Comparison between procalcitonin and C-reactive protein in predicting bacteremias and confounding factors: a case-control study.

BACKGROUND: The detection of infectious bacteria in blood culture samples is important for diagnosis and treatment, but this requires 1-2 days at least, and is not adequate as a rapid test. Therefore, we have investigated the diagnostic ability and the optimal cutoff value of procalcitonin (PCT) and C-reactive protein (CRP) for predicting the bacteremias using receiver operating characteristic (ROC) curves and relative cumulative frequency distribution (RCD) curves. METHODS: A case-control study was performed in inpatients (852 subjects: 426 positive cultures and 426 negative cultures) from January 1 to December 31, 2014. We retrospectively investigated their blood culture and blood chemistry findings recorded in this period using electronic medical records. RESULTS: Area under the ROC curve of PCT and CRP were 0.79 and 0.66, respectively. The optimal cutoff values were 0.5 µg/L with a sensitivity of 70% and specificity of 70% for PCT and 50.0 mg/L with a sensitivity of 63% and specificity of 65% for CRP. When the optimal cutoff value was treated as a reference, the odds ratio (OR) was 71.11 and the hazard ratio (HR) was 6.27 for PCT >2.0 µg/L, and the risk of blood culture positivity was markedly elevated. PCT levels were significantly higher in the population with Gram-negative rod (GNR) infections than in the population with Gram-positive coccal (GPC) infections. CONCLUSIONS: The elevation of CRP and PCT were significantly associated with bacteremias. PCT was superior to CRP as a diagnostic indicator for predicting bacteremias, for discriminating bacterial from nonbacterial infections, and for determining bacterial species.

Using novel micropore technology combined with artificial intelligence to differentiate Staphylococcus aureus and Staphylococcus epidermidis.

Methods for identifying bacterial pathogens are broadly categorised into conventional culture-based microbiology, nucleic acid-based tests, and mass spectrometry. The conventional method requires several days to isolate and identify bacteria. Nucleic acid-based tests and mass spectrometry are relatively rapid and reliable, but they require trained technicians. Moreover, mass spectrometry requires expensive equipment. The development of a novel, inexpensive, and simple technique for identifying bacterial pathogens is needed. Through combining micropore technology and assembly machine learning, we developed a novel classifier whose receiver operating characteristic (ROC) curve showed an area under the ROC curve of 0.94, which rapidly differentiated between Staphylococcus aureus and Staphylococcus epidermidis in this proof-of-concept study. Morphologically similar bacteria belonging to an identical genus can be distinguished using our method, which requires no specific training, and may facilitate the diagnosis and treatment of patients with bacterial infections in remote areas and in developing countries.

Mechanisms Underlying Pneumococcal Transmission and Factors Influencing Host-Pneumococcus Interaction: A Review.

Streptococcus pneumoniae (also called pneumococcus) is not only a commensal that frequently colonizes the human upper respiratory tract but also a pathogen that causes pneumonia, sepsis, and meningitis. The mechanism of pneumococcal infection has been extensively studied, but the process of transmission has not been fully elucidated because of the lack of tractable animal models. Novel animal models of transmission have enabled further progress in investigating pneumococcal transmission mechanisms including the processes such as pneumococcal shedding, survival in the external environment, and adherence to the nasopharynx of a new host. Herein, we present a review on these animal models, recent research findings about pneumococcal transmission, and factors influencing the host-pneumococcus interaction.

Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.

High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is currently the most-widely used technology to diagnose the presence of SARS-CoV-2. However, RT-PCR requires the extraction of viral RNA from clinical specimens to obtain high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity by using nanopores together with artificial intelligence, a relatively simple procedure that does not require RNA extraction. Our final platform, which we call the artificially intelligent nanopore, consists of machine learning software on a server, a portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. We show that artificially intelligent nanopores are successful in accurately identifying four types of coronaviruses similar in size, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2. Detection of SARS-CoV-2 in saliva specimen is achieved with a sensitivity of 90% and specificity of 96% with a 5-minute measurement.

Comparative usefulness of inflammatory markers to indicate bacterial infection-analyzed according to blood culture results and related clinical factors.

To assess relationships of inflammatory markers and 2 related clinical factors with blood culture results, we retrospectively investigated inpatients' blood culture and blood chemistry findings that were recorded from January to December 2014 using electronic medical records and analyzed the data of 852 subjects (426 culture-positive and 426 culture-negative). Results suggested that the risk of positive blood culture statistically increased as inflammatory marker levels and the number of related factors increased. Concerning the effectiveness of inflammatory markers, when the outcome definition was also changed for C-reactive protein (CRP), the odds ratio had a similar value, whereas when the outcome definition of blood culture positivity was used for procalcitonin (PCT), the greatest effectiveness of that was detected. Therefore, the current results suggest that PCT is more useful than CRP as an auxiliary indication of bacterial infection.