The Increase in Childhood Obesity and Its Association with Hypertension during Pandemics.

There has been a major ongoing health impact of the COVID-19 pandemic on children's lives, including lifestyle and overall health. Enforcement of prevention measures, such as school closures and social distancing, has significantly affected children's daily routines and activities. This perspective manuscript aims to explore the rise in childhood obesity and its association with hypertension during pandemics. The COVID-19 pandemic has led to significant disruptions in children's routines, including reduced physical activity, increased sedentary behavior, and changes in dietary patterns. These factors, coupled with the psychological impact of the pandemic, have contributed to an alarming increase in childhood obesity rates. This paper has highlighted the concerning increase in childhood obesity and hypertension during pandemics. The disruptions caused by the COVID-19 pandemic, including reduced physical activity, increased sedentary behaviors, and changes in dietary patterns, have contributed to the rise in these health conditions. It is crucial to recognize the long-term consequences of childhood obesity and hypertension and the urgent need for a comprehensive approach to address them.

Evaluating Serum Calcium and Magnesium Levels as Predictive Biomarkers for Tuberculosis and COVID-19 Severity: A Romanian Prospective Study.

In Romania, the highest incidence of tuberculosis (TB) within the European Union was reported in 2020, highlighting a significant health challenge. This is compounded by the COVID-19 pandemic, which has severely impacted healthcare services, including TB management. Both TB and COVID-19, diseases with considerable morbidity and mortality, have shown potential links to electrolyte imbalances. We conducted a prospective study at Victor Babes Hospital, Romania on 146 patients (74 with TB, 72 with COVID-19) between December 2021 and July 2023. This study assessed correlations between disease severity and serum calcium and magnesium levels, as well as pulmonary function. Adult patients with confirmed diagnoses and comprehensive medical records were included, excluding those with chronic respiratory diseases or unrelated electrolyte imbalances. Statistical analysis utilized the Kruskal-Wallis test and Dunn's procedure for non-normally distributed data. Low serum calcium and magnesium levels were significantly correlated with severe forms of TB and COVID-19, suggesting their potential as biomarkers of disease progression. Patients with more severe TB (i.e., multiple cavities) exhibited significantly lower serum calcium (p = 0.0049) and magnesium levels (p = 0.0004). ROC analysis revealed high AUC values for serum calcium and serum magnesium in predicting COVID-19 severity, indicating their potential as biomarkers. This study demonstrates a significant association between lower serum calcium and magnesium levels and increased TB severity. Similarly, these electrolytes show promise as predictive markers for COVID-19 severity. These findings could serve as biomarkers for predicting the severity of TB and COVID-19, offering potential utility in clinical decision-making.

Post-COVID-19 Syndrome Based on Disease Form and Associated Comorbidities.

(1) Background: SARS-CoV-2 has infected more than 97 million people worldwide and caused the death of more than 6 million. (2) Methods: Between 1 October and 31 December 2020, 764 patients diagnosed with SARS-CoV-2 infection were selected based on RT-PCR test results. The following parameters were noted: age, gender, origin, days of hospitalization, COVID-19 experienced form, radiographic imaging features, associated comorbidities, and recommended treatment at discharge. (3) Results: The mean age at the time of COVID-19 infection was 55.2 years for men and 55.3 years for women. There was a similar age distribution among patients, regardless of gender. There was a substantial difference between the average lengths of hospitalization and those with residual symptoms-most patients who reported symptoms after discharge had been admitted with moderately severe forms of illness. Fatigue was the main remaining symptom (36%). (4) Conclusions: In conclusion, to clarify the impact of SARS-CoV-2 infection on patients in the long term, further studies are needed to investigate the elements assessed. Well-designed recovery programs will be needed to effectively manage these patients, with multidisciplinary collaboration and a team of professionals involved in all aspects of post-COVID patient health.

COVID-19 and Artificial Intelligence: An Approach to Forecast the Severity of Diagnosis.

