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Mammography screening supported by deep learning-based artificial intelligence (AI) solutions can potentially reduce workload without compromising breast cancer detection accuracy, but the site of deployment in the workflow might be crucial. This retrospective study compared three simulated AI-integrated screening scenarios with standard double reading with arbitration in a sample of 249 402 mammograms from a representative screening population. A commercial AI system replaced the first reader (scenario 1: integrated AI first ), the second reader (scenario 2: integrated AI second ), or both readers for triaging of low- and high-risk cases (scenario 3: integrated AI triage ). AI threshold values were chosen based partly on previous validation and setting the screen-read volume reduction at approximately 50% across scenarios. Detection accuracy measures were calculated. Compared with standard double reading, integrated AI first showed no evidence of a difference in accuracy metrics except for a higher arbitration rate (+0.99%, P < .001). Integrated AI second had lower sensitivity (-1.58%, P < .001), negative predictive value (NPV) (-0.01%, P < .001), and recall rate (-0.06%, P = .04) but a higher positive predictive value (PPV) (+0.03%, P < .001) and arbitration rate (+1.22%, P < .001). Integrated AI triage achieved higher sensitivity (+1.33%, P < .001), PPV (+0.36%, P = .03), and NPV (+0.01%, P < .001) but lower arbitration rate (-0.88%, P < .001). Replacing one or both readers with AI seems feasible; however, the site of application in the workflow can have clinically relevant effects on accuracy and workload. Keywords: Mammography, Breast, Neoplasms-Primary, Screening, Epidemiology, Diagnosis, Convolutional Neural Network (CNN) Supplemental material is available for this article. Published under a CC BY 4.0 license.

This systematic review examines educational strategies in clinician-performed abdominal point-of-care ultrasound (POCUS), a critical skill with increasing relevance in medical care. Analyzing 28 studies, we highlight the strategies as well as advantages and disadvantages of various theoretical and practical components, including, for example, e-learning and simulation in training programs. The findings emphasize the necessity of blending various educational methods to enhance effectiveness and adaptability in training environments. Ultimately, robust training frameworks are essential to maximize diagnostic accuracy and improve patient outcomes in abdominal POCUS., (© 2024 The Author(s). Journal of Clinical Ultrasound published by Wiley Periodicals LLC.)

Aims: A multidisciplinary group of experts and patients developed the Model for ASsessing the value of Artificial Intelligence (MAS-AI) to ensure an evidence-based and patient-centered approach to introducing artificial intelligence technologies in healthcare. In this article, we share our experiences with meaningfully involving a patient in co-creating a research project concerning complex and technically advanced topics., Methods: The co-creation was evaluated by means of initial reflections from the research team before the project started, in a continuous logbook, and through semi-structured interviews with patients and two researchers before and after the active co-creation phase of the project., Results: There were initial doubts about the feasibility of including patients in this type of project. Co-creation ensured relevance to patients, a holistic research approach and the debate of ethical considerations. Due to one patient dropping out, it is important to foresee and support the experienced challenges of time and energy spent by the patient in future projects. Having a multidisciplinary team helped the collaboration. A mutual reflective evaluation provided insights into the process which we would otherwise have missed., Conclusions: We found it possible to create complex and data-intense research projects with patients. Including patients benefitted the project and gave researchers new perspectives on their own research. Mutual reflection throughout the project is key to maximise learning for all parties involved., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objectives: This systematic review and meta-analysis aimed to assess the stroke detection performance of artificial intelligence (AI) in magnetic resonance imaging (MRI), and additionally to identify reporting insufficiencies., Methods: PRISMA guidelines were followed. MEDLINE, Embase, Cochrane Central, and IEEE Xplore were searched for studies utilising MRI and AI for stroke detection. The protocol was prospectively registered with PROSPERO (CRD42021289748). Sensitivity, specificity, accuracy, and area under the receiver operating characteristic (ROC) curve were the primary outcomes. Only studies using MRI in adults were included. The intervention was AI for stroke detection with ischaemic and haemorrhagic stroke in separate categories. Any manual labelling was used as a comparator. A modified QUADAS-2 tool was used for bias assessment. The minimum information about clinical artificial intelligence modelling (MI-CLAIM) checklist was used to assess reporting insufficiencies. Meta-analyses were performed for sensitivity, specificity, and hierarchical summary ROC (HSROC) on low risk of bias studies., Results: Thirty-three studies were eligible for inclusion. Fifteen studies had a low risk of bias. Low-risk studies were better for reporting MI-CLAIM items. Only one study examined a CE-approved AI algorithm. Forest plots revealed detection sensitivity and specificity of 93% and 93% with identical performance in the HSROC analysis and positive and negative likelihood ratios of 12.6 and 0.079., Conclusion: Current AI technology can detect ischaemic stroke in MRI. There is a need for further validation of haemorrhagic detection. The clinical usability of AI stroke detection in MRI is yet to be investigated., Critical Relevance Statement: This first meta-analysis concludes that AI, utilising diffusion-weighted MRI sequences, can accurately aid the detection of ischaemic brain lesions and its clinical utility is ready to be uncovered in clinical trials., Key Points: There is a growing interest in AI solutions for detection aid. The performance is unknown for MRI stroke assessment. AI detection sensitivity and specificity were 93% and 93% for ischaemic lesions. There is limited evidence for the detection of patients with haemorrhagic lesions. AI can accurately detect patients with ischaemic stroke in MRI., (© 2024. The Author(s).)

Objectives: To validate an AI system for standalone breast cancer detection on an entire screening population in comparison to first-reading breast radiologists., Materials and Methods: All mammography screenings performed between August 4, 2014, and August 15, 2018, in the Region of Southern Denmark with follow-up within 24 months were eligible. Screenings were assessed as normal or abnormal by breast radiologists through double reading with arbitration. For an AI decision of normal or abnormal, two AI-score cut-off points were applied by matching at mean sensitivity (AI sens ) and specificity (AI spec ) of first readers. Accuracy measures were sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and recall rate (RR)., Results: The sample included 249,402 screenings (149,495 women) and 2033 breast cancers (72.6% screen-detected cancers, 27.4% interval cancers). AI sens had lower specificity (97.5% vs 97.7%; p < 0.0001) and PPV (17.5% vs 18.7%; p = 0.01) and a higher RR (3.0% vs 2.8%; p < 0.0001) than first readers. AI spec was comparable to first readers in terms of all accuracy measures. Both AI sens and AI spec detected significantly fewer screen-detected cancers (1166 (AI sens ), 1156 (AI spec ) vs 1252; p < 0.0001) but found more interval cancers compared to first readers (126 (AI sens ), 117 (AI spec ) vs 39; p < 0.0001) with varying types of cancers detected across multiple subgroups., Conclusion: Standalone AI can detect breast cancer at an accuracy level equivalent to the standard of first readers when the AI threshold point was matched at first reader specificity. However, AI and first readers detected a different composition of cancers., Clinical Relevance Statement: Replacing first readers with AI with an appropriate cut-off score could be feasible. AI-detected cancers not detected by radiologists suggest a potential increase in the number of cancers detected if AI is implemented to support double reading within screening, although the clinicopathological characteristics of detected cancers would not change significantly., Key Points: • Standalone AI cancer detection was compared to first readers in a double-read mammography screening population. • Standalone AI matched at first reader specificity showed no statistically significant difference in overall accuracy but detected different cancers. • With an appropriate threshold, AI-integrated screening can increase the number of detected cancers with similar clinicopathological characteristics., (© 2023. The Author(s).)

Technology has greatly influenced and radically changed human life, from communication to creativity and from productivity to entertainment. The authors, starting from considerations concerning the implementation of new technologies with a strong impact on people's everyday lives, take up Collingridge's dilemma and relate it to the application of AI in healthcare. Collingridge's dilemma is an ethical and epistemological problem concerning the relationship between technology and society which involves two approaches. The proactive approach and socio-technological experimentation taken into account in the dilemma are discussed, the former taking health technology assessment (HTA) processes as a reference and the latter the AI studies conducted so far. As a possible prevention of the critical issues raised, the use of the medico-legal method is proposed, which classically lies between the prevention of possible adverse events and the reconstruction of how these occurred.The authors believe that this methodology, adopted as a European guideline in the medico-legal field for the assessment of medical liability, can be adapted to AI applied to the healthcare scenario and used for the assessment of liability issues. The topic deserves further investigation and will certainly be taken into consideration as a possible key to future scenarios., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Artificial intelligence (AI) systems are proposed as a replacement of the first reader in double reading within mammography screening. We aimed to assess cancer detection accuracy of an AI system in a Danish screening population., Methods: We retrieved a consecutive screening cohort from the Region of Southern Denmark including all participating women between Aug 4, 2014, and August 15, 2018. Screening mammograms were processed by a commercial AI system and detection accuracy was evaluated in two scenarios, Standalone AI and AI-integrated screening replacing first reader, with first reader and double reading with arbitration (combined reading) as comparators, respectively. Two AI-score cut-off points were applied by matching at mean first reader sensitivity (AI sens ) and specificity (AI spec ). Reference standard was histopathology-proven breast cancer or cancer-free follow-up within 24 months. Coprimary endpoints were sensitivity and specificity, and secondary endpoints were positive predictive value (PPV), negative predictive value (NPV), recall rate, and arbitration rate. Accuracy estimates were calculated using McNemar's test or exact binomial test., Results: Out of 272,008 screening mammograms from 158,732 women, 257,671 (94.7%) with adequate image data were included in the final analyses. Sensitivity and specificity were 63.7% (95% CI 61.6%-65.8%) and 97.8% (97.7-97.8%) for first reader, and 73.9% (72.0-75.8%) and 97.9% (97.9-98.0%) for combined reading, respectively. Standalone AI sens showed a lower specificity (-1.3%) and PPV (-6.1%), and a higher recall rate (+ 1.3%) compared to first reader (p < 0.0001 for all), while Standalone AI spec had a lower sensitivity (-5.1%; p < 0.0001), PPV (-1.3%; p = 0.01) and NPV (-0.04%; p = 0.0002). Compared to combined reading, Integrated AI sens achieved higher sensitivity (+ 2.3%; p = 0.0004), but lower specificity (-0.6%) and PPV (-3.9%) as well as higher recall rate (+ 0.6%) and arbitration rate (+ 2.2%; p < 0.0001 for all). Integrated AI spec showed no significant difference in any outcome measures apart from a slightly higher arbitration rate (p < 0.0001). Subgroup analyses showed higher detection of interval cancers by Standalone AI and Integrated AI at both thresholds (p < 0.0001 for all) with a varying composition of detected cancers across multiple subgroups of tumour characteristics., Conclusions: Replacing first reader in double reading with an AI could be feasible but choosing an appropriate AI threshold is crucial to maintaining cancer detection accuracy and workload., (© 2023. The Author(s).)

Objectives: The objective of this study was to investigate renal function after robot-assisted partial nephrectomy (RAPN) and percutaneous cryoablation (PCA) in clinical stage T1 (cT1) renal cell carcinoma (RCC) and evaluate the relationship between baseline renal function and renal functional outcome., Material and Methods: Patients with cT1 RCC treated with RAPN or PCA were prospectively enrolled between June 2019 and January 2021. Renal function was evaluated using estimated glomerular filtration rate, Tc-99m diethylenetriamine-pentaacetate plasma clearance, Tc-99m mercaptoacetyltriglycine renography, and renal volume at baseline and 6 months after treatment., Results: Fifty-six patients were included (18 RAPN, 38 PCA). PCA patients had a significantly higher age (68.5 years; P = 0.019) and Charlson comorbidity index (3.0; P = 0.007). Tumor characteristics did not differ significantly between RAPN and PCA. Total renal volume decreased significantly after PCA (-18.2 cm 3 ; P = 0.001). Baseline chronic disease stage IIIb-IV leads to a greater reduction in renal volume (-31.8 cm 3 ; P = 0.003) but not other renal function measures. Renal function declined significantly after either treatment without significant differences between RAPN and PCA., Conclusion: This study found a small, similar decrease in renal function 6 months after RAPN or PCA, despite significant differences in baseline patient characteristics. Reduced renal function at baseline did not lead to a worse renal functional outcome., Competing Interests: There are no conflicts of interest., (© 2023 Published by Scientific Scholar on behalf of Journal of Clinical Imaging Science.)

Capsule retention is a rare complication to capsule endoscopy. It is often asymptomatic and resolves itself spontaneously. In some cases, endoscopy or surgery is necessary to remove the capsule. Cases of capsule retention in the colon are not reported very often and precautions in subsequent investigations must be considered. We present a case of a 74-year-old woman who underwent colon capsule endoscopy (CCE) due to a positive fecal immunochemical test. The CCE was incomplete, and the patient was referred to conventional colonoscopy, which was complicated by perforation of the large bowel during the procedure. This lead to a CT scan showing the capsule proximal to a stenotic colon segment which was subsequently surgically removed. In patients who report lack of capsule excretion and stenosis is not verified, colonoscopy can be carried out, but with caution., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s), 2023.)

