Despite the impressive progress in diagnosis and management of acute COVID-19, data regarding the consequences of this infection are just emerging. The World Health Organization has proposed the term post-COVID condition (PCC) to describe the wide range of sequelae of acute COVID-19. With more than 200 million confirmed cases of COVID-19, PCC may develop into a major problem for many years to come for the millions of COVID-19 survivors worldwide. Few studies were conducted in primary care, and very few studies have focused exclusively on children and adolescents.Objective. To review existing data on PCC. Analysis of manuscripts published in peer-reviewed journals and clinical protocols. PCC is characterized by a wide range of systemic, cardio-pulmonary, gastrointestinal, neurological, and psychosocial symptoms.Conclusion. Although PCC prevalence is difficult to estimate due to methodological limitations of the existing studies, there is no doubt that this problem is a significant healthcare burden. There is a need for further observational and interventional studies to establish optimal PCC prevention and management strategies.

Background The long-term sequelae of coronavirus disease 2019 (Covid-19) in children remain poorly characterised. This study aimed to assess long-term outcomes in children previously hospitalised with Covid-19 and associated risk factors. Methods This is a prospective cohort study of children (≤18 years old) admitted with confirmed Covid-19 to Z.A. Bashlyaeva Children’s Municipal Clinical Hospital in Moscow, Russia. Children admitted to the hospital during the first wave of the pandemic, between April 2, 2020 and August 26, 2020, were included. Telephone interview using the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) Covid-19 Health and Wellbeing paediatric follow up survey. Persistent symptoms (>5 months) were further categorised by system(s) involved. Findings Overall, 518 of 853 (61%) of eligible children were available for the follow-up assessment and included in the study. Median age was 10.4 years (IQR, 3–15.2) and 270 (52.1%) were girls; median follow-up since hospital discharge was 256 (223-271) days. At the time of the follow-up interview 126 (24.3%) participants reported persistent symptoms among which fatigue (53, 10.7%), sleep disturbance (36, 6.9%,) and sensory problems (29, 5.6%) were the most common. Multiple symptoms were experienced by 44 (8.4%) participants. Risk factors for persistent symptoms were: age “6-11 years” (odds ratio 2.74 (95% confidence interval 1.37 to 5.75) and “12-18 years” (2.68, 1.41 to 5.4), and a history of allergic diseases (1.67, 1.04 to 2.67). Interpretation A quarter of children experienced persistent symptoms months after hospitalization with acute covid-19 infection, with almost one in ten experiencing multi-system involvement. Older age and allergic diseases were associated with higher risk of persistent symptoms at follow-up. Our findings highlight the need for replication and further investigation of potential mechanisms as well as clinical support to improve long term outcomes in children. Funding None. Evidence before this study Evidence suggests that Covid-19 may result in short- and long-term consequences to health. Studies in children and adolescents are limited and available evidence is scarce. We searched Embase for publications from inception to April, 25, 2021, using the following phrases or combinations of phrases “post-covid condition” or “post-covid syndrome” or “covid sequalae” or “post-acute covid” or “long covid” or “long hauler” with “pediatric*” or “paediatric*” or “child*” or “infant*” or “newborn*” or “toddler*” or “neonate*” or “neonatal” or “adolescent*” or “teen*”. We found small case series and small cohort studies looking at Covid-19 consequences in children. No large cohort studies of previously hospitalised children, assessing symptom duration, categorisation or attempting multivariable analyses to identify independent risk factors for long Covid development were identified. Added value of this study To our knowledge, this is the largest cohort study with the longest follow-up since hospital discharge of previously hospitalised children. We found that even months after discharge from the hospital, approximately a quarter of children experience persistent symptoms with one in ten having multi-system involvement. Older age and allergic diseases are associated with Covid-19 consequences. Parents of some children report emotional and behavioural changes in their children after Covid-19. Implications of all the available evidence Our findings highlight the need for continued global research of Covid-19 consequences in the paediatric population. Older children admitted to the hospital should be carefully monitored upon discharge. Large, controlled studies aiming to identify risk groups and potential intervention strategies are required to fill knowledge gaps.

Diabetic neuropathy is one of the most common diabetes mellitus complications associated with mediocalcinosis of the lower extremities, a significant decrease in feet bone mineral density, and a high incidence of cardiovascular disease. In most cases, calcium-phosphorus metabolism changes occur in patients with diabetic neuroarthropathy, or Charcot foot, when we can observe feet local osteoporosis, which in 90% of cases associated with a vessel’s calcification of the lower extremities in the majority of diabetes population. A large number of studies presented literature have demonstrated that patients with Charcot foot can have accelerated bone metabolism and increased bone resorption. Patients with Charcot foot often have crucial abnormalities in the calcium-phosphorus parameters, bone metabolism, and levels of vitamin D and its metabolites. In addition, the duration of diabetes mellitus, the degree of its compensation widely affects the development of its micro- and macrovascular complications, which could also accelerate the development of mineral and bone disorders in these types of patients. Multifactorial pathogenesis of these disorders complicates the management of patients with a long and complicated course of diabetes mellitus. This review discusses the peculiarities of vitamin D metabolism, the importance of timely diagnosis in phosphorus-calcium disorders, and the specifics of therapy in these patients. Special attention is paid to the timely diagnosis of the Charcot’s foots acute stage based on the bone marrow edema by MRI evaluation and the possibility of reducing the immobilization period.

Background: Post-COVID-19 condition (PCC) affects many survivors, with evidence of sex-specific differences in prevalence and symptom profiles. However, few prediction studies have examined whether sex-stratified models improve prediction or generalize across sexes. This study aimed primarily to develop and compare sex-stratified machine learning models for PCC prediction using routinely available baseline variables, and secondarily to assess cross-sex generalizability and adversarial robustness. Methods: We analyzed a prospective longitudinal cohort of 1006 adults hospitalized with COVID-19 at Sechenov University Hospital Network (Moscow, Russia). Demographics, smoking status, and pre-existing comorbidities were extracted from medical records, and PCC status was assessed at 6-month follow-up. Machine learning models—including classical algorithms and graph-based neural networks—were trained separately for males and females. Cross-sex validation evaluated generalizability, variable importance aided interpretation, and adversarial perturbations assessed model robustness. