Background: The change from non-molecular to nucleic acid amplification tests (NAATs) is known to increase the detection of Clostridium difficile infection (CDI); however, the impact on stool rejection policies in clinical laboratories is unclear. The current guidelines have reinforced the importance of respecting strict conditions for performing tests on stool samples for CDI diagnosis. The purpose of this study was to estimate whether the implementation of molecular tests has resulted in changes in stool rejection policies between clinical laboratories that introduced NAATs and those that did not. Results: A survey was conducted to evaluate the change in the number of stool samples rejected and the rejection criteria among 12 hospital laboratories in southwestern France before and after the switch from non-molecular tests to NAATs using retrospective data from June 1 till September 30, 2013 and the same period 2014. Four laboratories introduced NAATs as a second or third step in the process. A total of 1378 and 1297 stools samples were collected in 2013 and 2014, respectively. The mean number of rejected stool samples significantly increased (p < 0.001, Chi square test), with a total of 99 (7.1%) and 147 (11.3%) specimens rejected in 2013 and 2014, respectively. Notably, these labo- ratories had more stringent criteria and were no longer testing the stool samples of patients with CDI-positive results within 7 days. In contrast, there was a significant decrease in the rate of rejected stool samples (p < 0.001, Chi square test) in the five laboratories that did not adopt NAATs and a less stringent stool rejection policy. Conclusion: Nucleic acid amplification test implementation improved compliance with recommended stool rejec- tion policies. Laboratories should follow the recommended laboratory algorithm for the CDI diagnosis combined with the correct stool rejection policy. Keywords: C. difficile , Diagnosis, Impact, Molecular, Algorithm, NAAT Infectious Diseases (ESCMID) guidelines [1–3] recom- Background mend combining two tests in an algorithm to optimize Clostridium difficile infection (CDI) is currently the the diagnosis. Despite its poor sensitivity when com- major cause of healthcare-associated diarrhea. Mul- pared to toxigenic culture (60–81%) , toxin enzyme tiple diagnostic approaches are available for CDI. No immunoassay (EIA) remains the preferred method for single test is suitable for use as a stand-alone test, and primary diagnosis in most laboratories because of its current Infectious Disease Society of America (IDSA) low cost and short turnaround time. In 2014, the results and European Society of Clinical Microbiology and of a European multicenter prospective point-prevalence study of CDI in hospitalized patients with diarrhea *Correspondence: firstname.lastname@example.org highlighted the poor performances of the tests used in Laboratoire de Bactériologie, C.H.U. de Bordeaux, Groupe Hospitalier clinical laboratories , these poor performances being Pellegrin, Place Amélie Raba Léon, 33076 Bordeaux Cedex, France responsible for 25% of misdiagnoses. Full list of author information is available at the end of the article © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/ publi cdoma in/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Goret et al. Gut Pathog (2018) 10:19 Page 2 of 6 To overcome this problem, nucleic acid amplification institution) and details of current CDI laboratory diag- tests (NAATs) have been developed and are increasingly nostic methods. adopted. They are reported to have sensitivities ranging We compared the stool rejection policy of laborato- from 84 to 94% and short turnaround times compared ries that introduced NAATs to that of laboratories that with toxigenic culture . Changing from EIA to more did not, between June 1 to September 30, 2013 and June sensitive molecular tests is reported to increase the CDI 1 to September 30, 2014. A laboratory that introduced detection during the transition year, with an increase up NAATs was defined as a laboratory using a novel molec - to 57% [4, 6–12]. The increased sensitivity of molecu - ular test in the first, second or third line of a diagnos - lar tests has improved the laboratory detection of CDI tic algorithm since October 2013. A laboratory without cases, and current guidelines recommend their use NAATs was defined as a laboratory using a non-molec - in diagnosis as the