Journal Pre-proof Diagnostic Errors in Clinical Microbiology and Antimicrobial Resistance Tulsi Chugh, Prof. PII:
S2352-0817(19)30209-0
DOI:
https://doi.org/10.1016/j.cmrp.2019.11.008
Reference:
CMRP 456
To appear in:
Current Medicine Research and Practice
Received Date: 19 June 2019 Revised Date:
31 October 2019
Accepted Date: 26 November 2019
Please cite this article as: Chugh T, Diagnostic Errors in Clinical Microbiology and Antimicrobial Resistance, Current Medicine Research and Practice, https://doi.org/10.1016/j.cmrp.2019.11.008. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier, a division of RELX India, Pvt. Ltd on behalf of Sir Ganga Ram Hospital.
Title Page: Title: Diagnostic Errors in Clinical Microbiology and Antimicrobial Resistance
Type of article: Review Article Author: Prof. Tulsi Chugh D-702, Som Vihar Appartments RK Puram, New Delhi-110022 Email:
[email protected] Contact No. +919818575933
Potential Conflicts of Interest: The author has nothing to disclose
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Diagnostic Errors in Clinical Microbiology and Antimicrobial Resistance Abstract: Antimicrobial resistance (AMR) is a serious public health threat worldwide, and is leading to resurgence of untreatable infectious diseases. However, AMR surveillance in low and middle-income countries (LMICs) may not be of appropriate level. Optimum utilisation of clinical microbiology services requires an integrated effort of several hospital services including supportive management and dedicated nursing staff. It requires regular and persistent motivation at all levels of the healthcare. Antimicrobial resistance (AMR) is a serious public health threat worldwide, and is leading to resurgence of untreatable infectious diseases. On May 26, 2015, the sixty-eighth World Health Assembly adopted a global action plan (WHA 68.7, agenda item 15.1). The global leaders committed at the Assembly in September 2016 to take action to control AMR.1,2 The World Health Organisation (WHO) has formulated a standard Global AMR Surveillance System (GLASS) to gather an evidencebased fully verified and validated data. It requires technical expertise, standardisation, and internal and external quality control. The reliable data is the key to informed decision-making. However, AMR surveillance in low and middle-income countries (LMICs) may not be of appropriate level. The Ministry of Health and Family Welfare, Government of India has identified it as a priority and is a partner in global action plan (GAP) for surveillance of antimicrobial resistance.3 Antibiotic consumption is the principal cause of AMR. Antibiotic use in 76 world countries during 2005-15 showed an overall increase of 65% (21.1 to 34.8 billion defined daily doses: DDDs). The antibiotic consumption rate increased by 39% (11.3-15.7 DDSs per 1000 persons per day). The rapid increase in consumption rate was high in LMICs (by 114%) while it fell by 4% in high income countries (HICs). During this period, the consumption was highest in India (increased from 3.2 to 6.5 billion DDDS: 103%). The antibiotic consumption rate of broad-spectrum antibiotics increased 56% and 15% in LMICs and HICs respectively.1 Therefore, national policies of improved public health sanitation, hospital hygiene, vaccination, and improved diagnostic laboratory practices to reduce emergence and spread of AMR are required.4,5 Diagnostic errors in microbiology practice Microbiology has an important role in the diagnosis and choice of therapy of infectious diseases. An optimal choice for antimicrobial with the help of clinician to decide, what to use. Some common errors observed are as under6,7,8,9 Pre analytic errors: Request forms duly filled in with the presumptive diagnosis and prior antibiotic therapy, choice and volume of specimens, aseptic collection and their proper transportation are critical. Pre-analytical errors account for about 50% to 67% of total diagnostic errors. Blood cultures10,11,12,13:
It is an important diagnostic investigation for detecting the pathogenic microbial growth and subsequently checking the antimicrobial resistance. Contamination with skin flora (Coagulase-negative staphylococci, Micrococcus sp., Bacillus sp., diphtheroids and propionibacteria) is frequent and lead to false-positive reports. Blood contamination rate should be less than 2-3%. However, it is reported to be much higher in some centres in India. Pseudobacteremia is the term used for various contaminants contributing to total positives. Around 50% of all positive blood cultures are due to contaminants. This proportion is even higher in children where collection is difficult. Clinical based (Q-probe of College of American Pathologists) and laboratory-based algorithms have been developed to differentiate true bacteraemias from pseudobacteremias. Species of bacteria, delayed positivity after 48hr, positivity when on antibiotics, multiplicity of species, and positivity only in one bottle should raise a suspicion of contamination. It can be reduced / prevented by appropriate choice of venipuncture site, use of appropriate antiseptic for disinfection of site, use of at least two sets of blood cultures, and collection of larger amount of blood. Contamination is significantly lower with phlebotomists than nurses (p= 0.03).