Diagnostic Exams Research Articles

Body Habitus vs. Hepatic Steatosis: Understanding the Drivers of Non-Diagnostic Shear Wave Elastography

PurposeShear Wave Elastography (SWE) is frequently non-diagnostic in obese patients, a key cohort at risk for liver disease. Subcutaneous fat and hepatic steatosis are suspected drivers, but their relative contribution is unknown. We compare ultrasound-guided attenuation parameter (UGAP), a marker of steatosis, body mass index (BMI), and skin-to-liver capsule distance (SCD) to predict non-diagnostic SWE. Materials and MethodsThis IRB approved, single center retrospective study included adults with SWE and diagnostic UGAP exams between June and December 2023. Fasting patients were imaged in supine position with right arm abducted, via an intercostal window during neutral breath hold. The median of 10 measurements in the right lobe was analyzed for SWE and UGAP. SWE measurements were ≥ 2 cm from the capsule while UGAP depth was fixed at 4 cm from the probe. Exams were considered non-diagnostic for SWE (measured in m/s) if the Interquartile Range/Median Ratio (IQR/M) was > 15% or if diagnostic measurements could not be obtained. UGAP IQR/M > 30% or complete measurement failure was considered non-diagnostic. Univariate Receiver Operating Characteristic (ROC) curves compared UGAP (dB/cm/MHz), BMI (kg/m2), and SCD (mm) prediction of non-diagnostic SWE by the DeLong test. Results87 participants (48 male) with mean age of 54.7 ± 15.7 years were analyzed. UGAP [OR: 1.63 per 0.1 dB/cm/MHz, p=0.02, AUC=0.66], BMI [OR: 1.23, p<0.001, AUC=0.77], and SCD [OR: 1.27, p<0.001, AUC=0.81) were predictors of non-diagnostic SWE. UGAP prediction of non-diagnostic SWE was similar in subgroups with the measurement region at least 1 cm (OR: 1.64, n = 68), and 2 cm (OR: 1.54, n = 16) from the liver capsule. UGAP was a worse predictor than SCD (p = 0.04), while not significantly different than BMI (p = 0.15). BMI and SCD did not differ in predicting non-diagnostic SWE (p = 0.44). ConclusionOur small preliminary study demonstrated that body habitus and hepatic attenuation, a marker of steatosis, both contribute to non-diagnostic SWE exams, however body wall thickness is the key driver. This informs patient selection for SWE exams and guides future research to mitigate these technical shortcomings. Clinical Relevance/ApplicationPatients with hepatic steatosis and large body habitus are at increased risk of non-diagnostic ultrasound shear wave elastography (SWE) exams. These patients, particularly those with increased body wall thickness, may benefit from liver fibrosis evaluation with alternative approaches following an initial non-diagnostic SWE exam. Researchers working to improve SWE technique should pay particular attention to mitigating attenuation and phase aberration from the body wall as this is the key driver of non-diagnostic exams.

Role of negative transthoracic echocardiography in excluding infective endocarditis

