In the SARS-CoV-2 endemic phase, assessing the effectiveness of COVID-19 booster doses in children is essential for public health policy. This study evaluated the vaccine effectiveness (VE) of three doses (primary series plus booster) against severe outcomes, comparing the pandemic and endemic periods and children with and without comorbidities. We carried out a cohort study based on the population, utilizing comprehensive Brazilian data from individuals under 18 years of age with confirmed SARS-CoV-2 infection, spanning from February 2020 to June 2025. The primary exposure of interest was three or more doses of COVID-19 vaccines. The primary outcome of interest was COVID-19-related death. VE and the number needed to vaccinate (NNV) to prevent one death were estimated in a propensity score-matched cohort, with adjustments for confounders. Among 3,730,007 reported pediatric cases, 5472 (0.1%) died, 99% of whom did not receive a booster dose. During the pandemic, the VE against death was higher in children with comorbidities (92.7% [95% CI, 63.5-99.0]; NNV = 23 [19-30]) than in those without (68.2% [25.7-86.4]; NNV = 2000 [1111-9774]). During the endemic period, the VE against death remained high and was comparable between groups: 89.4% (29.8-98.7) and 75.8% (36.4-95.7) for children with and without comorbidities, respectively. Nevertheless, NNV levels were significantly lower in children with comorbidities, reflecting an increased risk at baseline. Although booster doses continue to offer substantial protection against fatal COVID-19 outcomes, the magnitude of this benefit is directly correlated with the baseline risk. Consequently, these findings support the implementation of risk-based prioritization strategies in public health decision-making for children.

Pediatric patients with SARS-CoV-2 infection are at an increased risk of severe disease and adverse outcomes. Nevertheless, comprehensive data on COVID-19 vaccine effectiveness (VE) in children with diabetes during the post-pandemic period remain limited. This study assessed the VE against severe COVID-19 outcomes during both the pandemic and post-pandemic phases in children with and without diabetes mellitus (DM). A cohort study based on population data was carried out, including all patients under 18 years of age with symptomatic SARS-CoV-2 infection as registered in the Brazilian national surveillance systems from February 2020 to June 2025. The main outcomes were hospitalization due to COVID-19 and severe illness, which included admission to the intensive care unit (ICU), need for invasive ventilation, and death. Utilizing a propensity score-matched cohort, we estimated the VE and the number needed to vaccinate (NNV) for a booster dose against these outcomes by comparing vaccinated and unvaccinated individuals, employing conditional logistic regression adjusted for confounding variables. The cohort comprised 3,730,007 pediatric patients with COVID-19, of whom 7675 (0.2%) had DM. At baseline, children with DM exhibited a significantly higher prevalence of hospitalization (11.2% vs. 2.0%), severe COVID-19 (6.4% vs. 0.6%), and mortality (1.9% vs. 0.1%) than those without DM (all p < 0.001). During the pandemic period, the adjusted VE was consistently higher in children with DM. Against severe disease, the VE was 72.8% (95% CI: 12.3-93.2) in the DM cohort compared with 45.7% (28.1-59.0) in the non-DM cohort. This increased effectiveness corresponded to a more favorable NNV; the NNV to prevent one severe case was 24 (95% CI: 12-232) for children with DM versus 243 (168-440) for those without DM. In the post-pandemic period, the VE remained significantly higher in the DM cohort. Against severe disease, the VE was 76.2% (11.5-93.5) for children with DM and 52.9% (32.7-67.1) for those without. The NNV to prevent one severe case was consistently lower in the DM cohort (8 vs. 591). In conclusion, a complete vaccination regimen, including a booster dose, substantially mitigated severe COVID-19 outcomes in children with DM in the pandemic and post-pandemic periods.

