Costs associated with informal health care pathway for patients with suspected Lyme borreliosis.

OBJECTIVES: To compare the direct and indirect medical costs for patients with suspected Lyme borreliosis according to whether or not they had used an informal care pathway. PATIENTS AND METHODS: We retraced the care pathways of participating patients by a prospective questionnaire survey and a retrospective analysis of care records. Direct and indirect costs were estimated using a micro-costing method from different perspectives. We compared the costs of patients who had consulted a "Lyme Doctor" (informal care pathway) with those who had only used the formal care pathway. Non-parametric tests were appraised the significance of the differences between the two groups of patients. RESULTS: Out of 103 eligible patients, 49 (including 12 having used an informal health care pathway) agreed to be investigated. Five expenditure items entirely borne by patients were significantly higher for patients following an informal care pathway: productivity loss (3041 ± 6580 vs 194 ± 1177 euros, p = 0.01), alternative therapies (3484 ± 7308 vs 369 ± 956 euros), biological tests sent abroad (571 ± 1415 vs 17 ± 92 euros, p < 0.01), self-medication (918 ± 1998 vs 133 ± 689, p = 0.02) and transport (3 094 ± 3456 vs 1 123 ± 1903p = 0.01). CONCLUSIONS: From the patient's standpoint, the informal care pathway involving consultation with a Lyme Doctor is far more expensive than the formal care pathway. More specifically, the patient has to bear the costs of alternative treatments and repeated, non-recommended examinations.

Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images.

BACKGROUND AND OBJECTIVE: Lyme disease which is one of the most common infectious vector-borne diseases manifests itself in most cases with erythema migrans (EM) skin lesions. Recent studies show that convolutional neural networks (CNNs) perform well to identify skin lesions from images. Lightweight CNN based pre-scanner applications for resource-constrained mobile devices can help users with early diagnosis of Lyme disease and prevent the transition to a severe late form thanks to appropriate antibiotic therapy. Also, resource-intensive CNN based robust computer applications can assist non-expert practitioners with an accurate diagnosis. The main objective of this study is to extensively analyze the effectiveness of CNNs for diagnosing Lyme disease from images and to find out the best CNN architectures considering resource constraints. METHODS: First, we created an EM dataset with the help of expert dermatologists from Clermont-Ferrand University Hospital Center of France. Second, we benchmarked this dataset for twenty-three CNN architectures customized from VGG, ResNet, DenseNet, MobileNet, Xception, NASNet, and EfficientNet architectures in terms of predictive performance, computational complexity, and statistical significance. Third, to improve the performance of the CNNs, we used custom transfer learning from ImageNet pre-trained models as well as pre-trained the CNNs with the skin lesion dataset HAM10000. Fourth, for model explainability, we utilized Gradient-weighted Class Activation Mapping to visualize the regions of input that are significant to the CNNs for making predictions. Fifth, we provided guidelines for model selection based on predictive performance and computational complexity. RESULTS: Customized ResNet50 architecture gave the best classification accuracy of 84.42% ±1.36, AUC of 0.9189±0.0115, precision of 83.1%±2.49, sensitivity of 87.93%±1.47, and specificity of 80.65%±3.59. A lightweight model customized from EfficientNetB0 also performed well with an accuracy of 83.13%±1.2, AUC of 0.9094±0.0129, precision of 82.83%±1.75, sensitivity of 85.21% ±3.91, and specificity of 80.89%±2.95. All the trained models are publicly available at https://dappem.limos.fr/download.html, which can be used by others for transfer learning and building pre-scanners for Lyme disease. CONCLUSION: Our study confirmed the effectiveness of even some lightweight CNNs for building Lyme disease pre-scanner mobile applications to assist people with an initial self-assessment and referring them to expert dermatologist for further diagnosis.

Dual Inhibition of FLT3 and AXL by Gilteritinib Overcomes Hematopoietic Niche-Driven Resistance Mechanisms in FLT3-ITD Acute Myeloid Leukemia.

PURPOSE: AXL has been shown to play a pivotal role in the selective response of FLT3-ITD acute myeloid leukemia (AML) cells to FLT3 tyrosine kinase inhibitors (TKI), particularly within the bone marrow microenvironment. EXPERIMENTAL DESIGN: Herein, we compared the effect of dual FLT3/AXL-TKI gilteritinib with quizartinib through in vitro models mimicking hematopoietic niche conditions, ex vivo in primary AML blasts, and in vivo with dosing regimens allowing plasma concentration close to those used in clinical trials. RESULTS: We observed that gilteritinib maintained a stronger proapoptotic effect in hypoxia and coculture with bone marrow stromal cells compared with quizartinib, linked to a dose-dependent inhibition of AXL phosphorylation. In vivo, use of the MV4-11 cell line with hematopoietic engraftment demonstrated that gilteritinib was more effective than quizartinib at targeting leukemic cells in bone marrow. Finally, FLT3-ITD AML patient-derived xenografts revealed that this effect was particularly reproducible in FLT3-ITD AML with high allelic ratio in primary and secondary xenograft. Moreover, gilteritinib and quizartinib displayed close toxicity profile on normal murine hematopoiesis, particularly at steady state. CONCLUSIONS: Overall, these findings suggest that gilteritinib as a single agent, compared with quizartinib, is more likely to reach leukemic cells in their protective microenvironment, particularly AML clones highly dependent on FLT3-ITD signaling.

Delay in diagnosis of influenza virus in an elderly hospitalized patient: a fatal outcome.

Influenza is a well established cause of seasonal hospitalizations and deaths among older persons. However, influenza is frequently underdiagnosed by physicians, because its clinical presentations are often complex, particularly in elderly patients. We report the case of a 78-year-old woman admitted to the emergency department in January 2008 with fever, vomiting, and a history of asthenia and falls in the preceding three days. Diagnosis of influenza at admission was missed. Influenza was diagnosed by direct fluorescent antibody in a sputum specimen four days later, but the evolution was rapidly unfavorable with fatal respiratory distress syndrome. This case illustrates that, during the influenza season, influenza should be suspected in elderly patients admitted to hospital even if they do not present with classical symptoms. Immunofluorescence testing on sputum specimens can provide a rapid diagnosis and merits further evaluation.