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 ~  Abstract
 ~ Introduction
 ~  Materials and Me...
 ~ Results
 ~ Discussion
 ~ Conclusion
 ~ Acknowledgement
 ~  References
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  Table of Contents  
ORIGINAL ARTICLE
Year : 2014  |  Volume : 32  |  Issue : 4  |  Page : 391-397
 

Distribution of different yeasts isolates among trauma patients and comparison of accuracy in identification of yeasts by automated method versus conventional methods for better use in low resource countries


1 Department of Laboratory Medicine (Microbiology Division), All India Institute of Medical Sciences, New Delhi, India
2 Department of Microbiology,All India Institute of Medical Sciences, New Delhi, India
3 Department of Surgery, Jai Prakash Narayan Apex Trauma Centre, All India Institute of Medical Sciences, New Delhi, India

Date of Submission28-Jul-2013
Date of Acceptance06-Feb-2014
Date of Web Publication4-Oct-2014

Correspondence Address:
P Mathur
Department of Laboratory Medicine (Microbiology Division), All India Institute of Medical Sciences, New Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0255-0857.142243

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 ~ Abstract 

Introduction: As most trauma patients require long-term hospital stay and long-term antibiotic therapy, the risk of fungal infections in such patients is steadily increasing. Early diagnosis and rapid treatment is life saving in such critically ill trauma patients. Aims: To see the distribution of various species of Candida among trauma patients and compare the accuracy, rapid identification and cost effectiveness between VITEK 2, CHROMagar and conventional methods. Settings and design: Retrospective laboratory-based surveillance study performed over a period of 52 months (January 2009 to April 2013) at a level I trauma centre in New Delhi, India. Materials and Methods: All microbiological samples positive for Candida were processed for microbial identification using standard methods. Identification of Candida was done using chromogenic medium and by automated VITEK 2 Compact system and later confirmed using the conventional method. Time to identification in both was noted and accuracy compared with conventional method. Statistical analysis: Performed using the SPSS software for Windows (SPSS Inc. Chicago, IL, version 15.0). P values calculated using χ2 test for categorical variables. A P < 0.05 was considered significant. Results: Out of 445 yeasts isolates, Candida tropicalis (217, 49%) was the species that was maximally isolated. VITEK 2 was able to correctly identify 354 (79.5%) isolates but could not identify 48 (10.7%) isolates and wrongly identified or showed low discrimination in 43 (9.6%) isolates but CHROM agar correctly identified 381 (85.6%) isolates with 64 (14.4%) misidentification. Highest rate of misidentification was seen in C. tropicalis and C. glabrata (13, 27.1% each) by VITEK 2 and among C. albicans (9, 14%) by CHROMagar. Conclusions: Though CHROMagar gives identification at a lower cost compared with VITEK 2 and are more accurate, which is useful in low resource countries, its main drawback is the long duration taken for complete identification.


Keywords: Accuracy, automated method, Candida spp., CHROMagar, cost-effectiveness, trauma


How to cite this article:
Rajkumari N, Mathur P, Xess I, Misra M C. Distribution of different yeasts isolates among trauma patients and comparison of accuracy in identification of yeasts by automated method versus conventional methods for better use in low resource countries. Indian J Med Microbiol 2014;32:391-7

How to cite this URL:
Rajkumari N, Mathur P, Xess I, Misra M C. Distribution of different yeasts isolates among trauma patients and comparison of accuracy in identification of yeasts by automated method versus conventional methods for better use in low resource countries. Indian J Med Microbiol [serial online] 2014 [cited 2018 Jul 18];32:391-7. Available from: http://www.ijmm.org/text.asp?2014/32/4/391/142243



 ~ Introduction Top


Due to the rapid industrialisation in the developing countries, trauma related to machines is increasing and hence the need for more and better trauma care. Patients who survive the initial injury acquire nosocomial infections, which are the leading cause of death in them. [1],[2] Such patients require long-term hospital stay and hence making them vulnerable to hospital-acquired infections. Candida is fast becoming a very important pathogen among the critically ill hospitalised patients.

Candida is one of the major pathogens causing blood stream infections worldwide. [3] Its incidence is on a rise due to unscrupulous use of antibiotics among critically ill patients. Candidiasis is not only associated with a mortality of about 30-40%, but also extends the duration of hospital stay and increases the cost of medical care. [4] This shows that rapid identification for the early and timely treatment can be life saving for such patients.

