A New Bacterial Growth Graph Pattern Analysis to Improve Positive Predictive Value of Continuous Monitoring Blood Culture System.

False positive signals (FPSs) of continuous monitoring blood culture system (CMBCS) cause delayed reporting time and increased laboratory cost. This study aimed to analyze growth graphs digitally in order to identify specific patterns of FPSs and true positive signals (TPSs) and to find the method for improving positive predictive value (PPV) of FPS and TPS. 606 positive signal samples from the BACTEC FX (BD, USA) CMBCS with more than one hour of monitoring data after positive signal were selected, and were classified into FPS and TPS groups using the subculture results. The pattern of bacterial growth graph was analyzed in two steps: the signal stage recorded using the monitoring data until positive signal and the post-signal stage recorded using one additional hour of monitoring data gained after the positive signal. The growth graph before the positive signal consists of three periods; initial decline period, stable period, and steeping period. Signal stage analyzed initial decline period and stable period, and classified the graphs as standard, increasing, decreasing, irregular, or defective pattern, respectively. Then, all patterns were re-assigned as confirmed or suspicious pattern in the post-signal stage. Standard, increasing, and decreasing patterns with both initial decline period and stable period are typical patterns; irregular patterns lacking a smooth stable period and defective patterns without an initial decline period are false positive patterns. The false positive patterns have 77.2% of PPV for FPS. The confirmed patterns, showing a gradually increasing fluorescence level even after positive signal, have 97.0% of PPV for TPS.

Comparison of three rapid influenza diagnostic tests with digital readout systems and one conventional rapid influenza diagnostic test.

BACKGROUND: Rapid influenza diagnostic tests (RIDTs) show variable sensitivities in clinical settings. We aimed to compare three digital RIDTs and one conventional RIDT. METHODS: We assessed 218 nasopharyngeal swabs from patients between neonates and 90 years old in 2016. Three digital RIDTs were BUDDI, Sofia Influenza A+B Fluorescence Immunoassay, Veritor System Flu A+B assay. One conventional test was the SD Bioline Influenza Ag A/B/A(H1N1/2009). All test results were compared with those from the Anyplex Flu A/B Typing Real-time Detection real-time PCR. The four RIDTs were tested with diluted solutions from the National Institute for Biological Standards and Control (NIBSC) to compare lower detection limit. Cross-reactivity of four RIDTs within other respiratory viruses was identified. RESULTS: For influenza A, BUDDI, Sofia, Veritor, and Bioline showed 87.7%, 94.5%, 87.7%, and 72.6% sensitivity, and 100%, 97.7%, 96.5%, and 100% specificity. For influenza B, BUDDI, Sofia, Veritor, and Bioline showed 81.7%, 91.7%, 81.7%, and 78.3% sensitivity, and 100%, 95.3%, 100%, and 100% specificity, respectively. Each RIDT could detect diluted NIBSC solution, according to the level of dilution and specific influenza subtypes. Cross-reactivity of four RIDTs with other respiratory viruses was not noted. CONCLUSIONS: Sofia showed the highest sensitivity for influenza A and B detection. BUDDI and Veritor showed higher detection sensitivity than a conventional RIDT for influenza A detection, but similar results for influenza B detection. Further study is needed to compare the test performance of RIDTs according to specific, prevalent influenza subtypes.

Correction Equation for Estimation of Actual Potassium Concentration in Hemolyzed Specimen.

