Explore the vast range of titles available.

Over recent decades, wearable inertial sensors have become popular means to quantify physical activity and mobility. However, research assessing measurement accuracy and precision is required, especially before using device-based measures as outcomes in trials. The GT9X Link is a recent activity monitor available from ActiGraph, recognized as a “gold standard” and previously used as a criterion measure to assess the validity of various consumer-based activity monitors. However, the validity of the ActiGraph GT9X Link is not fully elucidated. A systematic review was undertaken to synthesize the current evidence for the criterion validity of the ActiGraph GT9X Link in measuring steps and energy expenditure. This review followed the PRISMA guidelines and eight studies were included with a combined sample size of 558 participants. We found that (1) the ActiGraph GT9X Link generally underestimates steps; (2) the validity and accuracy of the device in measuring steps seem to be influenced by gait speed, device placement, filtering process, and monitoring conditions; and (3) there is a lack of evidence regarding the accuracy of step counting in free-living conditions and regarding energy expenditure estimation. Given the limited number of included studies and their heterogeneity, the present review emphasizes the need for further validation studies of the ActiGraph GT9X Link in various populations and in both controlled and free-living settings.

Background The aim of this original study was to determine the number of parathyroid glands that can be saved and reimplanted thanks to autofluorescence during thyroid surgery. Preservation of parathyroid function remains challenging during thyroid surgery. The parathyroid glands must be identified and immediately autotransplanted in the case of devascularization. Near-infrared autofluorescence of parathyroid glands has recently been proposed to help surgeons during the dissection. Methods A total of 116 thyroid lobectomies were performed on 70 consecutive adult patients. Each lobectomy specimen was scanned in vitro with an autofluorescence imaging device. Every spot of autofluorescence was examined by the surgeon and subsequently the pathologist. The pathologist also performed a complete study of the rest of the lobe. We compared the results of the macroscopic and microscopic diagnoses. Results We detected 24 fluorescent spots on the specimens: 13 were considered to be parathyroid tissue by the surgeon and 11, non-parathyroid tissue. The pathologist confirmed the surgical diagnosis but also discovered 15 additional parathyroid glands that were hidden. Conclusions Autofluorescence imaging of the thyroidectomy specimen with surgical inspection is safe, quick, noninvasive and can help detect the accidental removal of parathyroid glands. About 60% of these glands can be spared and autotransplanted during the surgery.

Background In medicine, the patient-centered approach is based on interpersonal skills, including communication, structuring the medical interview, and empathy, which have an impact on health professionals’ interpersonal relationships and the quality of care. Training courses on this issue are therefore being developed in universities. We hypothesized that specific training courses in the physician–patient relationship could improve interpersonal skills among medical students during simulated consultations and the immediate satisfaction of standardized patients. Methods This cross-sectional study enrolled fourth-year medical students who participated in a simulated medical consultation session with standardized patients. The evaluation of interpersonal skills was carried out using the Four Habits Coding Scheme, producing a synthetic score out of 115 points used as the primary endpoint. Some students benefited from the training courses offered by the university or by other organizations, mainly based on communication, active listening, or patient-centered approach. A comparison was made with students from the same graduating class who had not received any training. Results The analysis of the primary endpoint showed a difference of 5 points between the group of students who had attended at least one training course and those who did not ( p  = 0.001). This difference was even more marked when the students had completed several training courses, up to 14 points higher with three training courses ( p  = 0.001), each with positive results in different areas of the care relationship. Conclusions Physician–patient relationship training currently provided in initial education appears to be effective in improving interpersonal skills. A repetition of this training is necessary to increase its impact.

Automated blood vessel segmentation is critical for biomedical image analysis, as vessel morphology changes are associated with numerous pathologies. Still, precise segmentation is difficult due to the complexity of vascular structures, anatomical variations across patients, the scarcity of annotated public datasets, and the quality of images. Our goal is to provide a foundation on the topic and identify a robust baseline model for application to vascular segmentation using a new imaging modality, Hierarchical Phase-Contrast Tomography (HiP-CT). We begin with an extensive review of current machine-learning approaches for vascular segmentation across various organs. Our work introduces a meticulously curated training dataset, verified by double annotators, consisting of vascular data from three kidneys imaged using HiP-CT as part of the Human Organ Atlas Project. HiP-CT pioneered at the European Synchrotron Radiation Facility in 2020, revolutionizes 3D organ imaging by offering a resolution of around 20 μm/voxel and enabling highly detailed localised zooms up to 1–2 μm/voxel without physical sectioning. We leverage the nnU-Net framework to evaluate model performance on this high-resolution dataset, using both known and novel samples, and implementing metrics tailored for vascular structures. Our comprehensive review and empirical analysis on HiP-CT data sets a new standard for evaluating machine learning models in high-resolution organ imaging. Our three experiments yielded Dice similarity coefficient (DSC) scores of 0.9523, 0.9410, and 0.8585, respectively. Nevertheless, DSC primarily assesses voxel-to-voxel concordance, overlooking several crucial characteristics of the vessels and should not be the sole metric for deciding the performance of vascular segmentation. Our results show that while segmentations yielded reasonably high scores-such as centerline DSC ranging from 0.82 to 0.88, certain errors persisted. Specifically, large vessels that collapsed due to the lack of hydrostatic pressure (HiP-CT is an ex vivo technique) were segmented poorly. Moreover, decreased connectivity in finer vessels and higher segmentation errors at vessel boundaries were observed. Such errors, particularly in significant vessels, obstruct the understanding of the structures by interrupting vascular tree connectivity. Our study establishes the benchmark across various evaluation metrics, for vascular segmentation of HiP-CT imaging data, an imaging technology that has the potential to substantively shift our understanding of human vascular networks.