Background/Objectives: Individuals with alcohol use disorder (AUD) and tobacco use disorder (TUD) are at increased risk for severe COVID-19 outcomes. However, real-world evidence on vaccine effectiveness (VE) in these populations remains limited, particularly in low- and middle-income countries. This study aimed to evaluate the effectiveness of three or more COVID-19 vaccine doses against mortality in hospitalized patients with AUD and TUD in Brazil. Methods: This retrospective cohort study used data from the SIVEP Gripe database, a national surveillance system of hospitalized COVID-19 cases in Brazil. The study included adults aged ≥18 years with confirmed SARS-CoV 2 infection between February 2020 and June 2025. The intervention was defined as receipt of three or more vaccine doses (fully vaccinated) versus no doses (unvaccinated). Propensity score matching was performed separately for AUD and TUD cohorts. Vaccine effectiveness was estimated using McNemar’s test for paired samples, and the average treatment effect (ATE) and number needed to vaccinate (NNV) were calculated. Results: Among 2,184,723 hospitalized patients, 12,115 had AUD and 45,679 had TUD. After matching, VE against mortality was 42% (95% CI: 27.5–53.5) in the AUD group and 52.6% (95% CI: 46.5–58.1) in the TUD group, compared to 58.5% and 58.9% in their respective non-exposed counterparts. The ATE was consistent across groups (approximately −0.12), and the NNV to prevent one death was 8 (95% CI: 6–15 for AUD; 7–12 for TUD). Conclusions: Although VE was attenuated in individuals with AUD and TUD compared to the general population, the absolute benefit of vaccination remained substantial.

In the post-pandemic era, identifying children who are most susceptible to severe illness and COVID-19-related mortality is essential for guiding public health policies. This study examined the risk factors for COVID-19-related severe illness and mortality from 2023 to mid-2025. We conducted a population-based cohort study using nationwide Brazilian data from patients aged <18 years with laboratory-confirmed SARS-CoV-2 infection between January 2023 and June 2025. The primary outcomes were COVID-19-related severity and death. Separate binary multivariable logistic regression models were developed for each of the outcomes. Among 465,689 children, 1.3% (n = 5963) developed severe illness, and 0.18% (n = 847) died. Factors associated with an increased risk of severe illness included age < 2 years, presence of comorbidities, Indigenous ethnicity, and lack of vaccination. Neurological disorders conferred the highest risk among the clinical conditions (adjusted odds ratio [aOR] = 34.1; 95% CI: 27.9–41.8). Regional differences were also observed; the North and Northeast regions showed higher mortality (aOR = 2.3; 95% CI: 1.8–3.0) than the Central-West region. Compared with White ethnicity, non-White ethnicities had higher mortality: Indigenous (aOR = 23.5; 95% CI: 13.5–39.3), Black (aOR = 1.95; 95% CI: 1.29–2.92), and Brown (aOR = 1.43; 95% CI: 1.18–1.73) ethnicities. Lack of any vaccine dose was associated with a significantly increased risk of severe illness (aOR = 1.39; 95% CI: 1.15–1.67. p < 0.001) and death (aOR = 2.1; 95% CI: 1.3–3.5; p < 0.001). In the post-pandemic era, younger age, comorbidities, sociodemographic disparities, and lack of vaccination were associated with an increased risk of severe illness and COVID-19-related death in the pediatric population.

