Kei Yamamoto

Dengue fever (DF) is endemic in tropical and subtropical regions. Nonetheless, sporadic cases of autochthonous dengue have also been reported in non-endemic countries. Although preparedness for dengue outbreaks in these settings is essential, evidence describing clinical presentation of patients and fluid management remains limited. This single-center retrospective descriptive study was conducted to examine the clinical management of DF in Japan, with a particular focus on fluid management. This study included patients diagnosed with DF from January 1, 2013, to December 31, 2020. The inclusion criterion was a body temperature of ≥ 37.0 °C. Epidemiological, demographic, and clinically relevant data were obtained through data extraction and chart review. Overall, 162 patients (115 inpatients and 47 outpatients) were included. The median age was 32 years (interquartile range [IQR], 24-42 years), and 59.3% were male. Six patients (3.7%) reported a history of DF. The median time from symptom onset to initial presentation was 3 days (IQR, 1-5 days), and 38 patients (23.5%) presented with warning signs (WS) at initial presentation. Among hospitalized patients, intravenous fluids were administered to 92.2%, with most receiving extracellular fluids. The median fluid volumes administered within 24 h, 72 h, and 7 days after diagnosis were 2569, 6769, and 10,011 mL, respectively, in severe disease; 1734, 5103, and 7855 mL in non-severe disease with WS; and 1500, 3650, and 5500 mL in non-severe disease without WS, respectively. These volumes were lower than those recommended by the World Health Organization and the Centers for Disease Control and Prevention. Nevertheless, no deaths or intensive care unit admissions occurred, and all inpatients were discharged without major sequelae. This study described the clinical management of DF in Japan. During hospitalization, effective fluid administration may be achievable with volumes lower than conventional recommendations. Further studies are warranted to determine optimal fluid administration strategies and volumes for adult patients with DF in high-resource, non-endemic settings, including Japan.

Gram staining provides rapid microbiological information that may assist in empirical antimicrobial selection; however, the results are often interpreted by microbiological specialists who are not always available. Therefore, we developed a computer-aided diagnosis system using artificial intelligence trained on microscopic images of Gram-stained urine, captured with an iPhone, using the Bartholomew and Mittwer method. The system interprets Gram-stained urine samples and classifies bacterial morphology (Class 1: 7 predefined morphology categories) and 17 predefined species-level categories (Class 2). In this retrospective observational study, five imaging devices and two staining methods (Bartholomew and Mittwer, Favor) were compared. Urine specimens were collected from two hospitals between 1 April and 31 December 2022. Validation images were generated using five devices (four smartphones and one microscopic camera). We used a micrometer with microscopy with all smartphones; some iPhone images were taken without a micrometer. Favor staining was only imaged using an iPhone without the micrometer. Image data sets were generated from 433 clinical and 17 spiked samples. The overall accuracy was 0.804 for Class 1 and 0.640 for Class 2. Images taken by the microscopic camera had the highest accuracy and kappa coefficient, whereas the AQUOS smartphone had the lowest accuracy and kappa coefficient. The accuracy of images created without a micrometer was 0.885 for Class 1 and 0.666 for Class 2. The Bartholomew and Mittwer method had better accuracy and a better kappa coefficient. Overall, accuracy depended on the staining method used in the training data, not on the imaging device. IMPORTANCE: Gram staining provides rapid information on both the site of infection and likely pathogens, guiding empirical antimicrobial selection. However, interpretation requires infectious disease expertise, which is not always available. We developed an artificial intelligence-based diagnostic support system trained on iPhone images of Gram-stained urine using the Bartholomew and Mittwer method to classify bacterial morphology (Class 1) and inferred species (Class 2). To provide essential baseline data on factors influencing accuracy and reliability, we compared Gram-stained urine images from two hospitals obtained with five imaging devices and two staining methods. Microscopic camera images showed the highest accuracy, whereas an AQUOS smartphone showed the lowest. Images without a micrometer performed better, and the Bartholomew and Mittwer method outperformed the Favor method. Accuracy increased when confidence levels were higher. Our findings suggest that using the same staining method as the training data and avoiding micrometer noise are critical, while device differences are less influential.