The ageing population in Europe, particularly in rural areas, creates new health challenges, including patients with multiple comorbidities and difficult access to care. Advanced Practice Nurses (APNs) could play a key role in improving access and care for frail older patients in France's rural areas, although how to achieve this remains unclear. This study aimed to identify the healthcare needs of frail patients living at home in rural areas and those of their healthcare providers to assess the potential role of APNs in addressing these needs. This interpretive descriptive qualitative study was conducted from June to September 2023, using focus groups (FGs). Three FGs with 20 participants, including healthcare providers and frail older people, were conducted in two French rural areas. Data were analysed using thematic analyse to identify key needs and potential APN contributions. The healthcare needs identified were: improving access to care, maintaining human interactions, and providing coordinated, preventive care. Participants emphasised the importance of interprofessional collaboration and the central role of APNs, whose expanded skillset enables them to coordinate care with caregivers and professionals. However, challenges remain, including a lack of understanding of the APN's skills and concerns about their integration within the care team. APNs could support access to person-centred, coordinated home care in rural areas by acting as key references for patients, caregivers, and teams. However, limited awareness of their role and concerns from other professionals remain barriers to their integration.

Biomedical systems span multiple spatial scales, encompassing tiny functional units to entire organs. Interpreting these systems through image segmentation requires the effective propagation and integration of information across different scales. However, most existing segmentation methods are optimised for single-scale imaging modalities, limiting their ability to capture and analyse small functional units throughout complete human organs. To facilitate multiscale biomedical image segmentation, we utilised Hierarchical Phase-Contrast Tomography (HiP-CT), an advanced imaging modality that can generate 3D multiscale datasets from high-resolution volumes of interest (VOIs) at ca. 1 μ m /voxel to whole-organ scans at ca. 20 μ m /voxel. Building on these hierarchical multiscale datasets, we developed a deep learning-based segmentation pipeline that is initially trained on manually annotated high-resolution HiP-CT data and then extended to lower-resolution whole-organ scans using pseudo-labels generated from high-resolution predictions and multiscale image registration. As a case study, we focused on glomeruli in human kidneys, benchmarking four 3D deep learning models for biomedical image segmentation on a manually annotated high-resolution dataset extracted from VOIs, at 2.58 to ca. 5 μ m /voxel, of four human kidneys. Among them, nnUNet demonstrated the best performance, achieving an average test Dice score of 0.906, and was subsequently used as the baseline model for multiscale segmentation in the pipeline. Applying this pipeline to two low-resolution full-organ data at ca. 25 μ m /voxel, the model identified 1,019,890 and 231,179 glomeruli in a 62-year-old donor without kidney diseases and a 94-year-old hypertensive donor, enabling comprehensive morphological analyses, including cortical spatial statistics and glomerular distributions, which aligned well with previous anatomical studies. Our results highlight the effectiveness of the proposed pipeline for segmenting small functional units in multiscale bioimaging datasets and suggest its broader applicability to other organ systems.

The Four Habits Coding Scheme (4-HCS) is a standardized instrument designed to assess physicians' communication skills from an external rater's perspective, based on video-recorded consultations. To perform the cross-cultural adaptation of the 4-HCS into French and to assess its psychometric properties. The 4-HCS was cross-culturally adapted by conducting forward and backward translations with independent translators, following international guidelines. Four raters rated 200 video-recorded medical student consultations with standardized patients, using the French version of the 4-HCS. We examined the internal consistency, factor structure, construct validity, and reliability of the 4-HCS. The mean overall 4-HCS score was 76.44 (standard deviation, 12.34), with no floor or ceiling effects across subscales. The median rating duration of rating was 8 min (range, 4-19). Cronbach's alpha was 0.94 for the overall 4-HCS, ranging from 0.72 to 0.88 across subscales. In confirmatory factor analysis, goodness-of-fit statistics did not corroborate the hypothesized 4-habit structure. Exploratory factor analysis resulted in two dimensions, with the merging of three conceptually related habits into a single dimension and substantial cross-loading for 15 out of 23 items. Median average absolute-agreement intra-class correlation coefficient estimates were 0.74 (range, 0.68-0.84) and 0.85 (range, 0.76-0.91) for inter- and intra-rater reliability of habit subscales, respectively. The French version of the 4-HCS demonstrates satisfactory internal consistency but requires the use of two independent raters to achieve acceptable reliability. The underlying factor structure of the original US version and cross-cultural adaptations of the 4-HCS deserve further investigation.