OBJECTIVE:This study analyzed the role of vaccination in preventing COVID-19-related mortality in patients with schizophrenia. METHODS:This retrospective cohort study analyzed data from the Influenza Epidemiological Surveillance Information System (Sistema de Informação da Vigilância Epidemiológica da Gripe [SIVEP-Gripe]) database, focusing on patients aged = 18 years with laboratory-confirmed COVID-19 between February 2020 and February 2023. The primary exposure was schizophrenia. The primary outcome of interest was the role of vaccines in preventing COVID-19-associated mortality. Statistical analysis included multiple binary logistic regressions to determine the impact of schizophrenia on mortality and to compare vaccine protection between cohorts. RESULTS:The cohort included 2,131,089 patients, 3,516 (0.2%) of whom had schizophrenia. After adjusting for potential confounders, patients with schizophrenia presented a significantly higher risk of severe disease (OR = 1.59, 95%CI 1.39-1.81) and mortality (OR = 1.65, 95%CI 1.45-1.87). After the booster dose, protection against mortality was estimated at 67.7% (95%CI 66.5-68.7) in the non-schizophrenia cohort and 62.4% (95%CI 44.1-74.6) in the schizophrenia cohort. Mortality rate differences of approximately 20% and 10% were observed between boosted and non-vaccinated individuals among the schizophrenia and non-schizophrenia cohorts, respectively. Consequently, five patients (95%CI 4-8) with schizophrenia and 10 patients (95%CI 9-11) in the general population would need to receive a booster dose to prevent one fatality. CONCLUSIONS:Our results suggest that vaccination provided similar protection against COVID-19-related mortality in individuals with and without schizophrenia. However, the magnitude of the intervention effect was double for individuals with schizophrenia due to their higher baseline risk.

Background To investigate predictive factors associated with neonatal mortality in infants with congenital anomalies of the kidney and urinary tract (CAKUT).Methods This study included a cohort of neonates with CAKUT born at a tertiary hospital between 1996 and 2021. Controls were matched with CAKUT cases by sex, time, and place of birth at a ratio of approximately 2:1. The covariates included in the analysis were sex, gestational age, birth weight, neonatal classification, and birth order. CAKUT was categorized into four phenotypes: urinary tract dilatation, lower urinary tract obstruction (LUTO), cystic diseases, and agenesis/hypodysplasia. The primary outcome was neonatal mortality. Survival analysis was performed using the Cox proportional hazards model.Results 857 cases and 1,755 controls were included in the analysis. The overall early mortality rate was 7.2%. After controlling for confounding factors, CAKUT cases exhibited a higher risk of early mortality than controls (hazard ratio [HR], 25.1; 95%CI, 14.0–45.2). The following covariates were independently associated with early mortality: prematurity (HR, 1.7; 95%CI, 1.2–2.5), LBW (HR, 2.4; 95%CI, 1.6–2.5), VLBW (HR, 2.9; 95%CI, 1.7–1.1), oligohydramnios (HR, 3.2; 95%CI, 2.2–4.8), cystic diseases (HR, 3.8; 95%CI, 2.3–6.4), LUTO (HR, 5.1; 95%CI, 3.0–8.5), kidney agenesis/hypodysplasia (HR, 5.1; 95%CI, 2.9–8.7), and extra-renal malformations (HR, 2.6; 95% CI, 1.7–3.9).Conclusions Our findings indicate that CAKUT was associated with an elevated early mortality rate compared with controls. Factors including prematurity, LBW, oligohydramnios, extra-renal malformations, and specific CAKUT phenotypes with kidney involvement were associated with increased mortality risk.

To investigate the real-world effectiveness of COVID-19 vaccines in a large cohort of patients with diabetes mellitus (DM), we analyzed all >18-year-old patients with COVID-19 registered in a Brazilian nationwide surveillance database between February 2020 and February 2023. The primary outcome of interest was vaccine effectiveness against death, evaluated using multivariate logistic regression models. Among the 2,131,089 patients registered in the SIVEP-Gripe, 482,677 (22.6%) had DM. After adjusting for covariates, patients with DM had a higher risk of death than those without comorbidities (adjusted odds ratio [aOR] = 1.43, 95% CI, 1.39-1.47). For patients without comorbidities (72.7%, 95% CI, 70.5-74.7) and those with DM (73.4%, 95% CI, 68.2-76.7), vaccine effectiveness was similar after the booster dose. However, it was reduced in patients with DM associated with other comorbidities (60.5%; 95% CI, 57.5-63.2). The strongest factor associated with booster failure was the omicron variant (aOR = 27.8, 95% CI, 19.9-40.1). Our study revealed that COVID-19 vaccines provided robust protection against death in individuals with DM. However, our findings underscore the need to update vaccines and develop tailored strategies for individuals with diabetes, especially those with additional underlying conditions.