Abstract Background Recent guidelines suggest an extensive role of transesophageal echocardiography (TOE) in the diagnostic work-up for suspected infective endocarditis (IE). However, the negative predictive value of transthoracic echocardiography (TTE) remains poorly investigated. Purpose The purpose of our study was to evaluate the accuracy of TTE in ruling out IE in order to avoid unnecessary TOE, a more invasive and expensive diagnostic exam. Methods We reviewed data of 637 consecutive patients referred to our laboratory of echocardiography with a suspected diagnosis of IE who underwent TOE within 14 days of TTE (median 4.4 days; interquartile range 2.4-7.4). For each patient we obtained age, sex, blood culture results, complete blood count, blood chemistry, evidence of systemic embolism or pulmonary embolism, and presence of moderate/severe heart valve disease, congenital heart disease, valve prostheses and intracardiac devices. Patients with initial doubtful findings at TOE were referred for a follow-up TOE after one week and/or 18F fluorodeoxyglucose positron emission tomography computed tomography to achieve a definitive clinical diagnosis. Patients in whom a clear diagnosis of IE could not be achieved (n=7) were considered to have the disease. Results Of the 637 patients enrolled, 375 had negative TTE for IE (59%). TOE was positive and doubtful for IE in 44 (12%) and 29 (8%) of these patients, respectively. After further assessment, a final diagnosis of IE was achieved in 56 patients (15%). Variables associated with IE at univariable analysis included presence of valve prostheses (p&amp;lt;0.001), systemic or pulmonary embolism (p&amp;lt;0.001), lower platelet count (p=0.003), positive blood culture (p=0.005), aortic valve regurgitation (p=0.02), aortic valve stenosis (p=0.03) and mitral regurgitation (p=0.03). At multivariable logistic regression, independent predictors of IE (OR=odds ratio; CI=confidence interval) included evidence of systemic or pulmonary embolism (OR 17.75, 95% CI 6.66-47.3, p&amp;lt;0.001), bioprosthetic heart valves (OR 2.93, 95% CI 1.31-6.53 p=0.023) and lower platelet count (OR 0.995, 95% CI 0.991-0.998, p=0.003). Among the subgroup of patients (n=183, 49%) with no evidence of embolism, no bioprosthetic valve and platelet count &amp;gt;190,000/mL (median value), IE was diagnosed in 11 patients only (6%). Conclusions In our study, a negative TTE in the subgroup of patients with suspected IE showing platelet count &amp;gt;190,000/mL and absence of embolism and valvular bio-prosthesis, had a negative predictive value for IE of 94%, suggesting that, in this subset of patients, TOE can initially be delayed and performed only if clinical suspicion continues to remain high.

Leveraging a Diagnostic Exam for Cultivating AI Literacy: Postgraduate Student Reflections on ChatGPT

Leveraging a Diagnostic Exam for Cultivating AI Literacy: Postgraduate Student Reflections on ChatGPT

Circulatory collapse requiring mechanical circulatory support in a child with autoimmune adrenal insufficiency: a case report

BackgroundWe report a rare case of new onset autoimmune adrenal insufficiency in childhood, presenting with severe shock requiring mechanical circulatory support. In the current era of readily available imaging, laboratory and other diagnostic investigations, medical history and careful physical exam can often provide valuable diagnostic information for timely therapy.Case presentationA 7-year-old boy with a history of mild intermittent asthma, presented with severe cardiogenic shock requiring extracorporeal membrane oxygenation (ECMO). Bronzing of his entire body was noted on physical exam. Stress dose hydrocortisone was given for suspected adrenal insufficiency. After weaning from ECMO and extensive rehabilitation, the patient recovered and was discharged home.ConclusionPrimary adrenal insufficiency (PAI) should be considered in the context of physical exam and laboratory findings, even in the presence of circulatory shock.

Benefits and Harms of Hepatocellular Carcinoma Screening Outreach in Patients with Cirrhosis: A Multi-Center Randomized Clinical Trial.

The value of hepatocellular carcinoma (HCC) screening is defined by the balance of benefits from early tumor detection vs harms due to false positive results. We evaluated the value of a mailed outreach strategy for HCC screening in patients with cirrhosis. We conducted a multi-center pragmatic randomized clinical trial comparing mailed outreach for HCC screening (n = 1436) and usual care with visit-based screening (n = 1436) among patients with cirrhosis at three health systems from March 2018 to September 2021. Outcomes of interest were early-stage HCC detection (ie, screening benefit) and diagnostic evaluation for false positive or indeterminate results (ie, screening harm). Screening harm was categorized as mild, moderate, and severe based on number and type of diagnostic exams. All patients were included in intention-to-screen analyses. Of 125 patients diagnosed with HCC (67 outreach and 58 usual care), 71.2% were found at an early stage per the Milan Criteria. Early tumor detection did not significantly differ between the outreach and usual care arms (64.2% vs 79.3%, p = .06). The proportion of patients with physical harms also did not differ between the outreach and usual care arms (10.8% vs 10.7%, p = .95) with 5.9% in both arms having mild harms, 4.0% and 3.8% respectively with moderate harms, and 0.9% and 1.0% respectively with severe harms. Most patients enrolled in HCC screening were detected at an early stage, and a minority experienced physical harms. A mailed outreach strategy did not significantly increase early HCC detection or physical harms compared to usual care. NCT02582918 and NCT03756051.