This study was aimed at comparing the learning efficacy of a traditional instructor-led lesson with that of a completely virtual, self-directed lesson in immersive virtual reality (IVR) in teaching basic point-of-care ultrasound (PoCUS) skills. We conducted a blinded, non-inferiority, parallel-group, randomized controlled trial in which final-year medical students were randomized to an instructor-led (n = 53) or IVR (n = 51) lesson. Participants' learning efficacy was evaluated by blinded assessors, who rated each participant's performance using the Objective Structured Assessment of Ultrasound Skills (OSAUS) assessment tool.The mean total scores for participants were 11.0 points (95% confidence interval: 9.8-12.2) for the instructor-led lesson and 10.3 points (95% confidence interval: 9.0-11.5) for the IVR lesson. No significant differences were observed between the groups with respect to total score (p = 0.36) or subgroup objectives of the OSAUS score (p = 0.34 for familiarity, p = 0.45 for image optimization, p = 0.96 for systematic approach and p = 0.07 for interpretation). Maintenance costs for both courses were estimated at 400 euros each. Startup costs for the instructor-led course were estimated 16 times higher than those for the IVR course. The learning efficacy of an instructor-led lesson on basic US did not differ significantly from that of a self-directed lesson in IVR, as assessed using the OSAUS. The results suggest that IVR could be an equivalent alternative to instructor-led lessons in future basic US courses, but further research is warranted to clarify the role of IVR in PoCUS courses., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: To assess and compare complications and readmissions after partial nephrectomy and percutaneous cryoablation of cT1 renal cell carcinoma (RCC)., Materials and Methods: Patients treated for cT1 RCC between 2019 and 2021 were prospectively and consecutively enrolled. Complications recorded within 30 and 90 days were graded according to the Clavien-Dindo classification, and percutaneous cryoablation was graded according to the Society of Interventional Radiology classification of adverse events. Major complications were defined as complications with a grade of ≥3 based on the Clavien-Dindo classification. Readmission within 30 days was recorded., Results: The cohort included 86 partial nephrectomies and 104 cryoablations. The complication rate within 90 days was 23% after partial nephrectomy and cryoablation (P = .98), with major complication rates of 3% after partial nephrectomy and 10% after cryoablation (P = .15). The readmission rates were 14% and 11% after partial nephrectomy and cryoablation, respectively (P = .48). Double-J stents were associated with overall complications (odds ratio [OR], 9.88; 95% confidence interval [CI], 2.18-44.68; P = .003) and readmissions (OR, 5.39; 95% CI, 1.37-21.06; P = .015) after cryoablation. A high versus low radius-endophytic-nearness-anterior-location score (OR, 5.86; 95% CI, 1.08-31.81; P = .040) and endophytic location (OR, 7.70; 95% CI, 1.72-34.50; P = .008) were associated with a higher complication rate after cryoablation. The Charlson Comorbidity Index (CCI) was associated with major complications after partial nephrectomy (OR, 2.12; 95% CI, 1.05-4.30; P = .036)., Conclusions: Partial nephrectomy and cryoablation are comparable regarding complications within 90 days after treatment. Tumor complexity and double-J stents were associated with complications after cryoablation, and a high CCI was associated with complications after partial nephrectomy., (Copyright © 2022 SIR. Published by Elsevier Inc. All rights reserved.)

Background: Artificial intelligence (AI) is seen as one of the major disrupting forces in the future healthcare system. However, the assessment of the value of these new technologies is still unclear, and no agreed international health technology assessment-based guideline exists. This study provides an overview of the available literature in the value assessment of AI in the field of medical imaging., Methods: We performed a systematic scoping review of published studies between January 2016 and September 2020 using 10 databases (Medline, Scopus, ProQuest, Google Scholar, and six related databases of grey literature). Information about the context (country, clinical area, and type of study) and mentioned domains with specific outcomes and items were extracted. An existing domain classification, from a European assessment framework, was used as a point of departure, and extracted data were grouped into domains and content analysis of data was performed covering predetermined themes., Results: Seventy-nine studies were included out of 5890 identified articles. An additional seven studies were identified by searching reference lists, and the analysis was performed on 86 included studies. Eleven domains were identified: (1) health problem and current use of technology, (2) technology aspects, (3) safety assessment, (4) clinical effectiveness, (5) economics, (6) ethical analysis, (7) organisational aspects, (8) patients and social aspects, (9) legal aspects, (10) development of AI algorithm, performance metrics and validation, and (11) other aspects. The frequency of mentioning a domain varied from 20 to 78% within the included papers. Only 15/86 studies were actual assessments of AI technologies. The majority of data were statements from reviews or papers voicing future needs or challenges of AI research, i.e. not actual outcomes of evaluations., Conclusions: This review regarding value assessment of AI in medical imaging yielded 86 studies including 11 identified domains. The domain classification based on European assessment framework proved useful and current analysis added one new domain. Included studies had a broad range of essential domains about addressing AI technologies highlighting the importance of domains related to legal and ethical aspects., (© 2022. The Author(s).)

