Aesthetic Evaluation of Facial Scars in Patients Undergoing Surgery for Basal Cell Carcinoma: A Prospective Longitudinal Pilot Study and Validation of POSAS 2.0 in the Lithuanian Language.

Facial basal cell carcinoma (BCC) surgery enhances the quality of life (QoL) but leaves patients with inferior QoL, presumably caused by scarring, emphasizing the need to understand post-surgery aesthetic satisfaction. This study aimed to validate the Lithuanian version of the Patient and Observer Scar Assessment Scale (POSAS) 2.0 and utilise it to identify scar evaluation differences and correlations among POSAS scores and specific aesthetic facial regions, age, gender, surgery types, and short- and long-term QoL. Employing a prospective longitudinal design, 100 patients with facial scars after surgical BCC removal were enrolled. The validation phase confirmed the translated POSAS 2.0 psychometric properties, while the pilot phase used statistical analyses to compare scores among demographic and clinical groups and evaluate correlations between scar assessment and QoL. The findings indicate that the translated Lithuanian version of POSAS 2.0 exhibits good psychometric properties, revealing insights into aesthetic satisfaction with post-surgical facial scars and their impact on QoL. The Lithuanian version of the POSAS 2.0 was established as a valid instrument for measuring post-surgical linear scars. QoL with scar assessment statistically significantly correlates, 6 months after surgery, with worse scores, particularly notable among women, younger patients, and those with tumours in the cheek region.

Carotid Plaques and Hypertension as Risk Factors for Cardiovascular Disease and All-Cause Mortality in Middle-Aged Adults.

Background/Objectives: Both hypertension and carotid atherosclerosis are independent risk factors for cardiovascular disease. We aim to investigate the synergistic effects of hypertension and carotid plaques on cardiovascular events and all-cause mortality. Methods: A follow-up study was conducted at the Preventive Cardiology Department of Vilnius University Hospital Santaros Klinikos between 2012 and 2021. The study recruited participants aged 40-65 who did not have overt cardiovascular disease (CVD) and were part of the Lithuanian High Cardiovascular Risk primary preventive program. The study collected demographic and clinical data, including an ultrasound assessment of carotid plaque. Results: The participants were monitored for 4-10 years for CVD events and all-cause mortality. Among 6138 participants, 954 (16%) experienced CVD events. The presence of carotid plaque on both sides was significantly associated with CVD events, myocardial infarction, and all-cause mortality. However, the combination of hypertension and carotid plaque did not significantly increase the risk for CVD events or all-cause mortality. Conclusions: The risk of CVD events or all-cause mortality was not significantly increased by the combination of hypertension and carotid plaque. Cardiovascular events depend on the extent of atherosclerosis in the carotid arteries.

Epidemiological changes of acute respiratory infections in children: A single-center experience after COVID-19 lockdown.

BACKGROUND: Since the start of the COVID-19 pandemic, the epidemiology of acute respiratory infections (ARIs) has continually changed, making it difficult to predict. Our study aimed to evaluate epidemiological changes and clinical outcomes of ARIs in pediatric patients in the post-lockdown period. METHODS: A single-center retrospective cross-sectional study was performed in one of the largest pediatric emergency departments in Lithuania during two cold seasons-from October 1, 2021, to April 30, 2022 (Season I) and in the same period in 2022-2023 (Season II). Patients under 18 years of age who had been tested for COVID-19 were enrolled in the study. Additional data about other respiratory pathogens in the study group (specifically influenza A/B, respiratory syncytial virus (RSV) and group A Streptococcus (GAS)), were included. RESULTS: During both seasons of our study, 19,366 children were screened for COVID-19. Positive tests for COVID-19 decreased from 14.5% in Season I to 5.9% in Season II, while at the same time, the rates of other infections increased significantly: influenza from 17.5% to 27.1%, RSV from 8.8% to 27.6%, and GAS from 8.4% to 44%, respectively. In Season II, COVID-19 infection presented in fewer admissions to pediatric intensive care (0.8% vs. 3.7%, p<0.01) and there were no deaths, while influenza presented in a higher proportion of hospitalizations (10.5% vs. 6.1%, p<0.01) and there was one death. The proportion of RSV hospitalizations also increased in Season II (34.6% vs. 44.0%, p<0.01). CONCLUSIONS: The early post-lockdown period saw a decline of COVID-19 and re-emergence of influenza, RSV and GAS infections in children. In Season II, COVID-19 cases became milder contrary to influenza. RSV infection contributed significantly to hospitalizations for respiratory infections in children in both seasons, particularly in Season II. Coinfections were not associated with a more severe course of the disease.

Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) was a cause of concern in the healthcare system and increased the need for disease severity indicators. However, they still vary in use to evaluate in-hospital outcomes and severity. The National Early Warning Score (NEWS) is routinely used to evaluate patient health status at the hospital. Further research is needed to ensure if NEWS can be a good instrument for an overall health status assessment with or without additional information like laboratory tests, intensive care needs, and history of chronic diseases. OBJECTIVE: To evaluate if NEWS can be an indicator to measure COVID-19 patient status in-hospital. METHODS: We used the fully anonymized Electronic Health Records (EHR) characterizing patients admitted to the hospital with COVID-19. Data was obtained from Vilnius University Hospital Santaros Klinikos EHR system (SANTA-HIS) from 01-03-2020 to 31-12-2022. The study sample included 3875 patients. We created several statistical and machine learning models for discrimination between in-hospital death/discharge for evaluation NEWS as a disease severity measure for COVID-19 patients. In these models, two variable sets were considered: median NEWS and its combination with clinical parameters and medians of laboratory test results. Assessment of models' performance was based on the scoring metrics: accuracy, sensitivity, specificity, area under the ROC curve (AUC), and F1-score. RESULTS: Our analysis revealed that NEWS predictive ability for describing patient health status during the stay in the hospital can be increased by adding the patient's age at hospitalization, gender, clinical and laboratory variables (0.853 sensitivity, 0.992 specificity and F1-score - 0.859) in comparison with single NEWS (0.603, 0.995, 0.719, respectively). A comparison of different models showed that stepwise logistic regression was the best method for in-hospital mortality classification. Our findings suggest employing models like ours for advisory routine usage. CONCLUSION: Our model demonstrated incremental value for COVID-19 patient's status evaluation.