BACKGROUND: A spuriously elevated serum potassium value could possibly cause medical decision errors because it leads to masked hypokalemia or pseudohyperkalemia. The aim of this study was to develop a correction equation for falsely elevated potassium level caused by hemolysis. METHODS: A total of 988 samples with a hemolysis index (HI) value greater than the potassium alert HI value were recollected within two hours from initial collection. We divided 988 paired samples into 3 groups: hypokalemia, normal, and hyperkalemia. When samples were checked after recollection within 2 hours, 525 cases showed HI of 1. We analyzed the relationship between the delta of initial and recollected samples' HI values and the delta of initial and recollected samples' potassium levels, resulting in 5 different delta groups. RESULTS: The proportion of masked hypokalemia and pseudohyperkalemia was 17.6% (125/710) and 64.1% (139/217), respectively. The trend and distribution of potassium concentration for each of the 5 delta HI groups according to delta HI level showed an exponential curve. From this exponential curve function, a correction equation for estimation of true potassium concentration in hemolyzed specimens was calculated: measured potassium (-0.0561e 0.6578* delta HI + 0.0804). CONCLUSIONS: The clinical application of the correction equation for adjusting the hemolysis effect on potassium concentration could be useful for the detection of masked hypokalemia or pseudohyperkalemia.

Scoring system for detecting spurious hemolysis in anticoagulated blood specimens.

BACKGROUND: The identification of in vitro hemolysis (IVH) using a hematology analyzer is challenging because centrifugation of the specimens cannot be performed for cell counts. In the present study, we aimed to develop a scoring system to help identify the presence of hemolysis in anticoagulated blood specimens. METHODS: Thirty-seven potassium EDTA anticoagulated blood specimens were obtained, and each specimen was divided into 3 aliquots (A, B, and C). Aliquots B and C were mechanically hemolyzed by aspirating 2 and 5 times, respectively, using a 27-gauge needle and then tested; aliquot A was analyzed immediately without any hemolysis. After the cells were counted, aliquots B and C were centrifuged and the supernatants were tested for the hemolytic index and lactate dehydrogenase levels. RESULTS: The 4 hematologic parameters were selected and scored from 0 to 3 as follows:< 34.0, 34.0-36.2, 36.3-38.4, and ≥38.5 for mean cell hemoglobin concentration (MCHC, g/dL); <0.02, 0.02, 0.03, and ≥0.04 for red blood cell ghosts (10(12)/L); <0.13, 0.13-0.38, 0.39-1.30, and ≥1.31 for difference value (g/dL) of measured hemoglobin and calculated hemoglobin; and <0.26, 0.26-0.95, 0.96-3.34, and ≥3.35 for difference value (g/dL) of MCHC and cell hemoglobin concentration mean. The hemolysis score was calculated by adding all the scores from the 4 parameters. At the cutoff hemolysis score of 3, the IVH of aliquots B and C were detected as 64.9% and 91.9%, respectively. CONCLUSIONS: The scoring system might provide effective screening for detecting spurious IVH.

Development of an integrated reporting system for verifying hemolysis, icterus, and lipemia in clinical chemistry results.

BACKGROUND: Hemolysis, icterus, and lipemia (HIL) cause preanalytical interference and vary unpredictably with different analytical equipments and measurement methods. We developed an integrated reporting system for verifying HIL status in order to identify the extent of interference by HIL on clinical chemistry results. METHODS: HIL interference data from 30 chemical analytes were provided by the manufacturers and were used to generate a table of clinically relevant interference values that indicated the extent of bias at specific index values (alert index values). The HIL results generated by the Vista 1500 system (Siemens Healthcare Diagnostics, USA), Advia 2400 system (Siemens Healthcare Diagnostics), and Modular DPE system (Roche Diagnostics, Switzerland) were analyzed and displayed on physicians' personal computers. RESULTS: Analytes 11 and 29 among the 30 chemical analytes were affected by interference due to hemolysis, when measured using the Vista and Modular systems, respectively. The hemolysis alert indices for the Vista and Modular systems were 0.1-25.8% and 0.1-64.7%, respectively. The alert indices for icterus and lipemia were <1.4% and 0.7% in the Vista system and 0.7% and 1.0% in the Modular system, respectively. CONCLUSIONS: The HIL alert index values for chemical analytes varied depending on the chemistry analyzer. This integrated HIL reporting system provides an effective screening tool for verifying specimen quality with regard to HIL and simplifies the laboratory workflow.

A case associated with comorbidities among cerebral infarction, idiopathic thrombocytopenic purpura, and triple x syndrome.

A 46-year-old female presented to the emergency room due to the chief complaint of left-sided weakness. By imaging study, she was diagnosed with cerebral infarction. Thrombolytic and antiplatelet agents were not considered due to the "golden hour" for treatment having passed and a low platelet count. The peripheral blood smear, bone marrow biopsy, and aspirate findings were consistent with immune thrombocytopenic purpura. The chromosome analysis revealed the 47,XXX karyotype. To the best of our knowledge, this is the first case report associated with the comorbidities of cerebral infarction, idiopathic thrombocytopenic purpura, and triple X syndrome.

Delta neutrophil index discriminates true bacteremia from blood culture contamination.

BACKGROUND: Delta neutrophil index (DNI) has been reported to be useful in the diagnosis of sepsis. We evaluated the role of DNI for differentiating true bacteremia from blood contamination and compared the DNI value with previously validated markers such as procalcitonin (PCT) and C-reactive protein (CRP). METHODS: The blood culture positive group was subdivided into true bacteremia (n=199) and contamination (n=158). The blood cultures were incubated in the BacT/Alert 3D (bioMérieux, Marcyl'Etoile, France) and BACTEC FX (Becton Dickinson, Sparks, MD, USA) systems for 5days. Data of complete blood cell count were collected from an automatic cell analyzer (ADVIA2120 Hematology System, Siemens Healthcare Diagnostics) to calculate DNI. RESULTS: Concentrations for DNI, PCT, and CRP were significantly higher in the true bacteremia group. When the gram-positive and gram-negative infections were compared among true bacteremia, only PCT was increased significantly in GNB bacteremia. DNI levels were well correlated with PCT (r=0.564, P<0.0001) and CRP (r=0.344, P<0.001) using the Spearman test among the culture positive bacteremia. The area under the ROC curve was 0.75 for PCT, 0.69 for CRP, and 0.69 for DNI. CONCLUSIONS: We demonstrated the usefulness of DNI in differentiating true bacteremia from contamination in patients with a positive blood culture.

Macrolide resistance of Mycoplasma pneumoniae and its detection rate by real-time PCR in primary and tertiary care hospitals.

BACKGROUND: This study aimed to evaluate the prevalence of Mycoplasma pneumoniae in primary and tertiary care hospitals and its macrolide resistance rate. METHODS: Nasopharyngeal swabs were collected from 195 pediatric patients in primary and tertiary care hospitals from October to November 2010. The AccuPower MP real-time PCR kit (Bioneer, Korea) was used for the detection of M. pneumoniae. Direct amplicon sequencing was performed to detect point mutations conferring resistance to macrolides in the 23S rRNA gene. RESULTS: Among the 195 specimens, 17 (8.7%) were M. pneumoniae positive, and 3 of the strains (17.6%) obtained from these 17 specimens displayed the A2063G mutation in 23S rRNA. Three macrolide-resistant M. pneumoniae isolates were isolated from patients hospitalized at the primary care hospital. The positive rates of M. pneumoniae for the primary and tertiary care hospitals were 12.1% (15/124) and 2.8% (2/71), respectively (P=0.033). CONCLUSIONS: The positive rate of M. pneumoniae in the primary care hospital was higher than that in the tertiary care hospital. Simultaneous detection of M. pneumoniae and macrolide-resistant mutation genes in the 23S rRNA by real-time PCR is needed for rapid diagnosis and therapy of M. pneumoniae infections.

Two cases of Mycoplasma pneumoniae pneumonia with A2063G mutation in the 23S rRNA gene in siblings.

We describe 2 cases of pneumonia caused by the same macrolide-resistant Mycoplasma pneumoniae in siblings. M. pneumoniae was identified using real-time PCR. Direct sequence analysis of the 23S rRNA gene revealed a point mutation in V domain (A2063G) of the 23S rRNA gene.

Evaluation of the MicroScan MICroSTREP plus antimicrobial panel for testing ß-hemolytic streptococci and viridans group streptococci.