first or second step [3 ]. However, a ular test such as EIA for toxins, EIA for glutamate dehy- molecular test is difficult to implement in clinical labo - drogenase (GDH) and/or culture with toxin detection, ratories because of its costs, the potential for confusion and EIA detection of strains, alone or combined into by physicians and overuse because of its novelty. It also algorithms. cannot differentiate a truly infected patient from a colo - The submitted survey included routine tests, the num - nized one [6, 13]. Its diagnostic accuracy is also variable ber of stools collected, the number of stools tested, the and depends on CDI prevalence . number of CDI-positive results, the number of tested To increase the diagnostic accuracy of CDI, European patients and the stool rejection policy during the two guidelines have reinforced the importance of respecting periods. A positive result was defined as a positive test strict conditions for performing tests on stool samples [2, for free toxins or toxin genes. The positivity rate was 3]. Unformed stool samples from patients aged 3 years or defined as the ratio of positive stool samples to the total older should be tested, and formed stool samples must number of tested stools. The stool rejection rate was be rejected . Tests should be performed after at least defined as the ratio of the number of tested stools to 3 days in the hospital or after antibiotic treatment . They the total number of stool samples received at the labo- should not have to be repeated within 7 days if they were ratories. The repetition of the tests was evaluated by the positive and no test of cure is needed [15–17]. CDI test- number of tests performed per patient. The request cri - ing should not be limited to samples with a specific physi - teria for performing tests were the following: only upon cian’s request. Davies et al.  highlighted that over a third physician’s request, on all stool samples, on all diarrheal of laboratories detect C. difficile only upon a physician’s stool samples, on formed stool samples, for a patient request. Dubberke et al.  showed that this request was 3 years or younger, for all patients 65 years or older, for inadequate, with 36% of the requests for non-diarrheal patients hospitalized for a minimum of 3 days, on stool stools and 19% after laxative administration. Selection of samples collected for 48 h or more, after a first positive the stool samples at the clinical laboratory level should sample during the same diarrheal episode, after a first improve the accuracy of the CDI diagnosis. However, it is negative sample during the same diarrheal episode, after unclear how closely the clinical laboratories follow these a first positive sample within 7 days and for a test of cure. guidelines and whether they have an adequate stool sam- The Chi square statistical test was used to assess ple rejection policy. The rate of rejected stool samples was differences. reported to increase after NAAT implementation . To differentiate patients with CDI from asymptomatic The purpose of this study was to estimate whether the carriers, we assessed whether the clinical picture of implementation of NAATs resulted in changes in stool patients with a positive toxin-gene result met the criteria rejection policies between clinical laboratories that intro- of CDI defined by Debast et al. : significant diarrhea, duced NAATs and those that did not, between 2013 and ileus, toxic megacolon or pseudomembranous colitis. 2014, in southwestern France. The stool rejection criteria and impact on the CDI positivity rate were determined. Results The correlation between a positive molecular test and a Ten of the 12 requested laboratories answered the sur- real case of CDI was also evaluated. vey. Data from one laboratory were not included because of the introduction of a molecular test before 2013. The Methods clinical laboratories included were from eight medium A multicenter comparative retrospective survey was size [100,000–500,000 patient bed days (pbds)] and one conducted in October 2014 in 12 clinical laboratories large size (> 500,000 pbds) hospitals. Between June 1 and from hospitals in southwestern France. The laborato - September 30, 2013, none of the laboratories from these ries provided hospital institutional data (size and type of nine hospitals performed molecular tests for CDI diag- nosis (Table 1), instead they used a one- to