Identification of yeast pathogens by traditional methods requires several days and specific mycological media. These methods are thus labour intensive and time consuming. Several brands of chromogenic media are available for rapid identification of Candida spp. The chromogenic media contain substrates that react with enzymes secreted by the target microorganisms to yield colonies of varying colours. [5],[6],[7]

Many commercial automated identification systems have also been developed and are being used in some routine clinical microbiology laboratories. These systems assert for accurate and rapid identification of medically relevant bacteria and yeast. [8],[9],[10],[11],[12] The VITEK 2 system (BioMιrieux, Durham, US) is a fully automated system utilised for the identification and susceptibility testing of microorganisms. In conjunction with the VITEK ID-YST card, the VITEK 2 system allows the identification of clinically important yeasts and yeast-like organisms in 15 h due to a sensitive fluorescence-based technology. [13] The ID-YST database of VITEK 2 for yeast identification comprises 51 different taxa, including newly described species, taking into account recent advances in taxonomy. Regarding its accuracy in identification, many queries need to be answered. Is the yeast identification by this method at par with the bacterial identification in accuracy? Is using the automated methods alone sufficient in reliability and accuracy? Can we do away the conventional methods of yeasts identification, which is very time consuming and cumbersome?

We have tried to explore through this study retrospectively the accuracy of the automation in rapid and easy identification of the different species of Candida compared with the conventional methods. Also, this study tried to see if we can do without the conventional media and tests for accurate identification. The study also tried to evaluate the efficiency in cost between the two methods.


 ~ Materials and Methods Top


This study was conducted in an apex tertiary trauma care centre of India for a period of 52 months from January 2009 to April 2013. All the clinical samples sent for microbiological culture from different hospitalised trauma patients were scanned and those showing yeasts on Gram's stained smear or wet mount according to the type of sample were noted.

Standard strains were used as controls for evaluation of the various methods: Candida albicans ATCC 10231, C. tropicalis ATCC 13803, C. krusei ATCC 14243 and C. glabarata 15126, C. kefyr ATCC 204093, C. guilliermondii ATCC 6260, and Cryptococcus neoformans ATCC 14116.

All yeasts were identified to the species level using the automated method by VITEK 2 (bioMeriιux, Durham, USA) in parallel to the chromogenic media (CHROMagar Candida, Becton-Dickinson, USA) following the manufacturer's protocol and results interpreted. Those isolates that give ≥90% discrimination are identified as true or correct identification by VITEK 2 but those that give low discrimination (≤50% discrimination or many species of Candida) were taken as "3 types identification of low discrimination" and those that cannot be identified were taken as "Unidentified". Further the results were confirmed by the conventional methods of phenotypic and biochemical methods of identification as per standard microbiological methods. [14],[15]

All the Candida isolates irrespective of the clinical specimens were initially sub-cultured onto Sabouraud dextrose agar (SDA) medium and incubated at 37°C till growth appeared. Colonies from the SDA were then plated onto corn meal agar with Tween 80 for morphological examination [14],[15] and triphenyltetrazolium chloride (TTC) medium for determination of pigment production. A germ tube test was performed on yeast-like colonies for presumptive identification of C. albicans. The strains were further characterised by manual sugar assimilation methods. [14],[16] The tests were performed according to standard methods and using the above control strains.

Growth from SDA slants or from the blood agar was plated onto CHROM agar® (CHROMagar Candida, BD, USA). The plates were incubated at 37°C for 48 h and the colony morphology (colour, size and texture) were assessed to interpret the identification of species. The interpretation was done on published appearance of various species on chromogenic agar: [17],[18] Parrot green colonies of C. albicans; steel blue colonies of C. tropicalis accompanied by purple pigmentation, which diffuses into surrounding agar by growth; larger, fuzzy, rose-colored colonies with white edges of C. krusei; smooth white to light pink colonies of C. glabrata, which later became pink; pink to lavender colonies of C. parapsilosis; grey to pale pink of Cryptococcus neoformans and green colour with pale borders of C. rugosa. The quality of the media was checked every time with the ATCC strains. Species were identified when the isolates conformed unequivocally to these morphological features. Two different observers observed the morphology of each isolates. All isolates that gave doubtful morphology or that did not conform to the accepted morphological features were taken as "unidentified" or "misidentified".