Factors Influencing Timely Follow-up After Inconclusive Screening Mammograms at a 3D Mobile Mammography Center.

Background The Linda Fenner 3D Mobile Mammography Center (LFMMC) was created to reduce disparities in screening for breast cancer and improve survival for women with limited access to such screening.However, for screened patients requiring follow-up testing, research has shown a wide variation of time taken to access diagnostic imaging, especially among uninsured women. Aim To explore factors associated with longer (>30 days) time intervals to complete diagnostic imaging after screening. Methods This was a retrospective cohort study using data from the LFMMC from 2014 to 2022. Women living in Miami-Dade County (MDC), over the age of 40, uninsured, and requiring follow-up diagnostic imaging after breast cancer screening were included. Factors assessed included women's age, area of residency, race, primary language spoken, marital status, body mass index (BMI), history of hormone use, previous mammogram, breast implants, breast cancer in immediate family, past breast surgery, and menopause status. The interval of time taken between receiving a screening mammogram result and completing further diagnostic imaging was the outcome, dichotomized into greater than 30 days (longer follow-up time) or up to 30 days.Multivariable binary logistic regression models were used to estimate independent associations (odds ratio [OR] and 95% confidence interval [CI]) of selected factors and longer time intervals to complete diagnostic imaging follow-up. Results We analyzed data from 926 eligible patients. Themean age was 50.1 years (SD = 8.81). A majority werewhite (n = 643; 69%), Hispanic (n = 698; 72%), had a history of previous mammograms (n = 589; 64%), and had no family history of breast cancer (n = 757; 82%).About 50% had a diagnostic follow-up exam performed after 30 days (median time to follow-up was 32, interquartile range 23-46 days). Single women had 30% lower odds of longer follow-up than married women (OR 0.70, 95% CI 0.52-0.93). Residents of Homestead (a city within Miami-Dade County) had 2.5 higher odds of having a longer time to follow-up, compared to non-Homestead residents (OR 2.50, 95% CI 1.60-3.90). Conclusions Being single was associated with a shorter time to follow up with diagnostic imaging while residing in Homestead was associated with a longer time to follow-up. Further research with a larger sample and further details on patient characteristics are warranted to better identify targets for interventions aimed at optimizing continuity of care and detecting breast cancer at earlier stages.

A Novel Method and Python Library for ECG Signal Quality Assessment.

Electrocardiogram (ECG) is one of the reference cardiovascular diagnostic exams. However, the ECG signal is very prone to being distorted through different sources of artifacts that can later interfere with the diagnostic. For this reason, signal quality assessment (SQA) methods that identify corrupted signals are critical to improve the robustness of automatic ECG diagnostic methods. This work presents a review and open-source implementation of different available indices for SQA as well as introducing an index that considers the ECG as a dynamical system. These indices are then used to develop machine learning models which evaluate the quality of the signals. The proposed index along the designed ML models are shown to improve SQA for ECG signals.

Access to genetic evaluation of 1463 individuals with orofacial cleft in Brazil

ObjectiveThe current study delves into the accessibility of genetic evaluations for individuals with orofacial clefts (OC), comparing data between genetics and treatment centers across Brazil. MethodsThis cross-sectional retrospective study analyzed primary data from 1463 OC individuals registered in the Brazilian Database of Craniofacial Anomalies (BDCA) between 2008 and 2018 without age or sex selection. Diagnostic exam results stemming from research projects until 2023 were considered. ResultsOf the 1463 individuals with typical OC, 987 were non-syndromic, 462 were syndromic (SOC), 10 presented atypical forms, and three were not specified OC cases. The average age for accessing laboratory diagnosis was 8.5 years among SOC individuals. Notably, more SOC cases were registered in genetics centers than treatment and rehabilitation centers (37.1 % vs. 29 %, p = 0.0015). Those originating from genetics centers accessed diagnosis at an average age of 7.3 years, while those from treatment and rehabilitation centers experienced delays with an average age of 10.7 years (p = 0.0581). ConclusionsIrrespective of the center of origin, the data highlight delayed diagnosis and challenges in accessing genetic tests for the syndromic group. Given the widespread reliance on the public health system by most of the Brazilian population, disseminating this data can significantly contribute to shaping an informed perspective on healthcare access. These insights can improve public policies tailored to the unique needs of individuals with OC.

