), 299-307. doi: 10.1353/pbm.2014.0024 PMID: 25959345
  16. Nunn, P. HIV-associated pulmonary tuberculosis. Afr. Health, 1991, 14(1), 10-11. PMID: 12343452
  17. Austin, B. The value of cultures to modern microbiology. Antonie van Leeuwenhoek, 2017, 110(10), 1247-1256. doi: 10.1007/s10482-017-0840-8 PMID: 28168566
  18. Moreno, I.; Cicinelli, E.; Garcia-Grau, I.; Gonzalez-Monfort, M.; Bau, D.; Vilella, F.; De Ziegler, D.; Resta, L.; Valbuena, D.; Simon, C. The diagnosis of chronic endometritis in infertile asymptomatic women: A comparative study of histology, microbial cultures, hysteroscopy, and molecular microbiology. Am. J. Obstet. Gynecol., 2018, 218(6), 602.e1-602.e16. doi: 10.1016/j.ajog.2018.02.012 PMID: 29477653
  19. Wunderink, R.G. Diagnosis of pneumonia. Curr. Opin. Pulm. Med., 1996, 2(3), 213-217. doi: 10.1097/00063198-199605000-00009 PMID: 9363142
  20. Chen, X.; Cao, K.; Wei, Y.; Qian, Y.; Liang, J.; Dong, D.; Tang, J.; Zhu, Z.; Gu, Q.; Yu, W. Metagenomic next-generation sequencing in the diagnosis of severe pneumonias caused by Chlamydia psittaci. Infection, 2020, 48(4), 535-542. doi: 10.1007/s15010-020-01429-0 PMID: 32314307
  21. Keane, O.M.; Budd, K.E.; Flynn, J.; McCoy, F. Increased detection of mastitis pathogens by real‐time PCR compared to bacterial culture. Vet. Rec., 2013, 173(11), 268-268. doi: 10.1136/vr.101598 PMID: 23976784
  22. Wang, Y.; Salazar, J.K. Culture-Independent Rapid Detection Methods for Bacterial Pathogens and Toxins in Food Matrices. Compr. Rev. Food Sci. Food Saf., 2016, 15(1), 183-205. doi: 10.1111/1541-4337.12175 PMID: 33371580
  23. Zhang, T.; Lv, C-F.; Wang, J.; Zheng, W-B.; Lu, L-Z.; Liu, S-J.; Bao, J. Direct tuberculosis drug susceptibility testing: Time-saving and cost-effective in detecting MDR-TB. Int. J. Tuberc. Lung Dis., 2016, 20(3), 323-328. doi: 10.5588/ijtld.15.0637 PMID: 27046712
  24. Diao, Z.; Han, D.; Zhang, R.; Li, J. Metagenomics next-generation sequencing tests take the stage in the diagnosis of lower respiratory tract infections. J. Adv. Res., 2022, 38, 201-212. doi: 10.1016/j.jare.2021.09.012 PMID: 35572406
  25. Liu, H.; Zhang, Y.; Yang, J.; Liu, Y.; Chen, J. Application of mNGS in the Etiological Analysis of Lower Respiratory Tract Infections and the Prediction of Drug Resistance. Microbiol. Spectr., 2022, 10(1), e02502-e02521. doi: 10.1128/spectrum.02502-21 PMID: 35171007
  26. Yu, G.; Zhao, W.; Shen, Y.; Zhu, P.; Zheng, H. Metagenomic next generation sequencing for the diagnosis of tuberculosis meningitis: A systematic review and meta-analysis. PLoS One, 2020, 15(12), e0243161. doi: 10.1371/journal.pone.0243161 PMID: 33259541
  27. Liu, J.; Zhang, Q.; Dong, Y.Q.; Yin, J.; Qiu, Y.Q. Diagnostic accuracy of metagenomic next-generation sequencing in diagnosing infectious diseases: A meta-analysis. Sci. Rep., 2022, 12(1), 21032. doi: 10.1038/s41598-022-25314-y PMID: 36470909
  28. Françoise, A.; Héry-Arnaud, G. The Microbiome in Cystic Fibrosis Pulmonary Disease. Genes (Basel), 2020, 11(5), 536. doi: 10.3390/genes11050536 PMID: 32403302