Hip dysplasia (HD) is a frequent cause of hip pain in skeletally mature patients and may lead to osteoarthritis (OA). An accurate and early diagnosis may postpone, reduce or even prevent the onset of OA and ultimately hip arthroplasty at a young age. The overall aim of this study was to assess the reliability of an algorithm, designed to read pelvic anterior-posterior (AP) radiographs and to estimate the agreement between the algorithm and human readers for measuring (i) lateral center edge angle of Wiberg (LCEA) and (ii) Acetabular index angle (AIA). The algorithm was based on deep-learning models developed using a modified U-net architecture and ResNet 34. The newly developed algorithm was found to be highly reliable when identifying the anatomical landmarks used for measuring LCEA and AIA in pelvic radiographs, thus offering highly consistent measurement outputs. The study showed that manual identification of the same landmarks made by five specialist readers were subject to variance and the level of agreement between the algorithm and human readers was consequently poor with mean measured differences from 0.37 to 9.56° for right LCEA measurements. The algorithm displayed the highest agreement with the senior orthopedic surgeon. With further development, the algorithm may be a good alternative to humans when screening for HD.

Background: Partial nephrectomy (PN) is the gold standard for the treatment of stage cT1 renal cell carcinoma (RCC). However, the increasing incidence of RCC in the elderly population calls for alternative minimally invasive treatments to reduce the negative effects on patients' health-related quality of life (HRQoL) and subsequent healthy life expectancy., Objective: To assess and compare short-term HRQoL and self-reported health status after PN and percutaneous cryoablation (PCA) of patients treated for RCC stage cT1., Design Setting and Participants: Patients who underwent PN or PCA between 2019 and 2021 for RCC stage cT1 at two university hospitals in Denmark were assessed. The exclusion criteria included insufficient understanding of the Danish language, dementia, metastatic RCC, conversion to nephrectomy, and salvage procedures., Intervention: PN and PCA., Outcome Measurements and Statistical Analysis: The European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire was distributed before treatment, and 14 and 90 d postoperatively. A linear mixed-effect model was used to analyze the changes from baseline to follow-up between PN and PCA treatment., Results and Limitations: The cohort included 165 patients (PN: 79; PCA: 86). The completion rate was 96-98%. Patients receiving PCA were significantly older (median 69.1 vs 62.1 yr) and had lower scores on physical ( p  < 0.001) and role functioning ( p  = 0.009) than PN. A statistically significant change from baseline to 14 d was found for several HRQoL scales, which favored PCA over PN. However, the observed change was no longer significant at 90-d follow-up. Limitations include sample size and confounding by indication., Conclusions: This study found a significant difference between baseline and 14-d follow-up in several HRQoL and symptoms scales, favoring PCA over PN. However, no significant differences were observed in any HRQoL scales between PN and PCA of RCC stage cT1 from baseline to 90-d follow-up., Patient Summary: Surgical removal and percutaneous cryoablation (freezing) of small tumors in the kidney had a similar impact on quality of life after 90 d., (© 2022 The Author(s).)