Prediction models have been used in several areas, especially in health science. In many situations, they can serve as a tool for clinical support, helping define risk groups by severity and assisting decision-making concerning the most appropriate treatment. A typical case is, for instance, to predict the risk of a patient dying in a specific window of time based on variables (clinical markers) recorded at the beginning of the study and over the follow-up period. This study was motivated by a clinical demand on building a death risk score for patients with Chagas disease from the SaMi-Trop prospective cohort project. Patients living in the state of Minas Gerais, Brazil, were followed for two years, and based on baseline information, a risk score was built to predict 2-year mortality. The follow-up study allowed the nature of the death risk to be dynamic. That is, clinical markers change over time, and for the two-year survivors, it is necessary to update the risk score. In this work, we compare four approaches to building dynamic scores: two naive ones that are based on updating the baseline score, another based on a new landmark, and the last one considering a joint modeling approach. Some simulation results in the literature seemed to favor joint modeling. In this paper, we compare the dynamic prediction approaches based on the Chagas disease short follow-up cohort. The predictive capacity of each risk score is assessed and compared using discrimination and calibration measures. The study results suggest that new baseline approaches (naive 1 and landmark) have better discrimination capacity and the other ones (naive 2 and joint modeling) have better calibration capacity.

OBJECTIVE:This study aimed to investigate the clinical outcomes and mortality risk factors associated with alcohol use disorder (AUD) in hospitalized COVID-19 patients. METHODS:We analyzed a national database containing information on the clinical and sociodemographic aspects of patients hospitalized with severe acute respiratory syndrome between February 2020 and February 2023 in Brazil, including those aged > 18 years with laboratory-confirmed COVID-19. The primary exposure of interest was a history of AUD before admission and the primary outcome was in-hospital mortality. RESULTS:Among the 2,124,285 patients, 11,433 (0.53 %) had AUD. The in-hospital mortality rate was higher in the patients with AUD (46.2%) than in those without AUD (31.9%). After adjusting for confounding covariates, individuals with AUD had twice the risk of death (Odds Ratio [OR]= 1.94, 95% confidence interval [CI] 1.85-2.03) compared with non-AUD patients. Among individuals with AUD, the covariates independently associated with the primary outcome were age > 60 years, male sex, hospitalization in the Central-West, Northeast and North regions, symptoms of dyspnea and reduced oxygen saturation at admission, presence of comorbidities, and year of admission. CONCLUSION:In this population-based study, we found that patients with AUD had twice the risk of fatal outcomes than those without AUD.

Introdução: Anomalias congênitas dos rins e do trato urinário (CAKUT) são malformações muito frequentes que afetam a sobrevida neonatal. Este estudo investigou fatores preditivos de mortalidade neonatal em recém-nascidos com CAKUT em uma coorte hospitalar ao longo de 25 anos. Objetivo: Investigar fatores preditivos de mortalidade neonatal em recém-nascidos com CAKUT. Método: Foram avaliados neonatos com CAKUT e controles pareados com os casos de CAKUT em uma proporção em torno de 2:1, nascidos entre 1996 e 2021. As covariáveis analisadas incluíram sexo, idade gestacional, peso ao nascer, classificação neonatal e ordem de nascimento. O desfecho primário foi mortalidade neonatal. Resultados: Foram analisados 857 casos e 1.755 controles com taxa geral de mortalidade neonatal de 7,2%. Controlando fatores de confusão, os casos de CAKUT apresentaram mortalidade 25 vezes maior do que os controles (razão de risco=25,1; IC95%, 14,0–45,2). As covariáveis independentemente associadas à mortalidade neonatal foram: prematuridade, baixo peso e muito baixo peso ao nascer, oligodrâmnio, doenças císticas, obstrução do trato urinário inferior, agenesia/hipodisplasia renal e malformações extrarrenais. Conclusão: A presença de CAKUT foi um fator preditivo independente da maior taxa de mortalidade. Prematuridade, baixo peso ao nascer, oligoidrâmnio, malformações extrarrenais e fenótipos CAKUT com envolvimento renal foram também associados a maior risco de mortalidade.