  29. Leopold, S.S. When should we adopt new technology into our practices? Arch. Orthop. Trauma Surg., 2021, 141(12), 2337-2340. doi: 10.1007/s00402-021-04086-6 PMID: 34402931
  30. Gupta, S. Paperless clinical trials: Myth or reality? Indian J. Pharmacol., 2015, 47(4), 349-353. doi: 10.4103/0253-7613.161247 PMID: 26288464
  31. Jiang, S.; Min, R.; Fang, P. The impact of healthcare reform on the efficiency of public county hospitals in China. BMC Health Serv. Res., 2017, 17(1), 838. doi: 10.1186/s12913-017-2780-4 PMID: 29262816
  32. James, S.; Rao, S.V.; Granger, C.B. Registry-based randomized clinical trials—a new clinical trial paradigm. Nat. Rev. Cardiol., 2015, 12(5), 312-316. doi: 10.1038/nrcardio.2015.33 PMID: 25781411
  33. Piubello Orsini, L.; Leardini, C.; Vernizzi, S.; Campedelli, B. Inefficiency of public hospitals: A multistage data envelopment analysis in an Italian region. BMC Health Serv. Res., 2021, 21(1), 1281. doi: 10.1186/s12913-021-07276-5 PMID: 34838006
  34. Flygare, S.; Simmon, K.; Miller, C.; Qiao, Y.; Kennedy, B.; Di Sera, T.; Graf, E.H.; Tardif, K.D.; Kapusta, A.; Rynearson, S.; Stockmann, C.; Queen, K.; Tong, S.; Voelkerding, K.V.; Blaschke, A.; Byington, C.L.; Jain, S.; Pavia, A.; Ampofo, K.; Eilbeck, K.; Marth, G.; Yandell, M.; Schlaberg, R. Taxonomer: An interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling. Genome Biol., 2016, 17(1), 111. doi: 10.1186/s13059-016-0969-1 PMID: 27224977
  35. Mongkolrattanothai, K.; Naccache, S.N.; Bender, J.M.; Samayoa, E.; Pham, E.; Yu, G.; Dien Bard, J.; Miller, S.; Aldrovandi, G.; Chiu, C.Y. Neurobrucellosis: Unexpected Answer From Metagenomic Next-Generation Sequencing. J. Pediatric Infect. Dis. Soc., 2017, 6(4), piw066. doi: 10.1093/jpids/piw066 PMID: 28062553
  36. Balloux, F.; Brønstad Brynildsrud, O.; van Dorp, L.; Shaw, L.P.; Chen, H.; Harris, K.A.; Wang, H.; Eldholm, V. From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic. Trends Microbiol., 2018, 26(12), 1035-1048. doi: 10.1016/j.tim.2018.08.004 PMID: 30193960
  37. Han, D.; Li, Z.; Li, R.; Tan, P.; Zhang, R.; Li, J. mNGS in clinical microbiology laboratories: On the road to maturity. Crit. Rev. Microbiol., 2019, 45(5-6), 668-685. doi: 10.1080/1040841X.2019.1681933 PMID: 31691607
  38. Beck, T.F.; Mullikin, J.C.; Biesecker, L.G. Systematic Evaluation of Sanger Validation of Next-Generation Sequencing Variants. Clin. Chem., 2016, 62(4), 647-654. doi: 10.1373/clinchem.2015.249623 PMID: 26847218
  39. Kalantar, K.L.; Carvalho, T.; de Bourcy, C.F.A.; Dimitrov, B.; Dingle, G.; Egger, R.; Han, J.; Holmes, O.B.; Juan, Y.F.; King, R.; Kislyuk, A.; Lin, M.F.; Mariano, M.; Morse, T.; Reynoso, L.V.; Cruz, D.R.; Sheu, J.; Tang, J.; Wang, J.; Zhang, M.A.; Zhong, E.; Ahyong, V.; Lay, S.; Chea, S.; Bohl, J.A.; Manning, J.E.; Tato, C.M.; DeRisi, J.L. IDseq—An open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring. Gigascience, 2020, 9(10), giaa111. doi: 10.1093/gigascience/giaa111 PMID: 33057676
  40. Chiu, C.Y.; Miller, S.A. Clinical metagenomics. Nat. Rev. Genet., 2019, 20(6), 341-355. doi: 10.1038/s41576-019-0113-7 PMID: 30918369