(1) Background: The new SARS-COV-2 pandemic overwhelmed intensive care units, clinicians, and radiologists, so the development of methods to forecast the diagnosis' severity became a necessity and a helpful tool. (2) Methods: In this paper, we proposed an artificial intelligence-based multimodal approach to forecast the future diagnosis' severity of patients with laboratory-confirmed cases of SARS-CoV-2 infection. At hospital admission, we collected 46 clinical and biological variables with chest X-ray scans from 475 COVID-19 positively tested patients. An ensemble of machine learning algorithms (AI-Score) was developed to predict the future severity score as mild, moderate, and severe for COVID-19-infected patients. Additionally, a deep learning module (CXR-Score) was developed to automatically classify the chest X-ray images and integrate them into AI-Score. (3) Results: The AI-Score predicted the COVID-19 diagnosis' severity on the testing/control dataset (95 patients) with an average accuracy of 98.59%, average specificity of 98.97%, and average sensitivity of 97.93%. The CXR-Score module graded the severity of chest X-ray images with an average accuracy of 99.08% on the testing/control dataset (95 chest X-ray images). (4) Conclusions: Our study demonstrated that the deep learning methods based on the integration of clinical and biological data with chest X-ray images accurately predicted the COVID-19 severity score of positive-tested patients.

The clinical-morphological profile of tuberculous pleurisies - our experience in relation to literature data.

AIM: The authors made a morphological evaluation of pleural tissue fragments from patients hospitalized in Thoracic Surgery Department of the Emergency County Hospital of Craiova, Romania, over a period of 26 years, diagnosed with tuberculous lesions in the Pathology Department of the same Hospital. PATIENTS, MATERIALS AND METHODS: The studied material consisted of pleural tissue samples taken by biopsy or surgical excision from 39 cases coming out of 841 patients investigated in the above-mentioned period of time and diagnosed from histological point of view with tuberculosis (TB). Granuloma cell population was assessed using immunohistochemical method. For diagnostic confirmation, Ziehl-Neelsen staining has been used as a rule but, in some cases, immunohistochemistry was also used. RESULTS: TB lesions predominated in men usually around or over 50 years old. The diagnostic was suspected in almost half of the cases. Right cavity was more affected and the extended fibrosis was present in a significant number of cases. The inflammatory conflict was of reactive type, with giant Langhans cells granulomas and acidophilic necrosis but sometimes with superinfection or significant fibrous sequelae. CONCLUSIONS: Pleural effusions of TB origin are a reality more and more present due to the recrudescence of pulmonary TB in the last decades. Their presence should be suspected if faced to a unilateral pleural effusion with free-flowing fluid occurred almost often to a man of any age from youth to elderly.

Linking minimum inhibitory concentrations to whole genome sequence-predicted drug resistance in Mycobacterium tuberculosis strains from Romania.

Mycobacterium tuberculosis drug resistance poses a major threat to tuberculosis control. Current phenotypic tests for drug susceptibility are time-consuming, technically complex, and expensive. Whole genome sequencing is a promising alternative, though the impact of different drug resistance mutations on the minimum inhibitory concentration (MIC) remains to be investigated. We examined the genomes of 72 phenotypically drug-resistant Mycobacterium tuberculosis isolates from 72 Romanian patients for drug resistance mutations. MICs for first- and second-line drugs were determined using the MycoTB microdilution method. These MICs were compared to macrodilution critical concentration testing by the Mycobacterium Growth Indicator Tube (MGIT) platform and correlated to drug resistance mutations. Sixty-three (87.5%) isolates harboured drug resistance mutations; 48 (66.7%) were genotypically multidrug-resistant. Different drug resistance mutations were associated with different MIC ranges; katG S315T for isoniazid, and rpoB S450L for rifampicin were associated with high MICs. However, several mutations such as in rpoB, rrs and rpsL, or embB were associated with MIC ranges including the critical concentration for rifampicin, aminoglycosides or ethambutol, respectively. Different resistance mutations lead to distinct MICs, some of which may still be overcome by increased dosing. Whole genome sequencing can aid in the timely diagnosis of Mycobacterium tuberculosis drug resistance and guide clinical decision-making.