Fostering Digital Health in Universities: An Experience of the First Junior Scientific Committee of the Brazilian Congress of Health Informatics.

OBJECTIVES: Digital health (DH) is a revolution driven by digital technologies to improve health. Despite the importance of DH, curricular updates in healthcare university programs are scarce, and DH remains undervalued. Therefore, this report describes the first Junior Scientific Committee (JSC) focusing on DH at a nationwide congress, with the aim of affirming its importance for promoting DH in universities. METHODS: The scientific committee of the Brazilian Congress of Health Informatics (CBIS) extended invitations to students engaged in health-related fields, who were tasked with organizing a warm-up event and a 4-hour session at CBIS. Additionally, they were encouraged to take an active role in a workshop alongside distinguished experts to map out the current state of DH in Brazil. RESULTS: The warm-up event focused on the topic "Artificial intelligence in healthcare: is a new concept of health about to arise?" and featured remote discussions by three professionals from diverse disciplines. At CBIS, the JSC's inaugural presentation concentrated on delineating the present state of DH education in Brazil, while the second presentation offered strategies to advance DH, incorporating viewpoints from within and beyond the academic sphere. During the workshop, participants deliberated on the most crucial competencies for future professionals in the DH domain. CONCLUSIONS: Forming a JSC proved to be a valuable tool to foster DH, particularly due to the valuable interactions it facilitated between esteemed professionals and students. It also supports the cultivation of leadership skills in DH, a field that has not yet received the recognition it deserves.

Gestational age assessed by optical skin reflection in low-birth-weight newborns: Applications in classification at birth.

Introduction: A new medical device was previously developed to estimate gestational age (GA) at birth by processing a machine learning algorithm on the light scatter signal acquired on the newborn's skin. The study aims to validate GA calculated by the new device (test), comparing the result with the best available GA in newborns with low birth weight (LBW). Methods: We conducted a multicenter, non-randomized, and single-blinded clinical trial in three urban referral centers for perinatal care in Brazil and Mozambique. LBW newborns with a GA over 24 weeks and weighing between 500 and 2,500 g were recruited in the first 24 h of life. All pregnancies had a GA calculated by obstetric ultrasound before 24 weeks or by reliable last menstrual period (LMP). The primary endpoint was the agreement between the GA calculated by the new device (test) and the best available clinical GA, with 95% confidence limits. In addition, we assessed the accuracy of using the test in the classification of preterm and SGA. Prematurity was childbirth before 37 gestational weeks. The growth standard curve was Intergrowth-21st, with the 10th percentile being the limit for classifying SGA. Results: Among 305 evaluated newborns, 234 (76.7%) were premature, and 139 (45.6%) were SGA. The intraclass correlation coefficient between GA by the test and reference GA was 0.829 (95% CI: 0.785-0.863). However, the new device (test) underestimated the reference GA by an average of 2.8 days (95% limits of agreement: -40.6 to 31.2 days). Its use in classifying preterm or term newborns revealed an accuracy of 78.4% (95% CI: 73.3-81.6), with high sensitivity (96.2%; 95% CI: 92.8-98.2). The accuracy of classifying SGA newborns using GA calculated by the test was 62.3% (95% CI: 56.6-67.8). Discussion: The new device (test) was able to assess GA at birth in LBW newborns, with a high agreement with the best available GA as a reference. The GA estimated by the device (test), when used to classify newborns on the first day of life, was useful in identifying premature infants but not when applied to identify SGA infants, considering current algohrithm. Nonetheless, the new device (test) has the potential to provide important information in places where the GA is unknown or inaccurate.

Congenital Solitary Functioning Kidney: A Review.

BACKGROUND: Solitary functioning kidney (SFK) is a subgroup of the Congenital Anomalies of the Kidneys and Urinary Tract (CAKUT). Although the prognosis of these patients was considered good in the past, numerous studies have shown different levels of kidney damage associated with this condition. Serum creatinine measurement is still the most used marker to assess renal function, even though the limitations are widely known. OBJECTIVE: The present review aims to summarize and update the scientific literature on congenital SFK, discussing its pathophysiology, diagnosis, complications, prognosis, role of novel urinary biomarkers, treatment, and follow-up. RESULTS: The natural history of congenital SFK is still an unresolved issue due to several factors. Although it has not yet been proven in humans, Brenner's hyperfiltration hypothesis is the most concrete theory to explain the poor renal outcomes of patients born with one functioning kidney. The search for novel urinary biomarkers capable of assessing renal function and predicting renal outcomes has already started, but there are still few studies on this specific population. Among the most studied markers, Cystatin C, EGF and NGAL have shown potential usefulness for the follow-up of these patients. The treatment still relies on the search for kidney injury and general renoprotective measures. CONCLUSION: Further research with a longer follow-up duration is needed to better understand the natural course of congenital SFK and the role of novel urinary biomarkers in this specific population. Thus, it will be possible to improve the prognosis of these patients.

Progression of Mitral Regurgitation in Rheumatic Valve Disease: Role of Left Atrial Remodeling.

Introduction: Mitral regurgitation (MR) is the most common valve abnormality in rheumatic heart disease (RHD) often associated with stenosis. Although the mechanism by which MR develops in RHD is primary, longstanding volume overload with left atrial (LA) remodeling may trigger the development of secondary MR, which can impact on the overall progression of MR. This study is aimed to assess the incidence and predictors of MR progression in patients with RHD. Methods: Consecutive RHD patients with non-severe MR associated with any degree of mitral stenosis were selected. The primary endpoint was a progression of MR, which was defined as an increase of one grade in MR severity from baseline to the last follow-up echocardiogram. The risk of MR progression was estimated accounting for competing risks. Results: The study included 539 patients, age of 46.2 ± 12 years and 83% were women. At a mean follow-up time of 4.2 years (interquartile range [IQR]: 1.2-6.9 years), 54 patients (10%) displayed MR progression with an overall incidence of 2.4 per 100 patient-years. Predictors of MR progression by the Cox model were age (adjusted hazard ratio [HR] 1.541, 95% CI 1.222-1.944), and LA volume (HR 1.137, 95% CI 1.054-1.226). By considering competing risk analysis, the direction of the association was similar for the rate (Cox model) and incidence (Fine-Gray model) of MR progression. In the model with LA volume, atrial fibrillation (AF) was no longer a predictor of MR progression. In the subgroup of patients in sinus rhythm, 59 had an onset of AF during follow-up, which was associated with progression of MR (HR 2.682; 95% CI 1.133-6.350). Conclusions: In RHD patients with a full spectrum of MR severity, progression of MR occurs over time is predicted by age and LA volume. LA enlargement may play a role in the link between primary MR and secondary MR in patients with RHD.