  41. Simner, P.J.; Miller, S.; Carroll, K.C. Understanding the Promises and Hurdles of Metagenomic Next-Generation Sequencing as a Diagnostic Tool for Infectious Diseases. Clin. Infect. Dis., 2018, 66(5), 778-788. doi: 10.1093/cid/cix881 PMID: 29040428
  42. van Dijk, E.L.; Jaszczyszyn, Y.; Thermes, C. Library preparation methods for next-generation sequencing: Tone down the bias. Exp. Cell Res., 2014, 322(1), 12-20. doi: 10.1016/j.yexcr.2014.01.008 PMID: 24440557
  43. van Griethuysen, J.J.M.; Fedorov, A.; Parmar, C.; Hosny, A.; Aucoin, N.; Narayan, V.; Beets-Tan, R.G.H.; Fillion-Robin, J.C.; Pieper, S.; Aerts, H.J.W.L. Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Res., 2017, 77(21), e104-e107. doi: 10.1158/0008-5472.CAN-17-0339 PMID: 29092951
  44. Greathouse, K.L.; Sinha, R.; Vogtmann, E. DNA extraction for human microbiome studies: The issue of standardization. Genome Biol., 2019, 20(1), 212. doi: 10.1186/s13059-019-1843-8 PMID: 31639026
  45. Roy, S.; Coldren, C.; Karunamurthy, A.; Kip, N.S.; Klee, E.W.; Lincoln, S.E.; Leon, A.; Pullambhatla, M.; Temple-Smolkin, R.L.; Voelkerding, K.V.; Wang, C.; Carter, A.B. Standards and Guidelines for Validating Next-Generation Sequencing Bioinformatics Pipelines. J. Mol. Diagn., 2018, 20(1), 4-27. doi: 10.1016/j.jmoldx.2017.11.003 PMID: 29154853
  46. Duan, H.; Li, X.; Mei, A.; Li, P.; Liu, Y.; Li, X.; Li, W.; Wang, C.; Xie, S. The diagnostic value of metagenomic next-generation sequencing in infectious diseases. BMC Infect. Dis., 2021, 21(1), 62. doi: 10.1186/s12879-020-05746-5 PMID: 33435894
  47. Wang, J.; Han, Y.; Feng, J. Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis. BMC Pulm. Med., 2019, 19(1), 252. doi: 10.1186/s12890-019-1022-4 PMID: 31856779
  48. Zheng, Y.; Qiu, X.; Wang, T.; Zhang, J. The Diagnostic Value of Metagenomic Next–Generation Sequencing in Lower Respiratory Tract Infection. Front. Cell. Infect. Microbiol., 2021, 11, 694756. doi: 10.3389/fcimb.2021.694756 PMID: 34568089
  49. Su, S.; Chen, X.; Zhou, L.; Lin, P.; Chen, J.; Chen, C.; Wu, Q.; Ye, J.; Li, Y. Diagnostic performance of the metagenomic next-generation sequencing in lung biopsy tissues in patients suspected of having a local pulmonary infection. BMC Pulm. Med., 2022, 22(1), 112. doi: 10.1186/s12890-022-01912-4 PMID: 35351079
  50. Miao, Q.; Ma, Y.; Wang, Q.; Pan, J.; Zhang, Y.; Jin, W.; Yao, Y.; Su, Y.; Huang, Y.; Wang, M.; Li, B.; Li, H.; Zhou, C.; Li, C.; Ye, M.; Xu, X.; Li, Y.; Hu, B. Microbiological Diagnostic Performance of Metagenomic Next-generation Sequencing When Applied to Clinical Practice. Clin. Infect. Dis., 2018, 67(Suppl. 2), S231-S240. doi: 10.1093/cid/ciy693 PMID: 30423048
  51. Shi, C.L.; Han, P.; Tang, P.J.; Chen, M.M.; Ye, Z.J.; Wu, M.Y.; Shen, J.; Wu, H.Y.; Tan, Z.Q.; Yu, X.; Rao, G.H.; Zhang, J.P. Clinical metagenomic sequencing for diagnosis of pulmonary tuberculosis. J. Infect., 2020, 81(4), 567-574. doi: 10.1016/j.jinf.2020.08.004 PMID: 32768450
  52. Husain, U.; Tilak, R.; Aggarwal, S.K.; Priyadarshi, K.; Dhameja, N. Time to speed up the diagnostic evaluation in clinically suspected rhinosinusitis patients: A debate on the conventional versus molecular workup to establish fungal infective etiology for prompt management. Curr. Med. Mycol., 2022, 8(1), 1-6. doi: 10.18502/cmm.8.1.9207 PMID: 36340434