Finally, the results of the two methods were compared with each other and confirmed with the conventional method and results interpreted as to which method gives faster and accurate result compared with the conventional method.

Data regarding the type of sample from which the yeasts were isolated, the ward from which it came, the type of trauma were noted. Yearly and month wise distribution pattern was also analysed. Also, due care was taken not to duplicate the patient during the study period.

Also, in this study we tried to see the cost of using automated method per test compared with that of chromogenic agar for better utilisation in low resource countries.

Statistical methods

Statistical analyses were performed using the SPSS software for Windows (SPSS Inc. Chicago, IL, version 15.0). Identification rates were presented as percentages. The identification rate to individual methods, its accuracy when compared with the conventional method and yearly and monthly trend of the different yeasts over the period of 52 months were compared and analysed. P values were calculated using χ2 test for categorical variables. A P < 0.05 was considered significant. McNemar-Bowker's test was used to analyse the symmetrical values.


 ~ Results Top


From a total of 445 non-duplicate trauma patients from whom yeasts were isolated during the study period, male patients (317, 71.2%) pre-dominated the female patients (128, 29%) in terms of isolation frequency (χ΂ = 0.236, df = 11). It was seen that maximum yeasts were isolated from blood (311,70%) followed by urine (93,21%), central venous pressure catheter tips (18,4%), tissue (8, 2%), pleural fluid (4, 1%), tracheal aspirates (4, 1%), broncho-alveolar lavage (3, 0.7%), peritoneal fluid (1, 0.2%), pus (1, 0.2%), wound debris (1, 0.2%) and drain fluid (1, 0.2%) in decreasing frequencies. Highest isolation was seen in samples of patients admitted to the surgery intensive care unit (ICU) (224, 50.3%) followed by samples from the neurosurgery ICU (117, 26.3%), orthopaedic ward (63, 14.1%), neurosurgery ward (38, 9%) and least in surgery ward (3, 1%). C. tropicalis (217, 49%) was the species that was maximally isolated among the trauma patients. Other Candida spp., which were also isolated in high numbers, were C. albicans (75, 17%), C. parapsilosis (58, 13%), C. glabrata (36, 8%) and C. rugosa (22, 5%). The species wise distribution of different Candida in different samples, wards and different patients is given in detail in [Table 1].
Table 1: Demographic profile of the patients from whom the different yeasts were isolated (n, %)


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Of the total 445 isolates, VITEK 2 was able to correctly identify 354 (79.5%) isolates but could not identify 48 (10.7%) isolates and wrongly identified or showed low discrimination in 43 (9.6%) isolates. The different species of Candida correctly identified, along with the pattern of yeasts identification by VITEK 2 is given in [Table 2]. All were counterchecked with the final confirmatory tests for yeasts using the conventional method. The failure to identify yeasts by VITEK 2 was highest among C. tropicalis and C. glabrata (13, 27.1% each) and second highest among C. albicans (6, 12.5%). Among those showing low discrimination or misidentification, the highest result seen was C. famata and C. parapsilosis followed by C. parapsilosis and C. tropicalis, which were later correctly identified using the conventional method. This included those that were showing three different species and some that were identified to the species level but wrongly identified when compared with the conventional method.
Table 2: Comparison of yeasts identification by VITEK 2 and CHROMagar and its accuracy when compared with that of conventional method


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Regarding the yeasts identification by CHROM agar, it correctly identified 381 (85.6%) out of a total of 445 isolates. Out of the remaining 64 (14.4%), 49 (11%) was misidentified because of the lack of proper colour development of the yeasts colonies on the media or due to improper interpretation of the colour developed and rest 15 (3.4%) of them were unidentified. All these were later confirmed using the conventional method. C. albicans (9, 14%) followed by C. parapsilosis (5, 8%) and C. tropicalis (4, 6.3%) were among those that were commonly misidentified or unidentified by CHROM agar. Details regarding its identification pattern are shown in [Table 2].