Background Giardiasis and cryptosporidiosis are often misdiagnosed by stool ova and parasite test (classical O&P). Multiplex PCR and rapid antigen immunochromatography (rapid-IC) could offer high diagnostic accuracy; however, their cost and restricted coverage, especially for parasites, limit routine use. This study evaluated the efficacy of adapted fluorescent antibody microscopy using ARK Checker® C/G – DyLight® 488 (FAM-TEST). The reagent is a liquid-form conjugated antibody preparation that directly reacts with Giardia cysts and Cryptosporidium oocysts. Methods Stool samples were incubated with DyLight-488–labeled antibodies as indicated in our original protocol and examined by fluorescence microscopy. Diagnostic accuracy of FAM-TEST was assessed with multiplex PCR results as reference and compared with that of rapid-IC. Samples with discordant results among these methods were additionally tested by conventional PCR with Sanger sequencing to verify infection status. Results A total of 694 stool samples were submitted for microbiological examination. FAM-TEST identified Giardia and/or Cryptosporidium in 35 samples. In addition, 49 FAM-TEST- negative samples from a randomly selected month were included as negative controls. For Giardia , all FAM-TEST results were identical to those of rapid-IC, including three false negatives [88.0% sensitivity, 100% specificity, 100% positive predictive value (PPV), and 95.2% negative predictive value (NPV)]. For Cryptosporidium , FAM-TEST showed 93.8% sensitivity, 100% specificity, 100% PPV, and 98.6% NPV, which were comparable with those of rapid-IC. Notably, nested PCR for Giardia produced negative results for three samples considered to yield FAM-TEST false negatives, raising another possibility of multiplex PCR false positives or extremely low pathogen burden, whereas conventional PCR for Cryptosporidium showed results fully consistent with those of multiplex PCR. Conclusion Concurrent use of FAM-TEST with classical O&P offers a cost-effective, practical diagnostic approach for enteric parasites, which especially strengthens diagnostic accuracy for Giardiasis/Cryptosporidiosis.

Background: Nested polymerase chain reaction (PCR) targeting the small subunit ribosomal ribonucleic acid (SSU rRNA, 18S rRNA) region is widely used to differentiate Plasmodium species. We identified a variant of the Plasmodium malariae SSU rRNA gene that suggests nested PCR may fail to detect P. malariae strains with unknown mutations. Case presentation: A 56-year-old Japanese man developed a fever 2 months after returning from a 2-month stay in Sierra Leone. Quartan malaria was suspected based on blood smear findings, and nested PCR confirmed P. malariae infection. However, the secondary PCR band obtained using P. malariae-specific primers was fainter than the primary PCR band amplified with universal primers—a reversal of the typical pattern. Sequence analysis revealed a four-base deletion in the SSU rRNA gene within the primer-binding site of the species-specific reverse primer used in the secondary PCR, suggesting that mutations in this region may partially impair amplification and hinder species identification. Cytochrome b gene sequencing confirmed 100% identity with P. malariae. Conclusions: These findings underscore the need for continued molecular surveillance and sequence-based validation to ensure accurate diagnosis of Plasmodium infections, particularly in regions where genetic variants and zoonotic strains are emerging.

Introduction. Timely and accurate diagnosis of bacterial infections enables early administration of appropriate antimicrobial treatment and improved outcomes. Hypothesis/Gap Statement. The accuracy of computer-aided diagnosis (CAD) for identifying organisms on urine Gram stains has not been compared with that of microbiology specialists (MS). Aim. To compare the interpretation of urine Gram-stain results by MS and a CAD app designed using artificial intelligence. Methodology. Urine specimens from patients with urinary tract infections were used and collected at two tertiary hospitals between 1 April and 31 December 2022. Using non-inferiority analysis to assess whether CAD was non-inferior to expert interpretation, CAD-predicted microscopic findings of the Gram-stained slide generated from iPhone camera images from two hospitals were compared with those from ten MS. A total of 153 images were taken from each hospital, and CAD interpreted a total of 306. The primary endpoint was the prediction accuracy based on the morphology of the Gram-stained bacteria. Results. The accuracy (95% confidence interval) of MS and CAD predictions was 83.0% (81.6%–84.3%) and 87.9% (83.7%–91.3%), respectively, with a difference of –4.93% (–8.43% to –0.62%) indicating non-inferiority of CAD. Conclusion. CAD was non-inferior to MS predictions for identifying Gram-stained pathogens; therefore, CAD was suggested to have the potential for guiding empirical antibiotic selection in patients with urinary tract infections.

We evaluated the viral load of varicella-zoster virus (VZV) in ambient air, vesicle, and pharyngeal swabs in VZV-infected patients. Of 46 cases, 6 had VZV detected in indoor air samples from patient rooms. Results suggest an association between viral load in the pharyngeal swab and indoor air.