The COVID-19 pandemic has catalyzed the application of advanced digital technologies such as artificial intelligence (AI) to predict mortality in adult patients. However, the development of machine learning (ML) models for predicting outcomes in children and adolescents with COVID-19 remains limited. This study aimed to evaluate the performance of multiple machine learning models in forecasting mortality among hospitalized pediatric COVID-19 patients. In this cohort study, we used the SIVEP-Gripe dataset, a public resource maintained by the Ministry of Health, to track severe acute respiratory syndrome (SARS) in Brazil. To create subsets for training and testing the machine learning (ML) models, we divided the primary dataset into three parts. Using these subsets, we developed and trained 12 ML algorithms to predict the outcomes. We assessed the performance of these models using various metrics such as accuracy, precision, sensitivity, recall, and area under the receiver operating characteristic curve (AUC). Among the 37 variables examined, 24 were found to be potential indicators of mortality, as determined by the chi-square test of independence. The Logistic Regression (LR) algorithm achieved the highest performance, with an accuracy of 92.5% and an AUC of 80.1%, on the optimized dataset. Gradient boosting classifier (GBC) and AdaBoost (ADA), closely followed the LR algorithm, producing similar results. Our study also revealed that baseline reduced oxygen saturation, presence of comorbidities, and older age were the most relevant factors in predicting mortality in children and adolescents hospitalized with SARS-CoV-2 infection. The use of ML models can be an asset in making clinical decisions and implementing evidence-based patient management strategies, which can enhance patient outcomes and overall quality of medical care. LR, GBC, and ADA models have demonstrated efficiency in accurately predicting mortality in COVID-19 pediatric patients.

Background Illicit substance use (ISU) may be a potential predisposing factor for severe COVID-19 outcomes. Objective To conduct a propensity score-matching analysis to assess and compare the mortality rate of individuals who reported ISU among a sizable cohort of hospitalized COVID-19 patients in Brazil. Methods This population-based retrospective cohort study analyzed a nationwide Brazilian database of patients hospitalized for COVID-19. Eligible patients were aged >18 years and tested positive for SARS-CoV-2 infection. The primary exposure of interest was ISU, defined as substances prohibited under Brazilian law, primarily marijuana, cocaine, and crack. Statistical analysis was performed using t-tests, chi-square tests, the Propensity Score Matching (PSM) technique to create a balanced comparison group, and the McNemar test for paired samples to assess mortality risk among patients with ISU. Results In a cohort of 2,124,285 patients, 1,845 had ISU. The mortality rate in the ISU group was slightly higher than that in the non-ISU group (33% vs. 32%). After PSM, we found a higher odds ratio for death in patients with ISU (OR 2.18; 95% CI 1.85-2.57; p < 0.001). Conclusion Our study highlights a significant association between ISU and an increased mortality risk in COVID-19 patients.

The purpose of the present study was to evaluate permanent teeth with post-traumatic transversal root fractures, for their initial healing modality, the effect of candidate predictors and their long-term prognosis. A retrospective longitudinal clinical study was conducted to evaluate records from patients bearing transversal root fractures in permanent teeth in order to radiographically assess short-term healing and non-healing events in the fracture line, their prognostic factors and their relationship with long term outcomes. The inter-fragmentary tissues were classified as healing: hard tissue (HT), connective tissue (CT) or connective tissue and bone (CT + B) and non-healing: interposition of granulation tissue (GT). A competing risk survival analysis was conducted to estimate the hazards of healing and non-healing events in the short-term and the effect of demographic, clinical, and treatment variables was assessed using the subdistribution regression model (Fine Gray). Radiographic findings showed 61.4