Objectives: Artificial intelligence (AI) is seen as a major disrupting force in the future healthcare system. However, the assessment of the value of AI technologies is still unclear. Therefore, a multidisciplinary group of experts and patients developed a Model for ASsessing the value of AI (MAS-AI) in medical imaging. Medical imaging is chosen due to the maturity of AI in this area, ensuring a robust evidence-based model., Methods: MAS-AI was developed in three phases. First, a literature review of existing guides, evaluations, and assessments of the value of AI in the field of medical imaging. Next, we interviewed leading researchers in AI in Denmark. The third phase consisted of two workshops where decision makers, patient organizations, and researchers discussed crucial topics for evaluating AI. The multidisciplinary team revised the model between workshops according to comments., Results: The MAS-AI guideline consists of two steps covering nine domains and five process factors supporting the assessment. Step 1 contains a description of patients, how the AI model was developed, and initial ethical and legal considerations. In step 2, a multidisciplinary assessment of outcomes of the AI application is done for the five remaining domains: safety, clinical aspects, economics, organizational aspects, and patient aspects., Conclusions: We have developed an health technology assessment-based framework to support the introduction of AI technologies into healthcare in medical imaging. It is essential to ensure informed and valid decisions regarding the adoption of AI with a structured process and tool. MAS-AI can help support decision making and provide greater transparency for all parties.

In this case report, a 40-year-old woman presented with altered mentation, central facial palsy and hemiparesis. Acute CT scan showed several hypodense, rounded areas in both hemispheres. Urine toxicology tested positive for amphetamine. Subsequent cerebral MRI had hyperintense T2-weighted fluid-attenuated inverse recovery (FLAIR) lesions in both hemispheres, indicating demyelinating disease. A biopsy was made from one of the lesions. The final diagnosis was toxic encephalopathy.

Background: Despite the fact that nephron-sparing treatment is considered preferable from a surgical perspective patients' quality of life (QoL) following different types of nephron-sparing treatments remains unclear., Purpose: To investigate the quality of life and complications after nephron-sparing treatment of renal cell carcinomas of stage T1., Materials and Methods: A systematic search of six databases was carried out. We included studies that reported the quality of life and complications in patients aged 18 years or older following nephron-sparing treatment of renal cell carcinoma stage T1. The quality assessment was performed using the Critical Appraisal Skills Programme (CASP) checklist for cohort studies and the CASP Randomized Controlled Trial Checklist. Data were analyzed using a narrative approach., Results: Eight studies were included, six of which investigated QoL after partial nephrectomy and two after ablation therapies. Seven studies reported complications. Three studies reported higher QoL scores after partial nephrectomy compared to radical nephrectomy. Two studies showed that QoL increased or returned to baseline levels up to 12 months following partial nephrectomy. One study reported a gradual increase in QoL after radiofrequency ablation, and one study reported that all patients recovered to baseline QoL following cryoablation. Across studies, we found a complication rate up to 20% after partial nephrectomy and up to 12.5% after ablation therapy., Conclusions: The results of this systematic review suggest that nephron-sparing treatment appears to be superior or comparable to other treatment alternatives with regard to QoL outcomes. Additionally, based on the studies included in this review, partial nephrectomy appears to have a higher complication rate compared with ablation therapies., Systematic Review Registration: PROSPERO CRD42020155594., (© 2021. The Author(s).)

Purpose: This study examined the impact of pronation and supination on the reliability of the radiographically measured values of dorsal tilt, radial inclination (RI), and ulnar variance (UV) in cadaveric forearms with artificially created distal radius fractures., Methods: We prepared 21 human cadaveric forearms (11 right and 10 left) for radiostereometric analysis (RSA) by insertion of tantalum markers. Distal radius fractures were created midway between the marker segments. Radiographs and RSA images were taken at different degrees of supination and pronation. The precise degree of forearm rotation was calculated using RSA software. Two observers (H.B.T. and T.T.) independently measured tilt, RI, and UV on all radiographs in a blinded and randomized fashion. Univariate linear regression analyses were used to determine the relationship between forearm rotation and the measured radiographic values., Results: The radiographically measured value of tilt was significantly impacted by forearm rotation. Supinating or pronating the forearm by 10° decreased and increased, respectively, the radiographic value of dorsal tilt by approximately 3°., Conclusions: This study showed that the positioning of the fractured forearm during the radiographic procedure significantly impacted subsequent radiographic measurements of tilt. Dorsal tilt measurements increased (ie, fracture displacement measured more dorsal) with pronation and decreased (ie, fracture displacement measured more toward neutral, with less dorsal tilt) with supination of the forearm. However, measurements of RI ( p  = 0.12 and  p  = 0.55 for observer 1 and 2) and UV ( p  = 0.34 and  p  = 0.17, observer 1 and 2) were not significantly impacted by rotation., Clinical Relevance: Treatment of a distal radius fracture is, at least to some extent, based on radiographic quantification of fracture deformity. Therefore, unreliable measurements may adversely influence clinical decision making., (© 2021 The Authors.)

