RESUMEN

BACKGROUND AND OBJECTIVES: Blood donor questionnaires are tools used to screen prospective blood donors to determine their eligibility. There are limited data regarding blood donor questionnaires and infectious disease screening of the blood supply in Latin American countries. This study aimed to survey donor centres in Latin American countries to learn more about blood donor screening and infection assessment. MATERIALS AND METHODS: An international team of transfusion medicine professionals including medical directors and supervisors who work or collaborate with Latin American donor centres, called 'Comité de Investigación en Medicina Transfusional', designed a survey (16 questions) to characterize blood donor eligibility in Latin America. RESULTS: Eighty-two institutions from 14 Latin American countries responded to the survey. Most donor centres (66%; 54 of 82) had a donor deferral percentage between 5% and 25%, and the most common causes of deferrals were low haemoglobin and high-risk behaviour. Most donors in blood centres were directed family donors compared with voluntary donors. Infection evaluation included mostly serologic assessment (81%; 30 of 37) for human immunodeficiency virus (HIV), Hepatitis B, Hepatitis C, Treponema pallidum and Trypanosoma cruzi rather than nucleic acid tests (5%; 2 of 37). CONCLUSION: Heterogeneity exists in donor selection and infectious disease screening in Latin American countries. This survey provides valuable information to understand Latin American blood centre practices.

RESUMEN

BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is one of the most prevalent neurodegenerative brain diseases worldwide. Therefore, accurate PD screening is crucial for early clinical intervention and treatment. Recent clinical research indicates that changes in pathology, such as the texture and thickness of the retinal layers, can serve as biomarkers for clinical PD diagnosis based on optical coherence tomography (OCT) images. However, the pathological manifestations of PD in the retinal layers are subtle compared to the more salient lesions associated with retinal diseases. METHODS: Inspired by textural edge feature extraction in frequency domain learning, we aim to explore a potential approach to enhance the distinction between the feature distributions in retinal layers of PD cases and healthy controls. In this paper, we introduce a simple yet novel wavelet-based selection and recalibration module to effectively enhance the feature representations of the deep neural network by aggregating the unique clinical properties, such as the retinal layers in each frequency band. We combine this module with the residual block to form a deep network named Wavelet-based Selection and Recalibration Network (WaveSRNet) for automatic PD screening. RESULTS: The extensive experiments on a clinical PD-OCT dataset and two publicly available datasets demonstrate that our approach outperforms state-of-the-art methods. Visualization analysis and ablation studies are conducted to enhance the explainability of WaveSRNet in the decision-making process. CONCLUSIONS: Our results suggest the potential role of the retina as an assessment tool for PD. Visual analysis shows that PD-related elements include not only certain retinal layers but also the location of the fovea in OCT images.

Asunto(s)

RESUMEN

PURPOSE OF REVIEW: This review seeks to describe the updates in the literature - particularly with regards to the epidemiology and diagnosis of Chagas disease. Additionally, this paper describes updates to the antiparasitic treatment for Chagas disease. RECENT FINDINGS: With regards to changing epidemiology, autochthonous cases are being found within the USA in addition to Latin America. Additionally, there appears to be more intermixing of discrete typing units-meaning, they are not confined to specific geographic regions. Screening for Chagas disease is recommended in persons who lived in areas with endemic Chagas, persons wtih family member diagnosed with Chagas Disease, persons who have lived in homes of natural material in Latin America, and persons with history of kissing bug bites. Treatment for the parasitic infection remains limited to benznidazole and nifurtimox, and the role of these treatments in Chagas cardiomyopathy has not yet been definitively defined. Finally, indications for and management of heart transplant in the setting of Chagas disease are discussed. FUTURE RESEARCH: Use of antiparasitics during chronic chagas disease should be further explored. Additionally, future research identifying other markers of infection would be valuable to defining cure from infection.

RESUMEN

Affordable, rapid methods for identifying mild Alzheimer's disease (AD) are needed. A simple, brief performance-based test involving the learning of functional upper-extremity movements has been developed and is associated with AD pathology and functional decline. However, its specificity to AD relative to other neurodegenerative diseases that present with motor impairment is unknown. This study examined whether this novel test could distinguish between 34 participants diagnosed with mild AD (Clinical Dementia Rating Scale = 0.5-1) from 23 participants with mild-to-moderate Parkinson's disease (PD) (Hoehn and Yahr = 2-3) using Receiver Operating Characteristic analysis of secondary data from two separate clinical trials. Indicators of diagnostic accuracy demonstrated that the test identified participants with AD, who had worse scores than those with PD, suggesting it may be a viable screening tool for mild AD. Exploratory analyses with a control group (n=52) further showed that test scores were not sensitive to motor dysfunction.