three-step Goret et al. Gut Pathog (2018) 10:19 Page 3 of 6 algorithm including GDH EIA, toxin EIA and toxigenic In 2014, the laboratories that introduced NAATs were culture with toxin EIA detection of strains. After Octo- no longer limiting their C. difficile detection only to phy - ber 2013, four of the nine laboratories introduced NAAT sicians’ requests; they performed tests on stools from in a two-step algorithm consisting of a screening test by all patients hospitalized for 3 days with diarrhea and no GDH EIA (Imm unoCard C. difficile GDH, Meridian, longer tested the stool samples of patients with a posi- Cincinnati, OH, USA) followed by a NAAT (illumigene , tive CDI result obtained within 7 days (Additional file 2: Meridian) for confirmation. A significant increase in the Table S2). The B laboratory was also the only one to test stool sample rejection rate was observed (Table 1) from all diarrheal stool samples collected. The laboratories that 7.1 in 2013 to 11.3% in 2014 (p < 0.001). In contrast, in did not implement NAATs did not adopt these criteria in the five laboratories that did not adopt NAATs, the over - 2014, and two of them performed tests on all collected all rate of rejected stool samples decreased from 11.7% samples. There was no change in their stool rejection pol - in 2013 to 6.1% in 2014 (p < 0.001). Among these five icy between the two periods. laboratories, one observed a significant increase in the The correlation between positive NAATs and the clini - rejection rate (E), two others did not reject any samples cal picture was evaluated. Seventy of 73 patients (95.8%) in both periods (F and H), and two noted a decrease in who had a positive NAAT result had a clinical picture the rejection rate (G and I). Among the laboratories that consistent with CDI in terms of the ESCMID criteria introduced NAATs, the rate of CDI-positive results was (Table 2). not significantly different (p = 0.07), except for one labo- ratory (B) (Table 1) that performed the largest number Discussion of tests (p = 0.003). In this laboratory, the positivity rate The clinical laboratories that introduced NAATs showed increased from 4.1 to 8.1%. No significant difference in a significantly increase in the rate of rejected stool sam - the percentage of positive results was found in laborato- ples. Previously, Cohen et al.  reported that laborato- ries that did not introduce NAATs. Overall, there was no ries adopted a more stringent stool rejection policy after change in the mean number of stool samples tested glob- NAAT implementation in the USA. These authors did ally or per patient (Additional file 1: Table S1) in the two not specifically ask laboratories to explain the ration - groups of laboratories. ale for adopting more stringent policies, and no studies were conducted to evaluate the stool rejection criteria Table 1 Change in the number of stool specimens tested for C. difficile and the rate of positive specimens according to the laboratories between 2013 and 2014 Laboratory Testing algorithm Number of rejected samples Number of positive results 2013 2014 2013 2014 p 2013 2014 p a d A GDH + EIA GDH + NAAT 10/133 (7.5) 34/137 (24.8) < 0.001 9/123 (7.3) 10/103 (9.7) 0.52 b d B GDH + EIA GDH + NAAT 89/776 (11.5) 83/653 (12.7) 0.47 29/687 (4.1) 46/570 (8.1) 0.003 b d C GDH + EIA GDH + NAAT 0/244 (0.0) 30/314 (9.6) < 0.001 21/244 (8.6) 20/284 (7.0) 0.50 b d D GDH + EIA + TC GDH + NAAT 0/225 (0.0) 0/193 (0.0) * 18/225 (8.0) 14/193 (7.3) 0.77 Total 99/1378 (7.1) 147/1297 (11.3) < 0.001 77/1279 (6.0) 90/1150 (7.8) 0.07 c a E EIA GDH + EIA 6/42 (14.2) 13/44 (29.5) 0.88 2/42 (4.7) 6/31 (19.4) 0.09 b b F GDH + EIA GDH + EIA 0/73 (0.0) 0/85 (0.0) * 6/73 (8.2) 4/85 (4.7) 0.37 b b G GDH + EIA GDH + EIA 47/178 (26.4) 25/152 (16.4) 0.82 20/147 (13.6) 17/127 (13.4) 0.96 b b H GDH + EIA + TC GDH + EIA + TC 0/228 (0.0) 0/267 (0.0) * 12/228 (5.3) 8/267 (3.0) 0.20 b b I GDH + EIA + TC GDH + EIA + TC 23/211 (10.9) 5/162 (3.1) 0.008 17/188 (9.0) 11/157 (7.0) 0.49 Total 76/648 (11.7) 43/710 (6.1) < 0.001 57/678 (8.4) 46/667 (6.9) 0.30 The number of rejected samples is expressed as the number of samples rejected/total number of samples collected (percent). The number of C. difficille infection (CDI)-positive samples is expressed as the number of CDI-positive samples/total number of samples tested (percent). The number of tests per patient is expressed as the number of tested samples/number of