Novel Approaches for Early Detection of Retinal Diseases Using Artificial Intelligence.

An increasing amount of people are globally affected by retinal diseases, such as diabetes, vascular occlusions, maculopathy, alterations of systemic circulation, and metabolic syndrome. This review will discuss novel technologies in and potential approaches to the detection and diagnosis of retinal diseases with the support of cutting-edge machines and artificial intelligence (AI). The demand for retinal diagnostic imaging exams has increased, but the number of eye physicians or technicians is too little to meet the request. Thus, algorithms based on AI have been used, representing valid support for early detection and helping doctors to give diagnoses and make differential diagnosis. AI helps patients living far from hub centers to have tests and quick initial diagnosis, allowing them not to waste time in movements and waiting time for medical reply. Highly automated systems for screening, early diagnosis, grading and tailored therapy will facilitate the care of people, even in remote lands or countries. A potential massive and extensive use of AI might optimize the automated detection of tiny retinal alterations, allowing eye doctors to perform their best clinical assistance and to set the best options for the treatment of retinal diseases.

NURS-15. THE ROLE OF THE ADVANCED PRACTICE PROVIDER AND NURSES IN CLINICAL TRIALS

Abstract BACKGROUND For many years clinical trials fell under the umbrella of medicine without much acknowledgement to the role of the nurse, both as advanced practice provider (APP) and staff nurse. Oncology continues to rank as one of the highest subspecialties when it comes to availability and participation in clinical trials. There remain multiple barriers to involvement including availability, lack of education, and medical mistrust. The specialized role and skill set of the APP and RN as part of the clinical trial team is important in overcoming these barriers. METHODS We distributed a survey to members of the Advanced Practice Provider and Nurse Investigator Committee (APPNIC), a group within the Pediatric Neuro-Oncology Consortium (PNOC), in order to identify themes, barriers to care, and opportunities for both the APP and RN within clinical trials. The use of a survey and interviews within our APPNIC cohort allowed us to collaborate on the nursing role, prioritize care in new and amended trials, and share unanticipated adverse effects and effective management. RESULTS APPs are actively involved with clinical trial enrollment, performance of diagnostic exams and procedures, education, and early recognition/management of adverse effects. There is also a growing theme of the APP as sub-investigator which provides value in facilitating consent, impacting accrual, determining eligibility, managing anticipated side effects. The role of the staff nurse in clinical trials is found to be vital in providing consistent communication/support, educating patients and families, and alleviating adherence and medical mistrust. CONCLUSION The APP and nurse have a specialized, relevant skill set, which when included as part of the multi-disciplinary team, has the ability to decrease barriers and increase overall delivery and safety of clinical trials. Our goal is to outline specific roles we feel should be standardized in the international arena for nursing involvement within clinical trials.

Repercussions of the COVID-19 pandemic on breast cancer actions in a Brazilian state.

To analyze whether the COVID-19 pandemic had an impact on the screening, diagnosis and treatment of breast cancer in women up to 50 years of age in the state of Pará. Retrospective, cross-sectional study with a quantitative approach, using data from the Information Technology Department of the Brazilian Unified Health System. (DATASUS). The number of exams carried out in the pre-pandemic (2018-2019) and pandemic (2020-2021) period was analyzed based on the percentage variation, application of the chi-square test and G test for the time of exams and start time of treatment. During the pandemic period, there was a greater number of screening mammograms (+3.68%), cytological (+23.68%), histological (+10.7%) and a lower number of diagnostic mammograms (-38.7%). The time interval for carrying out the exams was up to 30 days for screening and diagnostic exams and more than 60 days to start treatment during the pandemic period. Although the results indicate an increase in the number of screening and diagnostic procedures for breast cancer during the pandemic period, with the exception of diagnostic mammography, when considering probability values, the study points out that statistically the COVID-19 pandemic did not interfere with actions of breast cancer, in women over 50 years of age, in the state of Pará. Considering the autonomy of nursing and its role in public health, it is up to the professionals who are in charge of primary care programs to implement contingency plans in periods of crisis so that the population is not left unassisted.

Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge

Many real-world image recognition problems, such as diagnostic medical imaging exams, are “long-tailed” – there are a few common findings followed by many more relatively rare conditions. In chest radiography, diagnosis is both a long-tailed and multi-label problem, as patients often present with multiple findings simultaneously. While researchers have begun to study the problem of long-tailed learning in medical image recognition, few have studied the interaction of label imbalance and label co-occurrence posed by long-tailed, multi-label disease classification. To engage with the research community on this emerging topic, we conducted an open challenge, CXR-LT, on long-tailed, multi-label thorax disease classification from chest X-rays (CXRs). We publicly release a large-scale benchmark dataset of over 350,000 CXRs, each labeled with at least one of 26 clinical findings following a long-tailed distribution. We synthesize common themes of top-performing solutions, providing practical recommendations for long-tailed, multi-label medical image classification. Finally, we use these insights to propose a path forward involving vision-language foundation models for few- and zero-shot disease classification.

Professional identity work of nurse practitioners and family physicians in primary care in Quebec and Ontario – a study protocol

BackgroundSolo medical practices in primary healthcare delivery have been abandoned in favor of interdisciplinary teamwork in most Western countries. Dynamics in interdisciplinary teams might however be particularly difficult when two or more autonomous health professionals develop similar roles at the practice level. This is the case of family physicians (FPs) and nurse practitioners (NPs), due to the fact that the latter might accomplish not only the traditional role proper to a nurse, but also several medical activities such as requesting diagnostic exams and prescribing medical treatments. The tensions that this overlap might generate and their implications in regard of the development of professional identities, and consequently of the quality of health care delivered, have been suggested, but rarely examined empirically. The goal of this study is to examine identity work, i.e., the processes of (re)construction of professional identities, of NPs and FPs working together in primary care interdisciplinary teams.MethodsA longitudinal, interpretive, and comparative multiple (n = 2) case study is proposed. Identity work theory in organizations is adopted as theoretical perspective. Cases are urban primary care multidisciplinary teams from two different Canadian provinces: Quebec and Ontario. Participants are NPs, FPs, managers, and patients. Data gathering involves audio-diaries, individual semi-structured and focus group interviews, observations, and archival material. Narrative and metaphor techniques are adopted for analyzing data collected. Within- and cross-case analysis will be performed.DiscussionFor practice, the results of this investigation will: (a) be instrumental for clinicians, primary care managers, and policy decision-makers responsible for the implementation of interdisciplinary teamwork in primary healthcare delivery to improve decision-making processes and primary care team performance over time; (b) inform continuing interdisciplinary professional development educational initiatives that support competency in health professionals’ identity construction in interdisciplinary primary care organizations. For research, the project will contribute to enriching theory about identity construction dynamics in health professions, both in the fields of health services and primary care education research.

Screening for cardiac amyloidosis in patients with tenosynovial red flags: A collaboration between family medicine and cardiology