Asunto(s)

RESUMEN

Forty percent of diabetics will develop chronic kidney disease (CKD) in their lifetimes. However, as many as 50% of these CKD cases may go undiagnosed. We developed screening recommendations stratified by age and previous test history for individuals with diagnosed diabetes and unknown proteinuria status by race and gender groups. To do this, we used a Partially Observed Markov Decision Process (POMDP) to identify whether a patient should be screened at every three-month interval from ages 30-85. Model inputs were drawn from nationally-representative datasets, the medical literature, and a microsimulation that integrates this information into group-specific disease progression rates. We implement the POMDP solution policy in the microsimulation to understand how this policy may impact health outcomes and generate an easily-implementable, non-belief-based approximate policy for easier clinical interpretability. We found that the status quo policy, which is to screen annually for all ages and races, is suboptimal for maximizing expected discounted future net monetary benefits (NMB). The POMDP policy suggests more frequent screening after age 40 in all race and gender groups, with screenings 2-4 times a year for ages 61-70. Black individuals are recommended for screening more frequently than their White counterparts. This policy would increase NMB from the status quo policy between $1,000 to  $8,000 per diabetic patient at a willingness-to-pay of $150,000 per quality-adjusted life year (QALY).

RESUMEN

Background: Over the last 3 decades, over 700 million individuals worldwide have been diagnosed with chronic kidney disease (CKD). In a 2017 survey in southern Brazil, 11.4% of those surveyed had CKD. Early identification and effective therapy in Brazil may reduce CKD's impact. This panel discusses the early diagnosis and treatment of CKD and the barriers and actions needed to improve the management of CKD in Brazil. A panel of Brazilian nephrologists was provided with relevant questions to address before a multiday conference. During this meeting, each narrative was discussed and edited through several rounds until agreement on the relevant topics and recommendations was achieved. Summary: Panelists highlighted hurdles to early diagnosis and treatment of CKD. These include, but are not limited to, a lack of public and patient education, updated recommendations, multidisciplinary CKD treatment, and a national CKD database. People-centered, physician-centered, and healthcare institution-centered actions can be taken to improve outcomes. Patient empowerment is needed via multiple channels of CKD education and access to health-monitoring wearables and apps. Primary care clinicians and nonspecialists must be trained to screen and manage CKD-causing illnesses, including diabetes and hypertension. The healthcare system may implement a national health data gathering system, more screening tests, automated test result reporting, and telehealth. Key Messages: Increasing access to early diagnosis can provide a path to improving care for patients with CKD. Concerted efforts from all stakeholders are needed to overcome the barriers.

RESUMEN

The development of stem cell-derived tissue constructs (SCTCs) for clinical applications, including regenerative medicine, drug and disease screening offers significant hope for detecting and treating intractable disorders. SCTCs display a variety of biomarkers that can be used to understand biological mechanisms, assess drug interactions, and predict disease. Although SCTCs can be derived from patients and share the same genetic make-up, they are nevertheless distinct from human patients in many significant ways, which can undermine the clinical significance of measurements in SCTCs. This study defines biomarkers, how they apply to SCTCs, and clarifies specific ethical issues associated with the use of SCTCs for drug and disease screening.