When identification by VITEK 2 was compared with the CHROMagar, higher rate of true identification was seen in CHROMagar then in VITEK 2. VITEK 2 showed similar identification with CHROMagar in 139 C. tropicalis isolates, whereas one each of C. glabrata and C. rugosa were wrongly identified as C. tropicalis but correctly identified by CROMagar. C. albicans were similarly identified by both the methods in 49 (98%) isolates, whereas VITEK identified 1 isolate of C. famata as C. albicans but correctly identified by CHROMagar. Out of a total of 16 isolates of C. famata identified by VITEK 2, 4 (25%) were similarly identified by both the methods as C. famata, whereas among the remaining 12 isolates, CHROMagar identified 4 (25%) of them as C. parapsilosis, 3 (18.8%) as C. tropicalis, 2 (12.5%) each as C. albicans C. glabrata and 1 (6.3%) of them as C. rugosa. All the C. glabrata (10, 100%) and C. krusei (3, 100%) isolates were identified similarly by both the methods.

Of a total of five isolates identified as C. guilliermondii by VITEK 2, CROMagar showed similar identification with that of VITEK 2 in four (80%) isolates, whereas remaining one (20%) was identified as C. tropicalis by CHROMagar. Out of a total 17 isolates of C. hemuloni identified by VITEK 2, CHROMagar showed similar identification with VITEK 2 in 5 (29.4%) isolates, whereas CHROMagar identified 4 (23.5%) isolates each as C. glabrata, C. parapsilosis and C. rugosa. One isolate identified as C. laurentii by VITEK 2 was identified as C. glabrata both by the CHROMagar and conventional method. Two isolates identified as C. lusitaniae by VITEK 2 were identified as C. tropicalis by CHROMagar but one each was confirmed as C. tropicalis and C. parapsilosis by the conventional method. Of a total of 48 isolates identified as C. parapsilosis by VITEK 2, 37 (77.1%) were identified as the same species by both the methods. However, six (12.5%) were identified by CHROMagar as C. tropicalis and one (2.1%) each were identified as C. hemuloni, C. lusitaniae and Nocardia spp. One of the remaining was unidentified by CHROMagar but identified as C. parapsilosis by VITEK 2. Among the 23 isolates of C. rugosa identified by VITEK 2, 12 (%) could be identified equally by both the methods; remaining 7 (30.4%) were identified as C. tropicalis and 2 (8.7%) each were identified as C. albicans and C. glabrata, respectively, by CHROMagar. VITEK 2 identified two isolates as C. utilis but one of them was identified as C. krusei by both CHROMagar and conventional method and remaining one was unidentified by CHROMagar but identified as C. glabrata by conventional method.

Of the total 19 isolates identified as Cryptococcus laurentii by VITEK 2, 10 (52.6%) isolates were identified as C. tropicalis, 4 (21.1%) were identified as C. parapsilosis, whereas 2 (10.5%) and 1 (5.3%) were identified as C. albicans and C. rugosa, respectively, by CHROMagar, which was also confirmed by conventional method. However, two isolates identified as Crypotococcus launrentii by VITEK 2 could not be identified by CHROMagar but were identified as C. parapsilosis and Trichosporon asahii each by the conventional method. VITEK 2 identified 10 isolates as Streptococcus ciferii but 9 (90%) were identified as C. albicans and 1 was identified as C. tropicalis by CHROMagar. However, the conventional method identified eight (80%) of them as C. albicans and two (20%) isolates as C. tropicalis. Of the total seven isolates identified as Trichosporon asahii by VITEK 2, one (4.3%) each was identified as C. tropicalis and C. glabrata, respectively, by both CROMagar and conventional methods. The remaining five (71.5%) were unidentified by CHROMagar but confirmed to be Trichosporon asahii by the conventional method.

Of the total 48 (10.7%) isolates unidentified by VITEK 2, CHROMagar was able to identify 11 (22.9%) of them as C. tropicalis, 9 (18.8%) each as C. albicans and C. glabrata, 4 (8.3%) each as C. krusei and C. rugosa, 3 (6.3%) as C. parapsilosis, 2 (4.2%) as C. hemuloni and 1 (2.1%) each as C. famata and Nocardia spp. However, the remaining four (8.3%) were unidentified by CHROMagar. The isolates where VITEK 2 gives a low discrimination and its full identification are shown in [Table 3].
Table 3: Analysis of isolates with low discrimination by VITEK 2 and after confirmatory tests


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Pathogenic yeasts were maximally isolated from the trauma patients during the months of September-October but the frequency of isolation slowly declined and a trough was seen during the months of December-January (χ2 =0.268, df = 121). Regarding the yearly distribution pattern of yeasts, rate of isolation was highest at the beginning of this study (2008-2009), slowly declined (2010-2011) and then showed slight increase again (2012-2013). Details are shown in [Table 4].
Table 4: Yearly distribution of different species of yeasts during the study period (count and percentage count within that year)