BACKGROUND: In order to determine the clinical usefulness of the MicroScan (Siemens Healthcare Diagnostics, USA) MICroSTREP plus antimicrobial panel (MICroSTREP) for testing antimicrobial susceptibility of ß-hemolytic streptococci (BHS) and viridans group streptococci (VGS), we compared the accuracy of MICroSTREP with that of the CLSI reference method. METHODS: Seventy-five BHS and 59 VGS isolates were tested for antimicrobial susceptibility to ampicillin, penicillin, cefotaxime, meropenem, erythromycin, clindamycin, levofloxacin, and vancomycin by using MICroSTREP and the CLSI agar dilution method. RESULTS: The overall essential agreement with regard to minimum inhibitory concentrations (MICs) (within ±1 double dilution) between MICroSTREP and the CLSI reference method was 98.2%, and categorical agreement (CA) was 96.9%. For the BHS isolates, the CA for erythromycin was 96.0%, whereas that for cefotaxime, meropenem, levofloxacin, and vancomycin (for ampicillin, penicillin, and clindamycin; 98.7%) was 100%. For the VGS isolates, the CA for penicillin was 84.7% and that for erythromycin, clindamycin, and vancomycin (for meropenem, 86.5%; for ampicillin, 88.1%; and for cefotaxime and levofloxacin, 96.6%) was 100%. All categorical errors of penicillin and ampicillin in the VGS isolates were minor. CONCLUSIONS: The accuracy of MICroSTREP is comparable to that of the CLSI reference method, suggesting that this panel can be effective for testing antimicrobial susceptibility of BHS and VGS.

Actinomyces graevenitzii bacteremia in a patient with alcoholic liver cirrhosis.

We report the first case of Actinomyces graevenitzii septicemia in a patient with alcoholic liver cirrhosis. It was identified as A. graevenitzii by morphologic and 16S rRNA sequencing. Even though A. graevenitzii is rarely associated with human infections, it should be considered as a potential causative agent of bacteremia.

Rhodococcus erythropolis septicaemia in a patient with acute lymphocytic leukaemia.

Rhodococcus erythropolis rarely causes infection in humans. We report the second case of R. erythropolis septicaemia in a 7-year-old child. However, to our knowledge it is the first case in a patient with acute lymphocytic leukaemia who had been undergoing chemotherapy. The identification was performed using 16S rRNA gene sequencing. Even though R. erythropolis is rarely associated with human infections, it should be considered as a potential causative agent of bacteraemia, rather than overlooked as a contaminant.

Antimicrobial susceptibility patterns and macrolide resistance genes of beta-hemolytic viridans group streptococci in a tertiary Korean hospital.

The aim of this study was to investigate antimicrobial susceptibilities and macrolide resistance mechanisms of beta-hemolytic viridans group streptococci (VGS) in a tertiary Korean hospital. Minimum inhibitory concentrations (MICs) of seven antimicrobials were determined for 103 beta-hemolytic VGS isolated from various specimens. The macrolide resistance mechanisms of erythromycin-resistant isolates were studied by the double disk test and polymerase chain reaction (PCR). The overall resistance rates of beta-hemolytic VGS were found to be 47.5% to tetracycline, 3.9% to chloramphenicol, 9.7% to erythromycin, and 6.8% to clindamycin, whereas all isolates were susceptible to penicillin G, ceftriaxone, and vancomycin. Among ten erythromycin-resistant isolates, six isolates expressed a constitutive MLS(B) (cMLS(B)) phenotype, and each of the two isolates expressed the M phenotype, and the inducible MLS(B) (iMLS(B)) phenotype. The resistance rates to erythromycin and clindamycin of beta-hemolytic VGS seemed to be lower than those of non-beta-hemolytic VGS in our hospital, although cMLSB phenotype carrying erm(B) was dominant in beta-hemolytic VGS.

Macrolide resistance trends in beta-hemolytic streptococci in a tertiary Korean hospital.