patients (ratio). A to D, laboratories that introduced nucleic acid amplification tests (NAATs). E to I, laboratories that did not introduce NAATs GDH glutamate dehydrogenase by enzyme immunoassay, EIA toxin enzyme immunoassay, TC toxigenic culture Statistical analysis was performed using the Chi square test. A p value < 0.05 was considered significant *Not applicable a b c Methods: C. Diff. Quik Chek Complete©, Alere (Waltham, MA, USA); C. Diff. Quik Chek GDH©, Alere and TOX A/B Quik Chek©, Alere; . And TOX A/B Quik Chek©, Alere; d ® ® ImmunoCard C. difficile GDH, Meridian (Cincinnati, OH, USA) and NAAT illumigene , Mridiane Goret et al. Gut Pathog (2018) 10:19 Page 4 of 6 adopted in European laboratories after implementation performed the day the stool samples were received by the of a new testing algorithm for CDI diagnosis. In our laboratories. The current guidelines for CDI laboratory study, three criteria based on the current diagnosis rec- diagnosis  were adopted in southwestern France. PCR ommendations  were adopted by the NAAT labora- alone was described to be more sensitive than the GDH tories: they no longer limited their C. difficile detection EIA-based algorithm, but the data are conflicting [4, 25, to physicians’ requests, they performed tests on patients 26]; laboratories chose the two-step algorithm because of hospitalized for a minimum of 3 days with diarrhea and its lower cost per patient. Although the laboratories that they no longer tested the stool samples of patients with a did not implement NAATs used the recommended test- positive CDI result obtained within 7 days. The possibil - ing algorithm, they did not follow the recommendations ity for the microbiology laboratory to cancel repeat tests carefully and had a poor stool rejection policy. Greater within 1 week is thought to have contributed to a signifi - efforts to improve stool rejection policies are necessary. cant decrease in the number of tested stools . A reduc- The rate of positive results increased significantly for tion in the number of tested samples from 48 to 38.2% only one laboratory that introduced NAATs and per- was previously reported after NAAT implementation [6, formed the largest number of tests. Previous studies 7, 20]. This reduction was not observed in our study. The described an increase in CDI-positive results of up to number of stool samples tested per patient was stable, 57% with PCR testing alone [7, 8, 10–12, 20], and this highlighting that the laboratories controlled the number increase was expected for all laboratories that imple- of tests and limited the overuse of NAATs (Additional mented NAATs but was only observed for laboratory B file 1: Table S1). The cancellation of repeated tests should (Table 1). In Europe, the mean annual CDI testing and be considered as a priority by clinical laboratories, but CDI-positive rates were reported to be significantly we cannot conclude that only one criterion is needed for higher in medium-sized hospitals (46.2/10,000 and effective action. The laboratories must adopt all of the 3.3/10,000 pbds, respectively) compared to large hos- stool rejection recommendations [1–3] to improve CDI pitals (28.6/10,000 and 1.5/10,000 pbds, respectively) diagnosis. . The incidence of CDI in France ranges from 2.9 to The use of suboptimal clinical tests for CDI diagnosis 3.6 cases/10,000 pbds [24, 27]. In contrast, Cohen et al. is still prevalent throughout Europe [5, 21, 22]. Both the did not observe a systematic increase in positivity rates IDSA  and ESCMID [2, 3] suggest a GDH EIA-based after the implementation of a multistep algorithm involv- two-step algorithm or use of NAAT alone to improve ing NAATs . The enrollment of patients, the low level diagnostic accuracy. The French guidelines at the time, of awareness of physicians and the seasonal pattern of did not include these diagnosis algorithms , which the incidence of CDI could explain our results in the were added to the revised guidelines in 2015. Only one medium-sized hospitals [28–31]. The relatively low num - laboratory used toxin EIA alone in 2013, while the oth- ber of specimens processed by these laboratories and our ers used two- or three-step algorithms. In 2014, all of the short observation period could also explain these results. laboratories (100%) chose a recommended two- or three- Regarding the positivity rate, the study has several limi- step algorithm  with an