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Also, we have tried to see the cost efficiency between the two methods. A set of 20 identification cards of VITEK 2 costs approximately 10,400 Indian Rupees (171 United States Dollar approx.) and 1 card was used for identification of 1 isolate per patient. So, one sample patient cost 520 INR (9 USD approx.). However, a 500 g containing packet of CHROMagar (BD, USA) cost 14,700 INR (241 USD) approximately and one such a packet makes 30 plates of CHROMagar media. As one plate is used to identify one isolate per patient, the cost of one sample patient was 490 INR (8 USD approx.). Hence, CHROMagar was more cost efficient when compared with VITEK 2.


 ~ Discussion Top


In our study, we observed that VITEK 2 can give identification after incubation at 35°C for at least 15 h regarding the isolate and can also give its antifungal sensitivity pattern at the same time, which the chromogenic media could not. CHROMagar Candida, which is based on the development of colours for its identification, requires incubation at 30°C for at least 48 h for its complete identification. Though VITEK 2 gives a faster rate of identification compared with the CHROMagar, both methods gives a quicker result compared with the conventional method.

In terms of accuracy in identification, VITEK 2 was correctly able to identify 354 (79.5%) isolates without additional tests but could not identify 48 (10.7%) isolates and wrongly identified or showed low discrimination in 43 (9.6%) isolates in our study. This finding was a little lower compared with what was seen in other studies. [13],[19] In one study, the rates of correct identification with or without additional tests were 92.1% and 87.6%, respectively. [13] CHROMagar was correctly able to identify 381 (85.6%) out of a total of 445 isolates, whereas 11% was misidentified and remaining 3.4% was unidentified in our study. This finding was concordant to what was seen in other studies. [19]

Like the trend seen worldwide, [13],[19],[20] our study also observed a predominance of non-albicans Candida over C. albicans. C. tropicalis (216, 48.5%) was the maximally isolated species followed by C. albicans (75, 17%), C. parapsilosis (58, 13%) and C. rugosa (22, 5%).

As complexity in the pattern of disease treatment is increasing, there is a steady rise in infections by pathogenic yeasts; hence the need for early and rapid method for diagnosis. We have seen that CHROMagar forms a good medium for rapid screening of the yeasts but it is time consuming requiring at least 48 h to get an identification. However, VITEK 2 gives rapid identification along with its sensitivity pattern, which will help in early instillation of empiric antifungal therapy and is life saving in such critically ill trauma patients. The only drawback is the cost-factor considering the fact that it costs more than CHROMagar per sample patient, which is a factor of concern in low resource countries. Hence, we can use CHROM agar for routine screening supplemented with VITEK 2 for rapid identification wherever needed. VITEK 2 can also help to identify where there is confusion in the colour interpretation of colonies on CHROMagar. However, as none of the two methods gives 100% accuracy in identification, conventional methods are still needed to confirm their accuracy.


 ~ Conclusion Top


Even though CHROMagar gives identification at a lower cost compared with VITEK 2, which is useful in low resource countries, its main drawback is the long duration taken for complete identification. As early and rapid instillation of treatment can save the life of patients with fungal infections, rapid diagnosis is the need of the hour. So, we can use VITEK 2 for rapid identification supplemented with CHROMagar for correct identification wherever needed.


 ~ Acknowledgement Top


The authors would like to thank All India Institute of Medical Sciences, New Delhi for supporting this study. Also, the authors extend their gratitude to Mr Pawan Kumar for his help in compiling the data and Mrs Kusum Chopra for her help in statistical analysis.

 
 ~ References Top

1.Cornwell EE, Jacobs D, Walker M, Jacobs L, Porter J, Fleming A. National Medical Association Surgical Section position paper on violence prevention: A resolution of trauma surgeons caring for victims of violence. JAMA 1995;73:1788-9.  Back to cited text no. 1
    
2.Papia G, McLellan BA, El-Helou P, Louie M, Rachlis A, Szalai JP. Infection in hospitalized trauma patients: Incidence, risk factors, and complications. J Trauma 1999;47:923-7.  Back to cited text no. 2
    
3.Horn DL, Neofytos D, Anaissie EJ, Fishman JA, Steinbach WJ, Olyaei AJ, et al. Epidemiology and outcomes of candidemia in 2019 patients: Data from the Prospective Antifungal Therapy Alliance Registry. Clin Infect Dis 2009;48:1695-703.  Back to cited text no. 3
    
4.Lewis RE. Overview of the changing epidemiology of candidemia. Curr Med Res Opin 2009;25:1732-40.  Back to cited text no. 4
[PUBMED]    
5.Hospenthal DR, Beckius ML, Floyd KL, Horvath LL, Murray CK. Presumptive identification of Candida species other than C. albicans, C. krusei, and C. tropicaliswith the chromogenic medium CHROMagar Candida. Ann Clin Microbiol Antimicrob 2006;5:1.  Back to cited text no. 5
    
6.Pfaller MA, Houston A, Coffmann S. Application of CHROMagar Candida for rapid screening of clinical specimens for Candida albicans, Candida tropicalis, Candida krusei, and Candida (Torulopsis) glabrata. J Clin Microbiol 1996;34:58-61.  Back to cited text no. 6
    
7.Sivakumar VG, Shankar P, Nalina K, Menon T. Use of CHROMagar in the differentiation of common species of Candida. Mycopathologia 2009;167:47-9.  Back to cited text no. 7
    
8.Aubertine CL, Rivera M, Rohan SM, Larone DH. Comparative study of the new colorimetric VITEK 2 yeast identification card versus the older fluorometric card and of CHROMagar Candida as a source medium with the new card. J Clin Microbiol 2006;44:227-8.  Back to cited text no. 8
    
9.Buchaille L, Freydière AM, Guinet R, Gille Y. Evaluation of six commercial systems for identification of medically important yeasts. Eur J Clin Microbiol Infect Dis 1998;17:479-88.  Back to cited text no. 9
    
10.Hasyn JJ, Buckley HR. Evaluation of the AutoMicrobic system for identification of yeasts. J Clin Microbiol 1982;16:901-4.  Back to cited text no. 10
[PUBMED]    
11.Sood P, Mishra B, Dogra V, Mandal A. Comparison of Vitek Yeast Biochemical Card with conventional methods for speciation of Candida. Indian J Pathol Microbiol 2000;43:143-5.  Back to cited text no. 11
[PUBMED]  Medknow Journal  
12.Wadlin JK, Hanko G, Stewart R, Pape J, Nachamkin I. Comparison of three commercial systems for identification of yeasts commonly isolated in the clinical microbiology laboratory. J Clin Microbiol 1999;37:1967-70.  Back to cited text no. 12
    
13.Graf B, Adam T, Zill E, Gobel UB. Evaluation of the VITEK 2 system for rapid identification of yeasts and yeast-like organisms. J Clin Microbiol 2000;38:1782-5.  Back to cited text no. 13
    
14.Al-Doory Y. The yeasts. In: Al-Doory Y, editor. Laboratory Medica Mycology. Philadelphia: Lea and Febiger; 1980. p. 249-83.  Back to cited text no. 14
    
15.Larone DH. A Guide to Identification. Medically important fungi. 4 th ed. Washington DC: ASM Press; 2002.  Back to cited text no. 15
    
16.Rippon JW. Candidiasis and the pathogenic yeasts. In: Wonseiwicz M, editor. Medical Mycology. Philadelphia: W.B. Saunders; 1988. p. 531-81.  Back to cited text no. 16
    
17.García-Martos P, Mira-Gutiérrez J, Galán-Sánchez F, Hernández-Molina JM. Usefulness of the CHROM-agar Candida culture medium in the differentiation and presumed identification of yeast of clinical interest. Enferm Infecc Microbiol Clin 1997;15:70-2.  Back to cited text no. 17
    
18.Giusiano GE, Mangiaterra ML. Rapid differentiation and presumptive identification of yeasts using Candida CHROM-agar medium. Rev Argent Microbiol 1998;30:100-3.  Back to cited text no. 18
    
19.Agarwal S, Manchanda V, Verma N, Bhalla P. Yeasts identification in routine microbiology laboratory and its clinical relevance. Indian J Med Microbiol 2011;29:172-7.  Back to cited text no. 19
[PUBMED]  Medknow Journal  
20.Singh RI, Xess I, Mathur P, Behera B, Gupta B, Misra MC. Epidemiology of candidaemia in critically ill trauma patients: Experiences of a level I trauma centre in North India. J Clin Microbiol 2011;60:342-8.  Back to cited text no. 20
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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