Background: Although dorsal/palmar tilt, radial inclination (RI), and ulnar variance (UV) are measurements commonly performed in wrist radiographs, the impact of forearm rotation on those measurements during the radiographic procedure is uncertain. Our aim was to determine the impact of supination and pronation on the reliability of measurements of tilt, RI, and UV., Methods: Tantalum markers were inserted into the distal radius of 21 unfractured cadaver forearms. The forearms were radiographed in different degrees of supination and pronation. The exact degree of rotation was calculated with radiostereometric analyses. Tilt, RI, and UV were measured by two independent readers in a random and anonymised fashion. Association between forearm rotation and radiographic measurements was examined using linear regression., Results: Forearm rotation significantly impacted the radiographically measured tilt. One degree of supination and pronation respectively increased and decreased palmar tilt with 0.68° and 0.44°, observers 1 and 2, respectively. As opposed to observer 1, observer 2 found that RI was significantly impacted by rotation with a slope of 0.08. Ulnar variance was not significantly impacted by rotation with linear regression slopes of 0.01° (95% confidence interval [CI] - 0.02-0.05, p = 0.490) and 0.02° (95% CI - 0.02-0.07; p = 0.288), observer 1 and observer 2, respectively., Conclusion: In unfractured forearms, the radiographically measured tilt was significantly affected by rotation. Palmar tilt increased with supination and decreased with pronation. Rotation significantly affected radial inclination, although of a magnitude that is probably not clinically relevant. No significant impact on UV was found.

Background: Few long-time follow-up studies describe all complications, treatment outcome of complications, and mortality in relation to endovascular aneurysm repair (EVAR). The purpose of this study was to evaluate the incidence and treatment outcome including mortality of radiological visible complications related to the EVAR procedure at a single center with up to 10 years' surveillance., Materials and Methods: Patients treated with EVAR from March 2006 to March 2016 at a Danish university hospital, 421 in total, were included. Patient and aneurysm characteristics, follow-up, and secondary intervention data were collected from a national database and medical records. Follow-up computed tomography angiography and plain abdominal X-ray reports were reviewed for complications. Scans and X-rays with suspected complications were evaluated by an interventional radiologist., Results: A total of 172 complications in 147 patients, mainly in the beginning of the follow-up period, were found; 35% had a least one complication. The main part of complications (62%) was type II endoleaks, followed by stent graft stenosis (11%), type I endoleaks (9%), and stent graft occlusion (7%). A total of 66 (38%) complications, observed in 55 patients, were treated with reintervention, of which 77% were treated with endovascular procedures and 23% with surgical treatment, that is, 13% of all studied patients had a complication that required a reintervention. The remaining 2 of the 3 complications were treated conservatively. We found no increased all-cause mortality in connection with having a complication including those requiring reintervention., Conclusion: We presented a 10-year single-center study of EVAR. Many patients treated with EVAR had a radiological visible complication, mainly in the beginning of the follow-up period. Only a smaller fraction required reintervention and having a reintervention-requiring complication was not connected to increased mortality.

Background: It is unclear whether intensive blood pressure management is well-tolerated and affects risk uniformly across the body mass index (BMI) spectrum., Methods: The randomized, controlled Systolic Blood Pressure Intervention Trial (SPRINT) included 9361 individuals ≥50 years of age at high cardiovascular risk, without diabetes mellitus, with systolic blood pressure between 130 and 180 mmHg. Participants were randomized to intensive vs standard antihypertensive treatment and evaluated for the primary composite efficacy endpoint of acute coronary syndromes, stroke, heart failure, or cardiovascular death. The primary safety endpoint was serious adverse events. We used restricted cubic splines to determine the relationship between BMI, response to intensive blood pressure lowering, and clinical outcomes in SPRINT., Results: Body mass index could be calculated for 9284 (99.2%) individuals. Mean BMI was similar between the 2 treatment groups (intensive group 29.9±5.8 kg/m 2 vs standard group 29.8± 5.7 kg/m 2 ; P = 0.39). Median follow-up was 3.3 years (range 0-4.8 years). Body mass index had a significant, J-shaped association with risk of all-cause mortality, stroke, and serious adverse events (P < .05 for all), but these were no longer significant after accounting for key clinical factors (P > .05 for all). Intensive blood pressure lowering reduced the primary efficacy endpoint and increased the primary safety endpoint compared with standard targets, consistently across the BMI spectrum (P interaction > .05)., Conclusion: The overall efficacy and safety of intensive blood pressure lowering did not appear to be modified by baseline BMI among high-risk older adults., (Copyright © 2019 Elsevier Inc. All rights reserved.)