PURPOSE: Erythromycin-resistant beta-hemolytic streptococci (BHS) has recently emerged and quickly spread between and within countries throughout the world. In this study, we evaluate the antimicrobial susceptibility patterns and erythromycin resistance mechanisms of BHS during 2003-2004. MATERIALS AND METHODS: The MICs of seven antimicrobials were determined for 204 clinical isolates of BHS from 2003 to 2004. Resistance mechanisms of erythromycin-resistant BHS were studied by the double disk test as well as by polymerase chain reaction (PCR). RESULTS: Compared with our previous study, resistance among Streptococcus pyogenes isolates to a variety of drugs decreased strikingly: from 25.7% to 4.8% in erythromycin; 15.8% to 0% in clindamycin; and 47.1% to 19.0% in tetracycline. The prevalent phenotypes and genotypes of macrolide-lincosamide-streptograminB (MLSB) resistance in Streptococcus pyogenes isolates have been changed from the constitutive MLSB phenotype carrying erm(B) to the M phenotype with mef(A) gene. In contrast with Streptococcus pyogenes, resistance rates to erythromycin (36.7%), clindamycin (43.1%), and tetracycline (95.4%) in Streptococcus agalactiae isolates did not show decreasing trends. Among the Streptococcus dysgalactiae subsp. equisimilis isolates (Lancefield group C, G), resistance rates to erythromycin, clindamycin, tetracycline and chloramphenicol were observed to be 9.4%, 3.1%, 68.8%, and 9.4%, respectively. CONCLUSION: Continual monitoring of antimicrobial resistance among large-colony-forming BHS is needed to provide the medical community with current data regarding the resistance mechanisms that are most common to their local or regional environments.

A Case of Clostridium perfringens Septicemia with Fatal Hemolytic Complication.

Massive intravascular hemolysis secondary to Clostridium perfringens septicemia is rare but often fatal. We report a case of a fatal clostridial hemolytic complication in a 71-year-old woman with probable refractory anemia. The patient was admitted to the emergency room due to a comatose mental state and a high fever. Laboratory analysis showed massive hemolysis. She died from severe anemia two hours after admission. The next day, blood cultures grew gram positive cocci and boxcarshaped gram positive rods, which were identified as coagulase-negative staphylococci and C. perfringens, respectively.

Correlation of serotypes and genotypes of macrolide-resistant Streptococcus agalactiae.

Despite the necessity for studies of group B streptococci (GBS), due to the increase in serious adult infections, the emergence of new serotypes, and the increased resistance to macrolide antibiotics, such studies have been limited in Korea. The primary purpose of the present study was to determine the frequency trends of GBS serotypes, including serotypes VI, VII, and VIII. The final objective was to elucidate the relationship between the genotypes and serotypes of macrolide-resistant GBS isolates from a Korean population. Among 446 isolates of Streptococcus agalactiae, isolated between January 1990 and December 2002 in Korea, the frequency of serotypes were III (36.5%), Ib (22.0%), V (21.1%), Ia (9.6%), VI (4.3%), II (1.8%), VIII (1.3%), IV (1.1%), and VII (0.9%). The resistance rates to erythromycin, by serotype, were 85% (V), 23% (III), 21% (VI), 3% (Ib), and 2% (Ia). Of 135 erythromycin- resistant S. agalactiae, ermB was detected in 105 isolates, mefA in 20 isolates, and ermTR in seven isolates; most type V isolates harbored the ermB gene, Ib type isolates had an equal distribution of resistance genes, type III isolates accounted for 70% of all isolates carrying mefA genes, and one fourth of type VI isolates had mefA genes.

Serotypes and genotypes of erythromycin-resistant group B streptococci in Korea.

Among 78 erythromycin-resistant group B streptococcus (GBS) isolates from Korea, ermB was detected in 58 (74.4%), mefA was detected in 14 (17.9%), and ermTR was detected in 6 (7.7%). The most prevalent serotypes of erythromycin-resistant GBS were V (detected in 34 isolates [43.6%]) and III (detected in 33 isolates [42.3%]). All serotype V erythromycin-resistant GBS harbored the ermB gene.