RESUMEN

BACKGROUND: Fundus photography is the most important examination in eye disease screening. A facilitated self-service eye screening pattern based on the fully automatic fundus camera was developed in 2022 in Shanghai, China; it may help solve the problem of insufficient human resources in primary health care institutions. However, the service quality and residents' preference for this new pattern are unclear. OBJECTIVE: This study aimed to compare the service quality and residents' preferences between facilitated self-service eye screening and traditional manual screening and to explore the relationships between the screening service's quality and residents' preferences. METHODS: We conducted a cross-sectional study in Shanghai, China. Residents who underwent facilitated self-service fundus disease screening at one of the screening sites were assigned to the exposure group; those who were screened with a traditional fundus camera operated by an optometrist at an adjacent site comprised the control group. The primary outcome was the screening service quality, including effectiveness (image quality and screening efficiency), physiological discomfort, safety, convenience, and trustworthiness. The secondary outcome was the participants' preferences. Differences in service quality and the participants' preferences between the 2 groups were compared using chi-square tests separately. Subgroup analyses for exploring the relationships between the screening service's quality and residents' preference were conducted using generalized logit models. RESULTS: A total of 358 residents enrolled; among them, 176 (49.16%) were included in the exposure group and the remaining 182 (50.84%) in the control group. Residents' basic characteristics were balanced between the 2 groups. There was no significant difference in service quality between the 2 groups (image quality pass rate: P=.79; average screening time: P=.57; no physiological discomfort rate: P=.92; safety rate: P=.78; convenience rate: P=.95; trustworthiness rate: P=.20). However, the proportion of participants who were willing to use the same technology for their next screening was significantly lower in the exposure group than in the control group (P<.001). Subgroup analyses suggest that distrust in the facilitated self-service eye screening might increase the probability of refusal to undergo screening (P=.02). CONCLUSIONS: This study confirms that the facilitated self-service fundus disease screening pattern could achieve good service quality. However, it was difficult to reverse residents' preferences for manual screening in a short period, especially when the original manual service was already excellent. Therefore, the digital transformation of health care must be cautious. We suggest that attention be paid to the residents' individual needs. More efficient man-machine collaboration and personalized health management solutions based on large language models are both needed.

Asunto(s)

Asunto(s)

RESUMEN

Despite having significantly higher rates of atopic dermatitis, psoriasis, and pigmentary disorders compared to White patients, studies suggest that Asian Americans are underrepresented in outpatient dermatology clinics. In this study, we utilize the National Health Interview Survey (NHIS) and prioritize disaggregated analyses to evaluate differences between the most populous Asian American subgroups (Chinese, Filipino, Indian, and "Other") in utilization of outpatient dermatologic care. We utilized multivariable logistic regression to compare outpatient dermatologic care use between each Asian American subgroup and Non-Hispanic Whites. Out of 96,559 adults, our study included 5264 self-identified Asian American and 91,295 non-Hispanic White adults. Most Asian participants were female, had health insurance, and had incomes > 2 times above the federal poverty line. We found that, compared to 21.4% for NH whites, lifetime prevalence of total body skin exam was highest among Filipino Americans (12.3%) and lowest among Indian Americans (7%). Additionally, all Asian American subgroups had a significantly lower odd than NH Whites of ever having a total body skin exam, with Indian Americans having the lowest odds. While the benefit of TBSEs in Indian Americans is unclear, it is possible that differing cultural perceptions about dermatologic needs, barriers to care, or immigration status may be contributing to the observed difference. Furthermore, the Indian diaspora encapsulates a range of skin tones, risk factors, and behaviors that may differentially influence dermatologic disease risk, similar to trends identified among Hispanic patients (Trepanowski et al. in J Am Acad Dermatol 88:1206-1209, 2023). Additional research utilizing the seven national databases that have been identified as providing disaggregated Asian racial information (Kamal et al. in J Am Acad Dermatol, 2023) may be useful to further illuminate avenues for intervention.

Asunto(s)

RESUMEN

Introduction: Screening for chronic kidney disease relies on accurate and precise creatinine measurements. Traditionally, creatinine is measured in serum or plasma using high-throughput chemistry analyzers. However, dried blood spots (DBS) can also be utilized to improve testing access. Methods: Samples were obtained from a 6 mm DBS punch, which was reconstituted in water before undergoing an acetonitrile crash. The resulting supernatant was diluted using an 80:20 acetonitrile: water before injection. Creatinine was identified using an isocratic gradient, and detected using an API 4000 triple quadrupole mass analyzer. Quantification relied on matrix-matched calibrators, with values harmonized to the Roche Cobas enzymatic assay. Validation studies assessing method performance included precision, linearity, accuracy, method comparison, stability, interference, and matrix effects. Results: The LC-MSMS assay was linear from 0.3 to 20 mg/dL (y = 1.02x-0.11; R2 = 0.996). Precision ranged from 5.2 to 8.1 % using matrix-matched controls (n = 4) that spanned the analytical measurement range. LC-MSMS results corresponded to the enzymatic assay (Roche) with a fitted line equation of y = 0.956x-0.07 (R2 = 0.995; n = 173). The Siemens and Roche enzymatic assays demonstrated higher accuracy in correlating to the DBS creatinine concentration (n = 40 paired venous/DBS collections) compared to the Beckman Jaffe assay (-2.5 % and -0.8 % versus -6.3 % and -4.1 %, respectively) or the iSTAT (-28.4 % and -27.1 %, respectively). Accuracy was unaffected by hematocrit, blood spot volume, excess IgG or IgA, or hypertriglyceridemia. No matrix effects were observed, and both extraction and processing efficiency were robust.Ambient stability extended to at least 10 days, and exposure to extreme temperature did not affect the creatinine results. Conclusion: We successfully developed an accurate and precise LC-MSMS method for quantifying creatinine in DBS.