Objective: To determine clinical outcomes and mortality risk factors related to mental disorders in a cohort of hospitalized patients with Covid-19 in Brazil. Methods: This retrospective cohort study used a Brazilian database called the Sistema de Vigilancia Epidemiologica da Gripe (Influenza Epidemiological Surveillance System) to analyze patients aged X 18 years who were hospitalized with Covid-19 between 2020 and 2022. The exposure of interest was mental disorders (anxiety, depression, schizophrenia, and bipolar disorder) identified through self- report. The primary outcome was in-hospital mortality. Covariates included demographic and clinical characteristics. Descriptive statistics, t-tests, chi-square tests, and binary logistic regression were used to analyze the data. Results: A cohort of 2,124,285 patients was included in the analysis, with 23,246 individuals (1.1%) self-reporting mental disorders, of which depression was the most prevalent (52.3%). The mortality rate of patients with mental disorders was 30.8%. Age, sex, region, dyspnea, low oxygen saturation, and comorbidities were associated with a higher mortality risk, as was schizophrenia (adjusted OR: 1.68; 95%CI 1.54-1.81). Conclusions: Individuals with schizophrenia had a greater likelihood of Covid-19-related death than those without mental health conditions. These findings underscore the significant effect of serious mental disorders on Covid-19 mortality.

BACKGROUND:Oral health is recognized as integral to general health and impaired dentition status may affect physical performance among older adults. This study evaluated the longitudinal association between clinical and self-reported oral health measures and physical performance (outcome) in Brazilian older adults. METHODS:This was a longitudinal study that used data from the second (year 2006), third (year 2010) and fourth (year 2015) waves of the Health Well-being and Aging Study conducted in Brazil. Physical performance, evaluated using the Short Physical Performance Battery (SPPB), was the dependent variable. Independent variables of interest were the number of teeth, presence of periodontal pocket, use of dental prostheses, and poor perceived oral health. The association between oral health measures and physical function was analyzed using generalized estimating equations with an ordinal regression model. RESULTS:In the total sample, every additional tooth was associated with a greater chance of achieving a higher score on the SPPB test. Individuals wearing dental prostheses had higher chances of having higher scores than those not wearing them. In the analyses for the dentate sample, the presence of a periodontal pocket was not associated with SPPB and the increase in the number of teeth increased the chance of achieving a higher score. CONCLUSION:A greater number of teeth, and using dentures, were associated with higher physical performance. Periodontal disease was not associated with the outcome.

BACKGROUND AND OBJECTIVES:Understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with other respiratory viruses is crucial for developing effective public health strategies in the postpandemic era. This study aimed to compare the outcomes of SARS-CoV-2 and seasonal viruses in children and adolescents hospitalized with severe acute respiratory infection (SARI). METHODS:This population-based, retrospective cohort study included children and adolescents hospitalized with SARI from February 2020 to February 2023 in Brazil. The main exposure of interest was viral etiology. The primary outcome was in-hospital mortality. Competing risk analysis was used to account for time dependency and competing events. RESULTS:A total of 235 829 patients had available results of the viral tests, with SARS-CoV-2 predominance. According to the competing-risk survival analysis, the estimated probability of a fatal outcome at 30 days of hospitalization according to the viral strain was 6.5%, 3.4%, 2.9%, 2.3%, 2.1%, and 1.8%, for SARS-CoV-2, coinfection, adenovirus, influenza, other viruses, and respiratory syncytial virus, respectively. Individuals with a positive test for SARS-CoV-2 had hazard of death 3 times higher than subjects with a negative test (hazard ratio, 3.3; 95% confidence interval, 3.1-3.5). After adjustment by the competing-risk multivariable analysis, admission in Northeast and North regions, oxygen saturation <95%, and the presence of comorbidities were risk factors for death in all viral strains. CONCLUSIONS:SARS-CoV-2 infection had the highest hazard of in-hospital mortality in this pediatric cohort hospitalized with SARI. Regardless of viral etiology, the presence of underlying medical conditions was a risk factor for death.