This study compared the cost-effectiveness of telemonitoring with standard monitoring for patients with diabetic foot ulcers. The economic evaluation was nested within a pragmatic randomised controlled trial. A total of 374 patients were randomised to either telemonitoring or standard monitoring. Telemonitoring consisted of two tele-consultations in the patient's own home and one consultation at the outpatient clinic; standard monitoring consisted of three outpatient clinic consultations. Total healthcare costs were estimated over a 6-month period at individual patient level, from a healthcare sector perspective. The bootstrap method was used to calculate the incremental cost-effectiveness ratio, and one-way sensitivity analyses were performed. Telemonitoring costs were found to be €2039 less per patient compared to standard monitoring; however, this difference was not statistically significant. Amputation rate was similar in the two groups. In conclusion, a telemonitoring service in this form had similar costs and effects as standard monitoring.

Aims/hypothesis: The aim of this study was to describe the trends in rates of amputation among individuals with and without diabetes., Methods: We studied amputation rates in the County of Funen (approximately 0.5 million residents) during the period 1996-2011. Amputations were identified from the hospital administrative system, diabetes status by linkage with the Danish National Diabetes Register, and mortality and population data by extraction from Statistics Denmark. Amputation rates were analysed using proportional hazard models. We analysed the incidence of the first amputation at each level as well as the incidence of further amputations, subdivided by level of amputation., Results: During the period 1996-2011, a total of 2,832 amputations were performed, of which 1,285 were among patients with diabetes and 1,547 among individuals without diabetes. Relative to persons without diabetes, patients with diabetes had an HR for below-ankle amputations (BAAs) of 14.7 for men and 7.5 for women, and for from-ankle-to-knee amputations (BKAs) of 7.6 and 8.4 for men and women, respectively. For above-knee amputations (AKAs) the numbers were 4.0 for men and 3.7 for women. We found an annual reduction in BAA rates among patients with diabetes of 9.8%, and the annual reduction in BKA for patients with diabetes was 15.1%., Conclusions/interpretation: The amputation rate in patients with diabetes is still several-fold higher than in persons without diabetes, but the improvements in diabetes care in recent years have resulted in a steady decline in amputation rates among patients with diabetes from this Danish cohort.

Executive summary Purpose This document aims to provide wound care clinicians with a rapid and structured overview of the key issues related to use of eHealth applications (telemedicine and telehealth) within wound care. This includes: An overview of terminology and available literature Guidance on the methodology for evaluation of eHealth solutions An introduction to and discussion of the potential benefits of eHealth technologies in wound care, and the possible barriers to their implementation Recommendations for ensuring a good implementation process and supporting involvement of wound care professionals in safeguarding that eHealth solutions meet the needs of the patients. Methodology The document sections lean on the structure and focus areas of the Model for ASsessment of Telemedicine (MAST) which defines crucial items to evaluate an eHealth application. The content of the document is developed on the basis of a literature review, identifying available documentation for use of eHealth solutions in wound care. Furthermore, it draws on various key documents recently published on the general development, evaluation and implementation of eHealth solutions. These include valuable up-to-date information relevant for any group of clinicians wishing to follow and influence the way eHealth solutions are integrated into clinical practice. Findings and conclusions The literature review revealed that the amount and level of evidence for use of eHealth applications in wound care is still limited. Some MAST domains are not examined in any of the available studies. Thus, more research is required to identify the potential benefits and harms to patients, and the possible challenges related to implementation of eHealth solutions in wound care. Potential barriers and facilitators for the implementation of eHealth applications into wound care practice are identified in the document, and these may all either enhance or impede the process. However, the available research does demonstrate patient satisfaction, improved access to health services for all client cohorts, and increased job satisfaction for clinicians. The document recommends that wound management clinicians, considering the use of eHealth applications in their clinical practice, consult widely and conduct regular evaluation of the outcomes to ensure efficient implementation of these services. To support this approach, steps to ensure a good implementation process within a given organisation have been proposed. These are synthesised into a three circle model.