BackgroundAmyloid deposition in tenosynovial structures precedes cardiac involvement up to 20 years. Therefore, a cardiological screening in patients with a history of tenosynovial manifestations of cardiac amyloidosis (CA) could lead to an increased number of early diagnoses. MethodsPatients with tenosynovial manifestations of CA (carpal tunnel syndrome, atraumatic biceps tendon rupture, lumbar spinal stenosis) have been identified by general practitioners and evaluated in a Referral Center for CA. Patients with a high suspicion of CA underwent the CA diagnostic pathway. ResultsAmong 50 General Practitioners (GP) contacted, 10 (20%) agreed to participate in the study for a total of 5615 patients ≥60 years. One hundred forty-five patients met the inclusion criteria, 2 of them already had a diagnosis of CA, and 57 agreed to undergo a cardiological evaluation (electrocardiography, echocardiography, NTproBNP assay). The median age was 73 [67–80] years and 31 (54%) were women. Eight patients were suggested to start the CA diagnostic pathway, five of them underwent a complete diagnostic evaluation for CA, three refused to complete the diagnostic exams and no new diagnoses were made. ConclusionA screening program for CA in patients with tenosynovial manifestations identified by general practitioners is feasible, but may not yield a high rate of new diagnosis. In this study, we identified two patients who already had a diagnosis of CA, and among patients at high risk for CA, 37% refused to complete the diagnostic pathway. Increased awareness of CA among patients might increase participation and diagnostic yield in screening studies. Further validation of this protocol is needed to evaluate its diagnostic performance.

Development and analysis of a Numbas diagnostic tool for use in a mathematics refresher program

We describe the development and analysis of an online diagnostic tool implemented in the Numbas e-learning system and used in an Australian university mathematics refresher program. Following the rapid transition to online delivery of the refresher program caused by COVID-19, the diagnostic instruments and methods used within the pre-pandemic, in-person, version of the program were lost. In 2022, we undertook to revive them in a way that would honour their original diagnostic purpose but offer a more sophisticated approach utilising the Numbas diagnostic exam type. Improvement of the tool after its initial deployment has involved the use of Rasch-based item analysis and recursive refinement of the knowledge map underlying the items.

Improving Access to Anti-HDV Testing: Development and Validation of an Affordable In-House ELISA Assay.

In certain low-income nations, the hepatitis Delta virus and hepatitis B virus (HBV) pose a serious medical burden, where the prevalence of hepatitis B surface antigen (HBsAg) is greater than 8%. Especially in rural places, irregular diagnostic exams are the main restriction and reason for underestimation. Utilizing serum samples from a Pakistani isolate, an internal ELISA for the quick identification of anti-HDV was created, and the effectiveness of the test was compared to a commercial diagnostic kit. HDV-positive serum samples were collected, and a highly antigenic domain of HDAg antigen was derived from them. This antigenic HDAg was expressed in a bacterial expression system, purified by Ni-chromatography, and confirmed by SDS-PAGE and Western blot analysis. The purified antigen was utilized to develop an in-house ELISA assay for anti-HDV antibody detection of the patient's serum samples at very low cost. Purified antigens and positive and negative controls can detect anti-HDV (antibodies) in ELISA plates. The in-house developed kit's efficiency was compared with that of a commercial kit (Witech Inc., USA) by the mean optical density values of both kits. No significant difference was observed (a P value of 0.576) by applying statistical analysis. The newly developed in-house ELISA is equally efficient compared to commercial kits, and these may be useful in regular diagnostic laboratories, especially for analyzing local isolates.

Learned high-resolution cardiac CT imaging from ultra-high-resolution PCD-CT.

Coronary computed tomography angiography (cCTA) is a widely used non-invasive diagnostic exam for patients with coronary artery disease (CAD). However, most clinical CT scanners are limited in spatial resolution from use of energy-integrating detectors (EIDs). Radiological evaluation of CAD is challenging, as coronary arteries are small (3-4 mm diameter) and calcifications within them are highly attenuating, leading to blooming artifacts. As such, this is a task well suited for high spatial resolution. Recently, photon-counting-detector (PCD) CT became commercially available, allowing for ultra-high resolution (UHR) data acquisition. However, PCD-CTs are costly, restricting widespread accessibility. To address this problem, we propose a super resolution convolutional neural network (CNN): ILUMENATE (Improved LUMEN visualization through Artificial super-resoluTion imagEs), creating a high resolution (HR) image simulating UHR PCD-CT. The network was trained and validated using patches extracted from 8 patients with a modified U-Net architecture. Training input and labels consisted of UHR PCD-CT images reconstructed with a smooth kernel degrading resolution (LR input) and sharp kernel (HR label). The network learned the resolution difference and was tested on 5 unseen LR patients. We evaluated network performance quantitatively and qualitatively through visual inspection, line profiles to assess spatial resolution improvements, ROIs for CT number stability and noise assessment, structural similarity index (SSIM), and percent diameter luminal stenosis. Overall, ILUMENATE improved images quantitatively and qualitatively, creating sharper edges more closely resembling reconstructed HR reference images, maintained stable CT numbers with less than 4% difference, reduced noise by 28%, maintained structural similarity (average SSIM = 0.70), and reduced percent diameter stenosis with respect to input images. ILUMENATE demonstrates potential impact for CAD patient management, improving the quality of LR CT images bringing them closer to UHR PCD-CT images.

