Graefe's Archive for Clinical and Experimental Ophthalmology - Ferromagnetic foreign bodies (FFB) present during magnetic resonance imaging (MRI) explorations can lead to tissue injury due to... 相似文献
Immunologic Research - Hyper immunoglobulin M (HIGM) syndrome is a rare disorder of the immune system with impaired antibody functions. The clinical picture of the patients varies according to the... 相似文献
A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume–outcome relationship into minimum volume regulation (MVR) to increase the quality of care—yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accordingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure’s complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR’s intended benefit: concentrating treatment delivery to improve the quality of care.
Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus. 相似文献
Background: Breast cancer (BC) is the most common malignant tumor in women, and its morbidity and mortality are
increasing each year, due to the lack of specific clinical symptoms in the early stage of BC, and the lack of diagnostic
methods for early breast cancer. Therefore, identifying an effective diagnostic method for early BC has become urgent.
Materials and Methods: Breast lesions with a histological diagnosis that were examined by ultrasonic elastography
(UE) in our department from June 2020 to December 2021 were reviewed. qRT-PCR was performed to measure
the expression levels of miR-144-5p and miR-26b-5p in the plasma of patients with BC. The receiver operating characteristics (ROC) curve and area under the curve (AUC) were used to investigate the potential diagnostic value of miR-
144-5p, miR-26b-5p and the elastographic score in BC. Results: The ultrasonic elastography score(UES) was found to
be significantly upregulated in BC compared with that in benign breast lesions, and the AUC, sensitivity and specificity
were 0.809, 0.717 and 0.806 for distinguishing BC from benign breast lesions, respectively. miR-144-5p and miR-26b-
5p were found to be upregulated in the plasma of BC patients, and miR-144-5p+miR-26b-5p had 0.781 sensitivity and
0.780 specificity for the diagnosis of BC. Furthermore, we found that the diagnostic performance of miR-144-5p and
miR-26b-5p combined with UES for BC had 0.913 sensitivity and 0.890 specificity. Conclusions: The combination of
plasma miR-144-5p, miR-26b-5p and UES has a very high clinical application value for the early detection of BC. 相似文献