  53. Sun, T.; Wu, X.; Cai, Y.; Zhai, T.; Huang, L.; Zhang, Y.; Zhan, Q. Metagenomic Next-Generation Sequencing for Pathogenic Diagnosis and Antibiotic Management of Severe Community-Acquired Pneumonia in Immunocompromised Adults. Front. Cell. Infect. Microbiol., 2021, 11, 661589. doi: 10.3389/fcimb.2021.661589 PMID: 34141628
  54. Nwadike, V.U.; Onwah, A.L.; Owolabi, T.A.; Ogunnaike-Quaye, T. Candidaemia in the immunocompromised; a case for early diagnosis/detection and treatment. Jos J Med, 2013, 7(2)
  55. Arp, M.; Larsen, S.O. Comparison of detection speed and yield in agitated and non‐agitated aerobic blood culture bottles. Acta Pathol. Microbiol. Scand. Suppl., 1992, 100(7-12), 1061-1065. doi: 10.1111/j.1699-0463.1992.tb04041.x PMID: 1492974
  56. Sacco, O.; Battistini, E.; Oddera, S.; Silvestri, M.; Pallecchi, A.; Gandolpo, A.; Rossi, G.A. Clinical application of bronchoscopy and bronchoalveolar lavage in the immunocompromised host. Monaldi Arch. Chest Dis., 1994, 49(3), 217-220. PMID: 8087118
  57. Fekkar, A.; Pionneau, C.; Brossas, J.Y.; Marinach-Patrice, C.; Snounou, G.; Brock, M.; Ibrahim-Granet, O.; Mazier, D. DIGE enables the detection of a putative serum biomarker of fungal origin in a mouse model of invasive aspergillosis. J. Proteomics, 2012, 75(9), 2536-2549. doi: 10.1016/j.jprot.2012.01.040 PMID: 22370163
  58. Millon, L.; Larosa, F.; Lepiller, Q.; Legrand, F.; Rocchi, S.; Daguindau, E.; Scherer, E.; Bellanger, A.P.; Leroy, J.; Grenouillet, F. Quantitative polymerase chain reaction detection of circulating DNA in serum for early diagnosis of mucormycosis in immunocompromised patients. Clin. Infect. Dis., 2013, 56(10), e95-e101. doi: 10.1093/cid/cit094 PMID: 23420816
  59. Barnes, R.A. Early diagnosis of fungal infection in immunocompromised patients. J. Antimicrob. Chemother., 2008, 61(Suppl. 1), i3-i6. doi: 10.1093/jac/dkm424 PMID: 18063601
  60. Guo, Y.; Li, H.; Chen, H.; Li, Z.; Ding, W.; Wang, J.; Yin, Y.; Jin, L.; Sun, S.; Jing, C.; Wang, H. Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue. EBioMedicine, 2021, 73, 103639. doi: 10.1016/j.ebiom.2021.103639 PMID: 34700283
  61. Fu, M.; Cao, L.J.; Xia, H.L.; Ji, Z.M.; Hu, N.N.; Leng, Z.J.; Xie, W.; Fang, Y.; Zhang, J.Q.; Xia, D.Q. The performance of detecting Mycobacterium tuberculosis complex in lung biopsy tissue by metagenomic next-generation sequencing. BMC Pulm. Med., 2022, 22(1), 288. doi: 10.1186/s12890-022-02079-8 PMID: 35902819
  62. Wu, X.; Li, Y.; Zhang, M.; Li, M.; Zhang, R.; Lu, X.; Gao, W.; Li, Q.; Xia, Y.; Pan, P.; Li, Q. Etiology of Severe Community-Acquired Pneumonia in Adults Based on Metagenomic Next-Generation Sequencing: A Prospective Multicenter Study. Infect. Dis. Ther., 2020, 9(4), 1003-1015. doi: 10.1007/s40121-020-00353-y PMID: 33170499
  63. Peng, J.M.; Du, B.; Qin, H.Y.; Wang, Q.; Shi, Y. Metagenomic next-generation sequencing for the diagnosis of suspected pneumonia in immunocompromised patients. J. Infect., 2021, 82(4), 22-27. doi: 10.1016/j.jinf.2021.01.029 PMID: 33609588