Management of cancer treatment-induced bone loss in patients with breast and hormone sensitive prostate cancer: AIOM survey.

Cancer treatment-induced bone loss is a side effect of hormonal therapy that can severely affect patients' quality of life. The aim of this survey was to obtain an updated picture of management of bone health in patients with breast cancer undergoing adjuvant hormonal therapy and in patients with hormone sensitive prostate cancer according to Italian oncologists. Our survey was made up of 21 multiple-choice questions: the first part dealt with the respondents' characteristics, while the second with management of bone health in the described setting. An invitation to complete the survey was sent by e-mail to 2336 oncologists, members of Italian Association of Medical Oncology, in October 2022. Overall, 121 (5.2%) Italian oncologists completed the survey. In most cases (57%) the oncologist personally took charge of the management of bone health in patients at risk for cancer treatment-induced bone loss. At the beginning of hormonal therapy, most respondents reported to require bone health diagnostic exams, such as dual-energy X-ray absorptiometry (89%), repeated with different timing. Main reported reasons (not mutually exclusive) for prescribing antiresorptive drugs were modifying fracture risk (87%), densitometry values (75%) or prognosis (34%). Answers about the management of antiresorptive therapy were heterogeneous. A heterogeneous approach on the management of cancer treatment-induced bone loss in Italy arises from this survey. This scenario highlights the need for a major consensus of the Italian scientific community on the diagnostic and therapeutic approach of cancer treatment-induced bone loss and for a greater awareness of this topic among Italian oncologists.

Dementia- A Review of the Research and Therapeutic Measures

As our population ages, we are seeing more and more patients with variations of cerebral dementia. This review cites the symptoms, the neuropathology, the various research trials and ideas, the diagnostic exams, and the treatments commonly used.

Predicting students’ academic progress and related attributes in first-year medical students: an analysis with artificial neural networks and Naïve Bayes

BackgroundDropout and poor academic performance are persistent problems in medical schools in emerging economies. Identifying at-risk students early and knowing the factors that contribute to their success would be useful for designing educational interventions. Educational Data Mining (EDM) methods can identify students at risk of poor academic progress and dropping out. The main goal of this study was to use machine learning models, Artificial Neural Networks (ANN) and Naïve Bayes (NB), to identify first year medical students that succeed academically, using sociodemographic data and academic history.MethodsData from seven cohorts (2011 to 2017) of admitted medical students to the National Autonomous University of Mexico (UNAM) Faculty of Medicine in Mexico City were analysed. Data from 7,976 students (2011 to 2017 cohorts) of the program were included. Information from admission diagnostic exam results, academic history, sociodemographic characteristics and family environment was used. The main dataset included 48 variables. The study followed the general knowledge discovery process: pre-processing, data analysis, and validation. Artificial Neural Networks (ANN) and Naïve Bayes (NB) models were used for data mining analysis.ResultsANNs models had slightly better performance in accuracy, sensitivity, and specificity. Both models had better sensitivity when classifying regular students and better specificity when classifying irregular students. Of the 25 variables with highest predictive value in the Naïve Bayes model, percentage of correct answers in the diagnostic exam was the best variable.ConclusionsBoth ANN and Naïve Bayes methods can be useful for predicting medical students’ academic achievement in an undergraduate program, based on information of their prior knowledge and socio-demographic factors. Although ANN offered slightly superior results, Naïve Bayes made it possible to obtain an in-depth analysis of how the different variables influenced the model. The use of educational data mining techniques and machine learning classification techniques have potential in medical education.