Our goal was to investigate the effects of head-thorax elevation (HUP) during chest compressions (CC) on lung ventilation. A prospective study was performed on seven human cadavers. Chest was automatically compressed-decompressed in flat position and during progressive HUP from 18 to 35°. Lung ventilation was measured with electrical impedance tomography. In each cadaver, 5 sequences were randomly performed: one without CC at positive end-expiratory pressure (PEEP) 0cmH 2 O, 3 s with CC at PEEP0, 5 or 10cmH 2 O and 1 with CC and an impedance threshold device at PEEP0cmH 2 O. The minimal-to-maximal change in impedance (VT EIT in arbitrary unit a.u.) and the minimal impedance in every breathing cycle (EELI) the) were compared between flat, 18°, and 35° in each sequence by a mixed-effects model. Values are expressed as median (1st–3rd quartiles). With CC, between flat, 18° and 35° VT EIT decreased at each level of PEEP. It was 12416a.u. (10,689; 14,442), 11,239 (7667; 13,292), and 6457 (4631; 9516), respectively, at PEEP0. The same was true with the impedance threshold device. EELI/VT EIT significantly decreased from − 0.30 (− 0.40; − 0.15) before to − 1.13 (− 1.70; − 0.61) after the CC (P = 0.009). With HUP lung ventilation decreased with CC as compared to flat position. CC are associated with decreased in EELI.

Ageing, multimorbidity, and workforce shortages increasingly limit access to primary healthcare, especially in rural and underserved areas. To document impact of nurse practitioners (NPs) in primary care on patients with chronic diseases. Searches were conducted in Medline, EMBASE, CINAHL, and CENTRAL (March 1978-October 2023). This systematic review followed MECIR and PRISMA guidelines (PRISMA 2020 checklist: EQUATOR Network) with SWiM used as a PRISMA extension due to the lack of meta-analysis. The focus was on NPs' roles in chronic disease management and primary care in underserved or remote areas, excluding mental health, cancer, and dental care. Among 3,684 citations, 25 studies were selected, including 10 RCT. NPs may improve access to primary care and chronic disease management, particularly in underserved areas. Although not all studies directly compared NPs to traditional models, they were most often assessed against General Practitioners (GPs) alone. Seven studies also evaluated collaborative NP-GP models versus GP-only care. Patient satisfaction was generally higher with NPs, possibly due to longer consultations and greater patient education. Clinical and biological outcomes were often comparable between NPs and GPs, with the best results in collaborative models, which were also associated with higher costs. NPs may enhance access to care, particularly for vulnerable populations. Higher patient satisfaction may be linked to longer consultations and patient education. While clinical outcomes were comparable to those of GPs, collaborative models yielded the best results, though potentially at a higher cost.

Background Terrible triad of the elbow (TTE) is a complex dislocation associating radial head (RH) and coronoid process (CP) fractures. There is at present no reproducible anatomic model for TTE, and pathophysiology is unclear. The main aim of the present study was to create and validate an anatomic model of TTE. Secondary objectives were to assess breaking forces and relative forearm rotation with respect to the humerus before dislocation. Methods An experimental comparative study was conducted on 5 fresh human specimens aged 87.4 ± 8.6 years, testing 10 upper limbs. After dissection conserving the medial and lateral ligaments, interosseous membrane and joint capsule, elbows were reproducibly positioned in maximal pronation and 15° flexion, for axial compression on a rapid (100 mm/min) or slow (10 mm/min) protocol, applied by randomization between the two elbows of a given cadaver, measuring breaking forces and relative forearm rotation with respect to the humerus before dislocation. Results The rapid protocol reproduced 4 posterolateral and 1 divergent anteroposterior TTE, and the slow protocol 5 posterolateral TTE. Mean breaking forces were 3,126 ± 1,066 N for the lateral collateral ligament (LCL), 3,026 ± 1,308 N for the RH and 2,613 ± 1,120 N for the CP. Comparing mean breaking forces for all injured structures in a given elbow on the rapid protocol found a p-value of 0.033. Comparison of difference in breaking forces in the three structures (LCL, RH and CP) between the slow and rapid protocols found a mean difference of -4%. Mean relative forearm rotation with respect to the humerus before dislocation was 1.6 ± 1.2° in external rotation. Conclusions We create and validate an anatomic model of TTE by exerting axial compression on an elbow in 15° flexion and maximal pronation at speeds of 100 and 10 mm/min.