initial screening by GDH EIA, tations: this is a nonrandomized and retrospective study which is superior to the 65 and 85% reported in France that included a network of different sized hospitals. and the UK, respectively, in 2015 . The tests were all Concerns about the detection of colonized patients using NAAT have been raised and emphasize the importance of testing patients with clinically signifi - cant diarrhea in order to avoid false-positive tests. We assessed whether the clinical picture of patients Table 2 Clinical correlation of the positive nucleic acid amplification test (NAAT) results in 2014 in the 4 with a positive toxin-gene result met the criteria of laboratories that introduced NAATs as a second- or third- CDI defined by Debast et al. . Planche et al.  line test suggested that the presence of free toxins could best define true or severe CDI. The presence of free toxins Laboratory Number of positive Number Chart review NAAT results of patients in favor of CDI was significantly associated with unfavorable CDI, with an increase in white blood cells and a higher mortality A 10 9 9 (100.0%) rate. Using the clinical criteria defined by the European B 46 41 39 (95.1%) recommendations , there was a strong correlation C 20 15 14 (93.3%) between CDI-positive NAAT results and the clinical D 14 8 8 (100.0%) picture. The Meridian algorithm (EIA ImmunoCard C. Total 90 73 70 (95.8%) difficile GDH, followed by NAAT illumi gene for toxin The chart review was based on the clinical definition of C. difficile infection in the ESCMID recommendations  Goret et al. Gut Pathog (2018) 10:19 Page 5 of 6 Mont de Marsan, Mont de Marsan, France. C. H. Arcachon, Arcachon, France. gene), along with an adequate stool rejection policy, C.H.I.C Marmande-Tonneins, Marmande, France. provided a true CDI diagnosis. Acknowledgements Not applicable. Conclusion Competing interests Clinical laboratories will continue to adopt NAATs as The authors declare that they have no competing interests. part of their routine testing methods due to the higher Availability of data and materials sensitivity and short turnaround time of these tests. Not applicable. This is the first report on the impact of the implemen - Consent for publication tation of NAATs on stool rejection policies in Europe. Not applicable. The clinical laboratories took advantage of the change in the testing algorithm including NAATs to adopt Ethics approval and consent to participate Not applicable. the current recommendations. The current European guidelines have to be followed combined with by a cor- Funding rect stool rejection policy. The adoption of the largest None. number of the recommended criteria is necessary to have an effective rejection policy. An increase in the Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub- rate of rejected stool samples was observed because lished maps and institutional affiliations. hospitals no longer limited their C. difficile detection upon physicians’ requests only and furthermore they Received: 1 March 2018 Accepted: 19 May 2018 limited repeat tests. NAAT implementation will likely improve compliance with recommended stool rejection policies and improve detection of C. difficile. References Additional files 1. Cohen SH, Gerding DN, Johnson S, Kelly CP, Loo VG, McDonald LC, Pepin J, Wilcox MH. Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the society for healthcare epidemiology of Additional file 1: Table S1. Change in the number of stool specimens America (SHEA) and the infectious diseases society of America (IDSA). tested per patient expressed as a ratio of the number of tested samples/ Infect Control Hosp Epidemiol. 2010;31(5):431–55. number of patients. Statistical analysis was performed using the Chi 2. Crobach MJ, Dekkers OM, Wilcox MH, Kuijper EJ. European Society of square test. p value <0.05 was considered significant. * Not applicable. Clinical Microbiology and Infectious Diseases (ESCMID): data review and recommendations for diagnosing Clostridium difficile-infection (CDI). Clin Additional file 2: Table S2. Change in the stool rejection policy accord- Microbiol Infect. 2009;15(12):1053–66. ing to the laboratories between 2013 and 2014. Data are the number 3. Crobach MJ, Planche T, Eckert C, Barbut F, Terveer EM, Dekkers OM, Wilcox of laboratories that adopted the requested criteria for performing tests MH, Kuijper EJ. European Society of Clinical Microbiology and Infectious among the four laboratories that introduced nucleic acid amplification Diseases: update of the diagnostic guidance document for Clostridium tests (NAATs) and the five that did not introduce NAATs, between the difficile infection. Clin Microbiol Infect. 