  64. Lin, M.; Wang, K.; Qiu, L.; Liang, Y.; Tu, C.; Chen, M.; Wang, Z.; Wu, J.; Huang, Y.; Tan, C.; Chen, Q.; Zheng, X.; Liu, J. Tropheryma whipplei detection by metagenomic next-generation sequencing in bronchoalveolar lavage fluid: A cross-sectional study. Front. Cell. Infect. Microbiol., 2022, 12, 961297. doi: 10.3389/fcimb.2022.961297 PMID: 36061864
  65. Yan, L.; Sun, W.; Lu, Z.; Fan, L. Metagenomic Next-Generation Sequencing (mNGS) in cerebrospinal fluid for rapid diagnosis of Tuberculosis meningitis in HIV-negative population. Int. J. Infect. Dis., 2020, 96, 270-275. doi: 10.1016/j.ijid.2020.04.048 PMID: 32339718
  66. Buurma, H.A.; Buurma, B.J. The effect of smear layer on bacterial penetration through roots obturated using zinc oxide eugenol-based sealer. BMC Oral Health, 2020, 20(1), 88. doi: 10.1186/s12903-020-01069-8 PMID: 32216774
  67. Zhang, Y.; Cui, P.; Zhang, H.C.; Wu, H.L.; Ye, M.Z.; Zhu, Y.M.; Ai, J.W.; Zhang, W.H. Clinical application and evaluation of metagenomic next-generation sequencing in suspected adult central nervous system infection. J. Transl. Med., 2020, 18(1), 199. doi: 10.1186/s12967-020-02360-6 PMID: 32404108
  68. Alvarez-Payares, J.C.; Bello-Simanca, J.D.; De La Peña-Arrieta, E.D.J.; Agamez-Gomez, J.E.; Garcia-Rueda, J.E.; Rodriguez-Arrieta, A.; Rodriguez-Arrieta, L.A. Common Pitfalls in the Interpretation of Endocrine Tests. Front. Endocrinol. (Lausanne), 2021, 12, 727628. doi: 10.3389/fendo.2021.727628 PMID: 34557164
  69. Malvagia, S.; Forni, G.; Ombrone, D.; la Marca, G. Development of Strategies to Decrease False Positive Results in Newborn Screening. Int. J. Neonatal Screen., 2020, 6(4), 84. doi: 10.3390/ijns6040084 PMID: 33147868
  70. Geisler, B.P.; Jilg, N.; Patton, R.G.; Pietzsch, J.B. Model to evaluate the impact of hospital-based interventions targeting false-positive blood cultures on economic and clinical outcomes. J. Hosp. Infect., 2019, 102(4), 438-444. doi: 10.1016/j.jhin.2019.03.012 PMID: 30928573
  71. Healy, B.; Khan, A.; Metezai, H.; Blyth, I.; Asad, H. The impact of false positive COVID-19 results in an area of low prevalence. Clin. Med. (Lond.), 2021, 21(1), e54-e56. doi: 10.7861/clinmed.2020-0839 PMID: 33243836
  72. Kumar, P.; Gill, R.M.; Phelps, A.; Tulpule, A.; Matthay, K.; Nicolaides, T. Surveillance Screening in Li-Fraumeni Syndrome: Raising Awareness of False Positives. Cureus, 2018, 10(4), e2527. doi: 10.7759/cureus.2527 PMID: 29946497
  73. Dong, B.; He, Z.; Li, Y.; Xu, X.; Wang, C.; Zeng, J. Improved Conventional and New Approaches in the Diagnosis of Tuberculosis. Front. Microbiol., 2022, 13, 924410. doi: 10.3389/fmicb.2022.924410 PMID: 35711765
  74. Teixeira, H.C.; Abramo, C.; Munk, M.E. Diagnóstico imunológico da tuberculose: Problemas e estratégias para o sucesso. J. Bras. Pneumol., 2007, 33(3), 323-334. doi: 10.1590/S1806-37132007000300015 PMID: 17906795
  75. Aliannejad, R.; Bahrmand, A. Accuracy of a New Rapid Antigen Detection Test for Pulmonary Tuberculosis. PubMed, 2016, 8(4), 238-242.

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2024 Bentham Science Publishers