日本・京都府下の病院および長期療養施設における、vanAあるいはvanB陽性 Enterococcus gallinarumの地域的拡大

京都大学0048新制・課程博士博士(医学)甲第15748号医博第3510号新制||医||984(附属図書館)28309京都大学大学院医学研究科医学専攻(主査)教授 西渕 光昭, 教授 千葉 勉, 教授 木原 正博学位規則第4条第1項該当Doctor of Medical ScienceKyoto UniversityDA

Clinical characteristics of <it>Pneumocystis </it>pneumonia in non-HIV patients and prognostic factors including microbiological genotypes

Abstract Background The number of patients with non-HIV Pneumocystis pneumonia (PCP) is increasing with widespread immunosuppressive treatment. We investigated the clinical characteristics of non-HIV PCP and its association with microbiological genotypes. Methods Between January 2005 and March 2010, all patients in 2 university hospitals who had been diagnosed with PCP by PCR were enrolled in this study. Retrospective chart review of patients, microbiological genotypes, and association with 30-day mortality were examined. Results Of the 82 adult patients investigated, 50 patients (61%) had inflammatory diseases, 17 (21%) had solid malignancies, 12 (15%) had hematological malignancies, and 6 (7%) had received transplantations. All patients received immunosuppressive agents or antitumor chemotherapeutic drugs. Plasma (1→3) β-D-glucan levels were elevated in 80% of patients, and were significantly reduced after treatment in both survivors and non-survivors. However, β-D-glucan increased in 18% of survivors and was normal in only 33% after treatment. Concomitant invasive pulmonary aspergillosis was detected in 5 patients. Fifty-six respiratory samples were stored for genotyping. A dihydropteroate synthase mutation associated with trimethoprim-sulfamethoxazole resistance was found in only 1 of the 53 patients. The most prevalent genotype of mitochondrial large-subunit rRNA was genotype 1, followed by genotype 4. The most prevalent genotype of internal transcribed spacers of the nuclear rRNA operon was Eb, followed by Eg and Bi. Thirty-day mortality was 24%, in which logistic regression analysis revealed association with serum albumin and mechanical ventilation, but no association with genotypes. Conclusions In non-HIV PCP, poorer general and respiratory conditions at diagnosis were independent predictors of mortality. β-D-glucan may not be useful for monitoring the response to treatment, and genotypes were not associated with mortality.</p

The Body Fat Percentage Rather Than the BMI Is Associated with the CD4 Count among HIV Positive Japanese Individuals

Maintenance of the cluster of differentiation 4 (CD4) positive lymphocyte count (CD4 count) is important for human immunodeficiency virus (HIV) positive individuals. Although a higher body mass index (BMI) is shown to be associated with a higher CD4 count, BMI itself does not reflect body composition. Therefore, we examined the association of body weight, body composition and the CD4 count, and determined the optimal ranges of CD4 count associated factors in Japanese HIV positive individuals. This cross-sectional study included 338 male patients treated with antiretroviral therapy for &ge;12 months. Multiple logistic regression analysis was used to identify factors significantly associated with a CD4 count of &ge;500 cells (mm3)&minus;1. The cutoff values of factors for a CD4 &ge; 500 cells (mm3)&minus;1 and cardiovascular disease risk were obtained by receiver operating characteristic curves. Age, body fat percentage (BF%), nadir CD4 count, duration of antiretroviral therapy (ART), years since the HIV-positive diagnosis and cholesterol intake showed significant associations with the CD4 count. The cutoff value of BF% for a CD4 &ge; 500 cells (mm3)&minus;1 and lower cardiovascular disease risk were &ge;25.1% and &le;25.5%, respectively. The BF%, but not the BMI, was associated with CD4 count. For the management of HIV positive individuals, 25% appears to be the optimal BF% when considering the balance between CD4 count management and cardiovascular disease risk

Development and external validation of a deep learning-based computed tomography classification system for COVID-19

[BACKGROUND] We aimed to develop and externally validate a novel machine learning model that can classify CT image findings as positive or negative for SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR). [METHODS] We used 2, 928 images from a wide variety of case-control type data sources for the development and internal validation of the machine learning model. A total of 633 COVID-19 cases and 2, 295 non-COVID-19 cases were included in the study. We randomly divided cases into training and tuning sets at a ratio of 8:2. For external validation, we used 893 images from 740 consecutive patients at 11 acute care hospitals suspected of having COVID-19 at the time of diagnosis. The dataset included 343 COVID-19 patients. The reference standard was RT-PCR. [RESULTS] In external validation, the sensitivity and specificity of the model were 0.869 and 0.432, at the low-level cutoff, 0.724 and 0.721, at the high-level cutoff. Area under the receiver operating characteristic was 0.76. [CONCLUSIONS] Our machine learning model exhibited a high sensitivity in external validation datasets and may assist physicians to rule out COVID-19 diagnosis in a timely manner at emergency departments. Further studies are warranted to improve model specificity

The Kaplan–Meier curve showing the proportion of exposure-free patients from time of departure according to animal type.

Lines indicate dogs (solid black), cats (dotted red), monkeys (solid blue), and others (dotted green).</p

Countries where exposure occurred according to animal type.

Countries with the highest number of patients exposed to dogs, cats, and monkeys are shown in descending order.</p

Characteristics of animal exposure according to animal type (N = 322).

Characteristics of animal exposure according to animal type (N = 322).</p