Objective To provide a comprehensive overview of the epidemiologic characteristics, outcomes, and risk factors of COVID-19-related deaths in children and adolescents in Brazil. Study design We conducted a population-based, retrospective cohort study that included all patients aged <18 years with laboratory-confirmed, symptomatic SARS-CoV-2 infection as registered in official Brazilian national surveillance systems for COVID-19 between February 2020 and February 2023. The primary outcome was COVID-19-related deaths. Odds ratios (ORs) of risk factors associated with death were estimated using multivariable logistic regression. Results Over a three-year period, 2,855,704 pediatric patients with symptomatic SARS-CoV-2 infection were registered in Brazil. Of these, 59,179 (2.1%) were hospitalized, 13,844 (0.48%) were admitted to the intensive care unit, and 4,943 (0.17%) received mechanical ventilation. A total of 4,740 (0.17%) patients had fatal outcomes. The case fatality rate increased to 7.9% among patients who required hospitalization; 2,102 (44.3%) patients who died did not receive advanced critical support. Notably, two (65%, 95% CI 58-71) or three doses (86%, 95% CI 81-89) of the vaccine provided strong protection against death. The following adjusted covariates were significantly associated with increased odds of death: age (0-4 and 11-17 years), ethnicity (Brown and Indigenous), region (Northeast or North), dyspnea, nosocomial infection, and comorbidities. Conversely, living in the South or Central-West regions, admission in the later period of the pandemic, and receiving a vaccine were all associated with protection against death. Conclusion Our findings suggest that a complex interplay between individual factors and social inequities has shaped the impact of COVID-19 on Brazilian children and adolescents.

A higher incidence of primary congenital hypothyroidism (CH) has been related to increased sensitivity in neonatal screening tests. The benefit of treatment in mild cases remains a topic of debate. We evaluated the impact of reducing the blood-spot TSH cut-off (b-TSH) from 10 (Group 2) to 6 mIU/L (Group 1) in a public neonatal screening program. During the study period, 40% of 123 newborns with CH (n = 162,729; incidence = 1:1323) had b-TSH between 6 and 10 mIU/L. Group 1 patients had fewer clinical signs (p = 0.02), lower serum TSH (p < 0.01), and higher free T4 (p < 0.01) compared to those in Group 2 at diagnosis. Reducing the b-TSH cut-off from 10 to 6 mIU/L increased screening sensitivity, allowing a third of diagnoses, mainly mild cases, not being missed. However, when evaluating the performances of b-TSH cut-offs (6, 7, 8, 9, and 10 mIU/L), the lower values were associated with low positive predictive values (PPVs) and unacceptable increased recall rates (0.57%) for a public health care program. A proposed strategy is to adopt a higher b-TSH cut-off in the first sample and a lower one in the subsequent samples from the same child, which yields a greater number of diagnoses with an acceptable PPV.

To describe radiographic features, clinical signs and symptoms, and chronological patterns of post-traumatic transient apical breakdown (TAB) in luxated permanent teeth. Records from 56 patients treated at the Dental Trauma Clinic of the School of Dentistry of the Federal University of Minas Gerais from 1993 to 2024 were accessed to collect demographic, clinical, and imaging features of 89 teeth that presented with radiographic signs of TAB after traumatic dental injury (TDI). Kaplan–Meier curves were built to illustrate the time elapsed between trauma until TAB onset and resolution for the whole sample and for each one of the TAB patterns. A Cox regression was used to explore the effect of clinical covariates in both events. Patients’ mean age at the time of trauma was 17.7 ± 6.6 years (range 9.1 to 39.7 years), with most being male (59.6