RESUMEN

Existing osteoporosis screening tools have limitations, including using race as a predictor, and development on homogeneous samples. This biases risk assessment of osteoporosis in diverse populations and increases health inequities. We develop a tool that relies on variables easily learned during point-of-care, known by individuals, and with negligible racial bias. Data from the 2012-2016 waves of the population-based cohort Health and Retirement Study (HRS) were used to build a predictive model of osteoporosis diagnosis on a 75 % training sample of adults ages 50-90. The model was validated on a 25 % holdout sample and a cross-sectional sample of American individuals ages 50-80 from the National Health and Nutrition Examination Survey (NHANES). Sensitivity and specificity were compared across sex and race/ethnicity. The model has high sensitivity in the HRS holdout sample (89.9 %), which holds for those identifying as female and across racial/ethnic groups. Specificity is 57.9 %, and area under the curve (AUC) is approximately 0.81. Validation in the NHANES sample using empirically measured osteoporosis produced relatively good values of sensitivity, specificity, and consistency across groups. The model was used to create a publicly-available, open-source tool called the Osteoporosis Health Equality (& Equity) Evaluation (OsteoHEE). The model provided high sensitivity for osteoporosis diagnosis, with consistently high results for those identifying as female, and across racial/ethnic groups. Use of this tool is expected to improve equity in screening and increase access to bone density scans for those at risk of osteoporosis. Validation on alternative samples is encouraged.

RESUMEN

Alzheimer's disease (AD) is characterized by amyloid beta (Aß) plaques and hyperphosphorylated tau in the brain. Aß plaques precede cognitive impairments and can be detected through amyloid-positron emission tomography (PET) or in cerebrospinal fluid (CSF). Assessing the plasma Aß42/Aß40 ratio seems promising for non-invasive and cost-effective detection of brain Aß accumulation. This approach involves some challenges, including the accuracy of blood-based biomarker measurements and the establishment of clear, standardized thresholds to categorize the risk of developing brain amyloid pathology. Plasma Aß42/Aß40 ratio was measured in 277 volunteers without dementia, 70 AD patients and 18 non-AD patients using single-molecule array. Patients (n = 88) and some volunteers (n = 66) were subject to evaluation of amyloid status by CSF Aß quantification or PET analysis. Thresholds of plasma Aß42/Aß40 ratio were determined based on a Gaussian mixture model, a decision tree, and the Youden's index. The 0.0472 threshold, the one with the highest sensitivity, was retained for general population without dementia screening, and the 0.0450 threshold was retained for research and clinical trials recruitment, aiming to minimize the need for CSF or PET analyses to identify amyloid-positive individuals. These findings offer a promising step towards a cost-effective method for identifying individuals at risk of developing AD.

Asunto(s)

RESUMEN

OBJECTIVE: Exercise improves health, but illnesses can cause changes in exercise behavior, including starting or stopping. This study investigated the effects of chronic disease screening on inactive individuals' exercise behavior and analyzed the impact of age and chronic disease history on this relationship using stratified analysis. METHODS: Using a community-based prospective observational cohort design and data from the Changhua Community-Based Integrated Screening (CHCIS) dataset from 2005 to 2020, we examined 12,038 people who were screened at least twice and self-reported having never exercised at their first screening. Changes in exercise behavior were classified as "initiating exercise" and "remaining inactive." We obtained chronic disease screening results from CHCIS records, which included measurements of waist circumference, blood glucose, blood pressure, triglycerides, and high-density lipoproteins. SAS version 9.4 was used for COX proportional hazards regression. RESULTS: The findings indicated that abnormal waist circumference and blood pressure increased the likelihood of initiating exercise compared to normal results. Age stratification showed that those aged 40-49 with abnormal results were more likely to start exercising than normal participants, but not those under 40 or over 65. When stratified by chronic disease history, abnormal screening results correlated with exercise initiation only in groups without chronic disease history, except for those with a history of hyperlipidemia. CONCLUSIONS: This is the first study to demonstrate that abnormal screening results may influence exercise initiation in individuals who have never exercised, and this association varies by screening item, age, and disease history.