2016;22(Suppl 4):S63–81. studied periods. 4. Eastwood K, Else P, Charlett A, Wilcox M. Comparison of nine commer- cially available Clostridium difficile toxin detection assays, a real-time PCR assay for C. difficile tcdB, and a glutamate dehydrogenase detection assay to cytotoxin testing and cytotoxigenic culture methods. J Clin Microbiol. Authors’ contributions 2009;47(10):3211–7. JG, JB and FM conceived the study and wrote the article. JG and JB coordi- 5. Davies KA, Longshaw CM, Davis GL, Bouza E, Barbut F, Barna Z, Delmee nated the survey, collected the data and carried out the analysis. FP, OP, DC, M, Fitzpatrick F, Ivanova K, Kuijper E, et al. Underdiagnosis of Clostridium RS, HB, RL, DL, BL, SM and TF answered to the survey and collected the data in difficile across Europe: the European, multicentre, prospective, biannual, each included laboratory. They read and corrected the manuscript. All authors point-prevalence study of Clostridium difficile infection in hospitalised read and approved the final manuscript. patients with diarrhoea (EUCLID). Lancet Infect Dis. 2014;14(12):1208–19. 6. Cohen J, Limbago B, Dumyati G, Holzbauer S, Johnston H, Perlmutter R, Authors’ information Dunn J, Nadle J, Lyons C, Phipps E, et al. Impact of changes in Clostridium This study was presented at the 25th European Congress of Clinical difficile testing practices on stool rejection policies and C. difficile positiv- Microbiology and Infectious Diseases (ECCMID). 25–28 April 2015. Copen- ity rates across multiple laboratories in the United States. J Clin Microbiol. hagen, Denmark. JG was a recipient of an ECCMID Travel Grant 2015 for 2014;52(2):632–4. this work. The manuscript was edited for proper English language, gram- 7. Grein JD, Ochner M, Hoang H, Jin A, Morgan MA, Murthy AR. Comparison mar, punctuation, spelling, and overall style by one or more of the highly of testing approaches for Clostridium difficile infection at a large com- qualified native English-speaking editors at American Journal Experts munity hospital. Clin Microbiol Infect. 2014;20(1):65–9. (6E65-F836-8CCF-406C-DF44). 8. Fong KS, Fatica C, Hall G, Procop G, Schindler S, Gordon SM, Fraser TG. Impact of PCR testing for Clostridium difficile on incident rates and poten- Author details tial on public reporting: is the playing field level? Infect Control Hosp Laboratoire de Bactériologie, C.H.U. de Bordeaux, Groupe Hospitalier Pel- Epidemiol. 2011;32(9):932–3. legrin, Place Amélie Raba Léon, 33076 Bordeaux Cedex, France. C.H.U. de 9. Goldenberg SD, Price NM, Tucker D, Wade P, French GL. Mandatory Bordeaux, Hôpital Haut-Lévèque, Pessac, France. C.H. de Dax-Côte d’Argent, 4 5 reporting and improvements in diagnosing Clostridium difficile infection: Dax, France. C.H. de Périgueux, Périgueux, France. G.H. de La Rochelle-Ré- 6 7 an incompatible dichotomy? J Infect. 2011;62(5):363–70. Aunis, La Rochelle, France. C. H. de la Côte Basque, Bayonne, France. C.H. Goret et al. Gut Pathog (2018) 10:19 Page 6 of 6 10. Longtin Y, Trottier S, Brochu G, Paquet-Bolduc B, Garenc C, Loungnarath in a whole nation: where is the problem? Clin Microbiol Infect. V, Beaulieu C, Goulet D, Longtin J. Impact of the type of diagnostic assay 2012;18(7):E204–13. on Clostridium difficile infection and complication rates in a mandatory 22. Alcala L, Reigadas E, Marin M, Martin A, Catalan P, Bouza E. Impact of clini- reporting program. Clin Infect Dis. 2013;56(1):67–73. cal awareness and diagnostic tests on the underdiagnosis of Clostridium 11. Moehring RW, Lofgren ET, Anderson DJ. Impact of change to molecular difficile infection. Eur J Clin Microbiol Infect Dis. 2015;34(8):1515–25. testing for Clostridium difficile infection on healthcare facility-associated 23. Examen microbiologique des selles. In: Référentiel en microbiologie incidence rates. Infect Control Hosp Epidemiol. 