(Reference?) Correct choice of samples14,15,16 Nasopharyngeal swab/ aspirates and washings (not throat swabs) should be collected in children for the diagnosis of lower respiratory infections. Also these samples must be processed within 2 hours of collection. Mid-stream urine samples without contamination with vaginal secretions should be processed within 30 minutes. Obtain adequate volumes of pus and debrided tissues instead of pus swabs are desirable. Inadequate specimens or leaking samples should be rejected. Specimens should be correctly labelled and transported. Analytic errors: These may be due to lack of standardization, calibrated and malfunction of equipment, mix-ups of samples, and not following the procedure / protocol or lack of quality controls. Microscopy17,18 Unstained and stained smears provide a rapid provisional diagnosis and guidelines for empiric therapy. Correlation with culture results and rejection of inappropriate samples e.g. sputum contaminated with saliva or urine with vaginal secretions. It acts as an internal quality by comparing smear and culture reports. However, smears reports should clearly spell out morphotypes of organisms and cellular exudate and suggested diagnosis to help the clinicians. Use of rapid laboratory techniques19,20,21,22: Fluorescence microscopy including using monoclonal antibodies, antigen-antibody tests: enzymelinked immunosorbent assay (ELISA), immunochromatographic (ICT) tests, Legionella urine test, molecular diagnostics, rapid diagnostic testing and biomarkers are essential. Nucleic acid amplification tests are rapid with short turn-around time. However, cost and technical expertise is a consideration. Point-of-care test for pyuria (leukocyte esterase and nitrate reduction) is strongly recommended. Matrix
Assisted Laser Desorption/Ionization-Time of Flight (MALDI-TOF) for diagnosis of pathogens (bacteria, yeasts and mycobacteria) in 10-30 min is useful for rapid identification of blood-stream pathogens. Post-analytic errors: These include delay or failure to report or wrong validation or wrong data entry. Microbiologists should regularly provide cumulative antimicrobial susceptibility reports to help or guide clinicians to make a correct empiric choice of antibiotics. Direct and regular communication with clinicians by regular visits to the wards in addition to providing educational sessions at staff and clinical meetings is important. Quality control (QC)23,24,25: The quality control can be effectively implemented through total quality management at all levels through internal QC, and external QC: participation in National and International (WHO or CAP) programs is essential to build patient’s /clinician’s confidence through improved results. It has an impact on outcome, cost and length of stay in hospital. Institutional data of laboratory errors should be shared with clinicians and management regularly. The cornerstone of antibiotic stewardship is making an accurate diagnosis of nature and site of infection and antimicrobial susceptibility of pathogens through quality clinical microbiology. Optimum utilisation of clinical microbiology services requires an integrated effort of various hospital services including supportive management and dedicated nursing staff. It requires regular and persistent motivation at all levels.26,27 References: 1. Gandra S, Tseng KK, Arora A, et al. The mortality burden of multidrug-resistant pathogens in India: a retrospective observational study. Clin Infect Dis. 2018. doi: 10.1093/cid/ciy955. 2. Scherz V, Durussel C, Greub G. Internal quality assurance in diagnostic microbiology: A simple approach for insightful data. PLoS One. 2017;12:e0187263. 3. Ganguly NK, Arora NK, Chandy SJ, et al. Global Antibiotic Resistance Partnership (GARP) India Working Group. Rationalizing antibiotic use to limit antibiotic resistance in India. Indian J Med Res. 2011;134:281-94. 4. Schofield CB. Preventing errors in the microbiology lab. 2006;38:10. 5. Singh H. Diagnostic Errors: a new chapter in patient safety science, policy, and practice. Jan 2016. https://psnet.ahrq.gov/perspectives/perspective/188/diagnostic-errors-a-new-chapter-inpatient-safety-science-policy-and-practice. 6. Abdollahi A, Saffar H, Saffar H. Types and frequency of errors during different phases of testing at a clinical medical laboratory of a teaching hospital in Tehran, Iran. N Am J Med Sci. 2014;6:224-8. 7. Khan ID, Gupta N, Rangan NM, et al. Evaluation of pre- and post-analytical variables in clinical microbiology services in multidisciplinary ICU of a medical college and tertiary care hospital. J Basic Clin Med 2016; 5: 2-4.
8. Nwose EU. Quality in diagnostic microbiology: experiential note to emphasize value of internal control programs. N Am J Med Sci. 2013;5:82-7. 9. Samuel L, Plebani M. Targeting errors in microbiology: the case of the Gram stain. Clin Chem Lab Med. 2017;55:309-310. 10. Bekeris LG, Tworek JA, Walsh MK, Valenstein PN. Trends in blood culture contamination: a College of American Pathologists Q-Tracks study of 356 institutions. Arch Pathol Lab Med. 2005;129:1222-5. 11. Hossain B, Weber MW, Hamer DH, et al. Classification of blood culture isolates into Contaminaħts and halogens on the bar basis of clinical and laboratory data. The Paed Infect Dis J 2016; 35: Suppl S52-54. 12. Tantry Mc Abishek V, Vandna KE, et al. Quality Assurance in blood culture: a prospective a blood culture contamination rate in a tertiary care hospital in Southern India. 13. Sidhu SK, Malhotra S, Devi P, Tuli AK. Significance of coagulase negative Staphylococcus from blood cultures: persisting problems and partial progress in resource constrained settings. Iran J Microbiol. 2016;8:366-371. 14. Hijazi Z, Pacsa A, el-Gharbawy F, et al. Acute lower respiratory tract infections in children in Kuwait. Ann Trop Paediatr. 1997;17:127-34. 15. Behbehani N, Mahmood A, Mokaddas EM, et al. Significance of atypical pathogens among community-acquired pneumonia adult patients admitted to hospital in Kuwait. Med Princ Pract. 2005;14:235-40. 16. Panigrahi D, Ratini VO, Chugh TD, et al The anaerobic bacteriology of intrapulmonary infections in Kuwait. Med Princ Pract 2001;10:102-105. 17. Thomson RB Jr. One Small Step for the Gram Stain, One Giant Leap for Clinical Microbiology. J Clin Microbiol. 2016;54:1416-1417. 18. Samuel LP, Balada-Llasat JM, Harrington A, Cavagnolo R. Correction for Samuel et al., Multicenter Assessment of Gram Stain Error Rates. J Clin Microbiol. 2016;54:2405. 19. Wise GJ, Schlegel PN. Sterile pyuria. N Engl J Med. 2015;372:1048-54. 20. Hendow MT, favag SI, Chugh TD. Evaluation of microbiology quality assessment scheme in Kuwait. Med Princ Pract 1992; 3: 160-166. 21. Kothari A, Morgan M, Haake DA. Emerging technologies for rapid identification of bloodstream pathogens. Clin Infect Dis. 2014;59:272-8. 22. Khan F, Kirmani N, Siddiqui et al. CONS in blood Culture: contaminants and pathogens? Int J Curr Microbiol App Sci 2015; 1: 88-94 23. Morency-Potvin P, Schwartz DN, Weinstein RA. Antimicrobial Stewardship: How the Microbiology Laboratory Can Right the Ship. Clin Microbiol Rev. 2016;30:381-407. 24. Plebani M Lippi G. Improving diagnosis and reducing diagnostic errors: the next frontier of laboratory medicine. Clin Chem Lab Med. 2016; 54: 117-8. 25. Bentley J, Thakore S, Muir L, et al. A change of culture: reducing blood culture contaminants rates in an emergency department. BMJ Qual Improv Rep 2016; 5: 206760.W2754. 26. Malik S, Ravishankar K. Significance of coagulase - negative staphylococcus species in blood
culture. J Clin Diagnostic Res 2012; 6:632-5. 27. Watson ID, Wilkie P, Hannan A, Beastall GH. Role of laboratory medicine in collaborative healthcare. Clin Chem Lab Med. 2018;57:134-142.