Asunto(s)

RESUMEN

High-throughput detection of large-scale samples is the foundation for rapidly accessing massive metabolic data in precision medicine. Machine learning is a powerful tool for uncovering valuable information hidden within massive data. In this work, we achieved the extraction of a single fingerprinting of 1 µL serum within 5 s through a high-throughput detection platform based on functionalized nanoparticles. We quickly obtained over a thousand serum metabolic fingerprintings (SMFs) including those of individuals with Helicobacter pylori (HP) infection. Combining four classical machine learning models and enrichment analysis, we attempted to extract and confirm useful information behind these SMFs. Based on all fingerprint signals, all four models achieved area under the curve (AUC) values of 0.983-1. In particular, orthogonal partial least squares discriminant analysis (OPLS-DA) model obtained value of 1 in both the discovery and validation sets. Fortunately, we identified six significant metabolic features, all of which can greatly contribute to the monitoring of HP infection, with AUC values ranging from 0.906 to 0.985. The combination of these six significant metabolic features can enable the precise monitoring of HP infection in serum, with over 95 % of accuracy, specificity and sensitivity. The OPLS-DA model displayed optimal performance and the corresponding scatter plot visualized the clear distinction between HP and HC. Interestingly, they exhibit a consistent reduction trend compared to healthy controls, prompting us to explore the possible metabolic pathways and potential mechanism. This work demonstrates the potential alliance between high-throughput detection and machine learning, advancing their application in precision medicine.

Asunto(s)

RESUMEN

In May 2003, Madrid established the universal newborn screening (NBS) for sickle cell disease (SCD). However, there are no studies resembling the evolution of a SCD neonate cohort followed according to national guidelines in Spain. The aim of this study is to describe the morbimortality and the stroke prevention programme in patients diagnosed by SCD NBS in Madrid. This is a multicentre, observational, prospective cohort study between 2003 and 2018; 187 patients diagnosed with SCD were included (151 HbSS, 6 HbSß0, 27 HbSC, 3 HbSß +), and median follow-up was 5.2 years (0.03-14.9). There were 5 deaths: 2 related to SCD in patients with severe genotype (HbSS/HbSß0). Overall survival reached 95% and SCD-related survival 96.8%. The most frequent events were fever without focus, vaso-occlusive crises and acute chest syndromes. Eight strokes occurred in 5 patients which led to a 90.7% stroke-free survival in severe genotype patients (first stroke rate, 0.54 per 100 patient-years). Transcranial Doppler (TCD) was performed in 95% of eligible patients; 75% of children with pathological TCD remained stroke-free. Regarding HbSS/HbSß0 patients, 50.1% received hydroxyurea and 9.5% haematopoietic stem cell transplantation. This study reflects the evolution of Madrid SCD cohort and provides morbimortality data similar to other developed countries.

Asunto(s)

RESUMEN

PURPOSE: To assess the performance and generalizability of a convolutional neural network (CNN) model for objective and high-throughput identification of primary angle-closure disease (PACD) as well as PACD stage differentiation on anterior segment swept-source OCT (AS-OCT). DESIGN: Cross-sectional. PARTICIPANTS: Patients from 3 different eye centers across China and Singapore were recruited for this study. Eight hundred forty-one eyes from the 2 Chinese centers were divided into 170 control eyes, 488 PACS, and 183 PAC + PACG eyes. An additional 300 eyes were recruited from Singapore National Eye Center as a testing data set, divided into 100 control eyes, 100 PACS, and 100 PAC + PACG eyes. METHODS: Each participant underwent standardized ophthalmic examination and was classified by the presiding physician as either control, primary angle-closure suspect (PACS), primary angle closure (PAC), or primary angle-closure glaucoma (PACG). Deep Learning model was used to train 3 different CNN classifiers: classifier 1 aimed to separate control versus PACS versus PAC + PACG; classifier 2 aimed to separate control versus PACD; and classifier 3 aimed to separate PACS versus PAC + PACG. All classifiers were evaluated on independent validation sets from the same region, China and further tested using data from a different country, Singapore. MAIN OUTCOME MEASURES: Area under receiver operator characteristic curve (AUC), precision, and recall. RESULTS: Classifier 1 achieved an AUC of 0.96 on validation set from the same region, but dropped to an AUC of 0.84 on test set from a different country. Classifier 2 achieved the most generalizable performance with an AUC of 0.96 on validation set and AUC of 0.95 on test set. Classifier 3 showed the poorest performance, with an AUC of 0.83 and 0.64 on test and validation data sets, respectively. CONCLUSIONS: Convolutional neural network classifiers can effectively distinguish PACD from controls on AS-OCT with good generalizability across different patient cohorts. However, their performance is moderate when trying to distinguish PACS versus PAC + PACG. FINANCIAL DISCLOSURES: The authors have no proprietary or commercial interest in any materials discussed in this article.

Asunto(s)

RESUMEN

Background: Migrants in Europe face a disproportionate burden of undiagnosed infection, including tuberculosis, blood-borne viruses, and parasitic infections and many belong to an under-immunised group. The European Centre for Disease Control (ECDC) has called for innovative strategies to deliver integrated multi-disease screening to migrants within primary care, yet this is poorly implemented in the UK. We did an in-depth qualitative study to understand current practice, barriers and solutions to infectious disease screening in primary care, and to seek feedback on a collaboratively developed digitalised integrated clinical decision-making tool called Health Catch UP!, which supports multi-infection screening for migrant patients. Methods: Two-phase qualitative study of UK primary healthcare professionals, in-depth semi-structured telephone-interviews were conducted. In Phase A, we conducted interviews with clinical staff (general practitioners (GPs), nurses, health-care-assistants (HCAs)); these informed data collection and analysis for phase B (administrative staff). Data were analysed iteratively, using thematic analysis. Results: In phase A, 48 clinicians were recruited (25 GPs, 15 nurses, seven HCAs, one pharmacist) and 16 administrative staff (11 Practice-Managers, five receptionists) in phase B. Respondents were positive about primary care's ability to effectively deliver infectious disease screening. However, we found current infectious disease screening lacks a standardised approach and many practices have no system for screening meaning migrant patients are not always receiving evidence-based care (i.e., NICE/ECDC/UKHSA screening guidelines). Barriers to screening were reported at patient, staff, and system-levels. Respondents reported poor implementation of existing screening initiatives (e.g., regional latent TB screening) citing overly complex pathways that required extensive administrative/clinical time and lacked financial/expert support. Solutions included patient/staff infectious disease champions, targeted training and specialist support, simplified care pathways for screening and management of positive results, and financial incentivisation. Participants responded positively to Health Catch-UP!, stating it would systematically integrate data and support clinical decision-making, increase knowledge, reduce missed screening opportunities, and normalisation of primary care-based infectious disease screening for migrants. Conclusions: Our results suggest that implementation of infectious disease screening in migrant populations is not comprehensively done in UK primary care. Primary health care professionals support the concept of innovative digital tools like Health Catch-UP! and that they could significantly improve disease detection and effective implementation of screening guidance but that they require robust testing and resourcing.

RESUMEN

Heart disease accounts for millions of deaths worldwide annually, representing a major public health concern. Large-scale heart disease screening can yield significant benefits both in terms of lives saved and economic costs. In this study, we introduce a novel algorithm that trains a patient-specific machine learning model, aligning with the real-world demands of extensive disease screening. Customization is achieved by concentrating on three key aspects: data processing, neural network architecture, and loss function formulation. Our approach integrates individual patient data to bolster model accuracy, ensuring dependable disease detection. We assessed our models using two prominent heart disease datasets: the Cleveland dataset and the UC Irvine (UCI) combination dataset. Our models showcased notable results, achieving accuracy and recall rates beyond 95 % for the Cleveland dataset and surpassing 97 % accuracy for the UCI dataset. Moreover, in terms of medical ethics and operability, our approach outperformed traditional, general-purpose machine learning algorithms. Our algorithm provides a powerful tool for large-scale disease screening and has the potential to save lives and reduce the economic burden of heart disease.

Asunto(s)

RESUMEN

Rheumatic heart disease (RHD) is a public health concern in many developing nations around the world. Early detection of latent or subclinical RHD can help in reversing mild lesions, retarding disease progression, reducing morbidity and mortality, and improving the quality of life of patients. Echocardiography is the gold-standard method for screening and confirming latent RHD cases. The rates and determinants of progression of latent RHD cases as assessed by echocardiography have been found to be variable through studies. Even though latent RHD has a slow rate of progression, the rate of progression of its subtype, 'definite' RHD, is substantial. A brief training of nonexpert operators on the use of handheld echocardiography with a simplified protocol is an important strategy to scale up the screening program to detect latent cases. Newer advancements in screening, such as deep-learning digital stethoscopes and telehealth services, have provided an opportunity to expand screening programs even in resource-constrained settings. Newer studies have established the efficacy and safety profile of secondary antibiotic prophylaxis in latent RHD. The concerned authorities in endemic regions of the world should work on improving the availability and accessibility of antibiotic prophylaxis.