2013;34(10):1055–61. médicale (REMIC), Chapter 15. Paris, France: Sociéte Française de Microbi- 12. Tartof SY, Yu KC, Wei R, Tseng HF, Jacobsen SJ, Rieg GK. Incidence of poly- ologie 4ème Ed; 2010. p. 105–10. merase chain reaction-diagnosed Clostridium difficile in a large high-risk 24. Davies K, Davis G, Barbut F, Eckert C, Petrosillo N, Wilcox MH. Variability cohort, 2011–2012. Mayo Clin Proc. 2014;89(9):1229–38. in testing policies and impact on reported Clostridium difficile infection 13. Planche TD, Davies KA, Coen PG, Finney JM, Monahan IM, Morris KA, rates: results from the pilot longitudinal European Clostridium difficile O’Connor L, Oakley SJ, Pope CF, Wren MW, et al. Differences in outcome infection diagnosis surveillance study (LuCID). Eur J Clin Microbiol Infect according to Clostridium difficile testing method: a prospective multicen- Dis. 2016;35(12):1949–56. tre diagnostic validation study of C. difficile infection. Lancet Infect Dis. 25. Novak-Weekley SM, Marlowe EM, Miller JM, Cumpio J, Nomura JH, Vance 2013;13(11):936–45. PH, Weissfeld A. Clostridium difficile testing in the clinical laboratory by 14. Deshpande A, Pasupuleti V, Rolston DD, Jain A, Deshpande N, Pant C, use of multiple testing algorithms. J Clin Microbiol. 2010;48(3):889–93. Hernandez AV. Diagnostic accuracy of real-time polymerase chain reac- 26. Tenover FC, Novak-Weekley S, Woods CW, Peterson LR, Davis T, Schreck- tion in detection of Clostridium difficile in the stool samples of patients enberger P, Fang FC, Dascal A, Gerding DN, Nomura JH, et al. Impact of with suspected Clostridium difficile Infection: a meta-analysis. Clin Infect strain type on detection of toxigenic Clostridium difficile: comparison Dis. 2011;53(7):e81–90. of molecular diagnostic and enzyme immunoassay approaches. J Clin 15. Cardona DM, Rand KH. Evaluation of repeat Clostridium difficile enzyme Microbiol. 2010;48(10):3719–24. immunoassay testing. J Clin Microbiol. 2008;46(11):3686–9. 27. Eckert C, Coignard B, Hebert M, Tarnaud C, Tessier C, Lemire A, Burghoffer 16. Mohan SS, McDermott BP, Parchuri S, Cunha BA. Lack of value of repeat B, Noel D, Barbut F. Clinical and microbiological features of Clostridium dif- stool testing for Clostridium difficile toxin. Am J Med. 2006;119(4):356 ficile infections in France: the ICD-RAISIN 2009 national survey. Med Mal e357–358 e357. Infect. 2013;43(2):67–74. 17. Nemat H, Khan R, Ashraf MS, Matta M, Ahmed S, Edwards BT, Hussain 28. Archibald LK, Banerjee SN, Jarvis WR. Secular trends in hospital-acquired R, Lesser M, Pekmezaris R, Dlugacz Y, et al. Diagnostic value of repeated Clostridium difficile disease in the United States, 1987-2001. J Infect Dis. enzyme immunoassays in Clostridium difficile infection. Am J Gastroen- 2004;189(9):1585–9. terol. 2009;104(8):2035–41. 29. McDonald LC, Owings M, Jernigan DB. Clostridium difficile infection in 18. Dubberke ER, Han Z, Bobo L, Hink T, Lawrence B, Copper S, Hoppe-Bauer patients discharged from US short-stay hospitals, 1996–2003. Emerg J, Burnham CA, Dunne WM Jr. Impact of clinical symptoms on interpreta- Infect Dis. 2006;12(3):409–15. tion of diagnostic assays for Clostridium difficile infections. J Clin Microbiol. 30. Pepin J, Valiquette L, Alary ME, Villemure P, Pelletier A, Forget K, Pepin 2011;49(8):2887–93. K, Chouinard D. Clostridium difficile-associated diarrhea in a region of 19. Debast SB, Bauer MP, Kuijper EJ. European Society of Clinical Microbiology Quebec from 1991 to 2003: a changing pattern of disease severity. CMAJ. and Infectious Diseases: update of the treatment guidance document for 2004;171(5):466–72. Clostridium difficile infection. Clin Microbiol Infect. 2014;20(Suppl 2):1–26. 31. Polgreen PM, Yang M, Bohnett LC, Cavanaugh JE. A time-series analysis 20. Akbari M, Vodonos A, Silva G, Wungjiranirun M, Leffler DA, Kelly CP, of Clostridium difficile and its seasonal association with influenza. Infect Novack V. The impact of PCR on Clostridium difficile detection and clinical Control Hosp Epidemiol. 2010;31(4):382–7. outcomes. J Med Microbiol. 2015;64(9):1082–6. 21. Alcala L, Martin A, Marin M, Sanchez-Somolinos M, Catalan P, Pelaez T, Bouza E. The undiagnosed cases of Clostridium difficile infection Ready to submit your research ? Choose BMC and benefit from: fast, convenient online submission thorough peer review by experienced researchers in your ﬁeld rapid publication on acceptance support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations maximum visibility for your research: over 100M website views per year At BMC, research is always in progress. Learn more biomedcentral.com/submissions
Gut Pathogens – Springer Journals
Published: May 30, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera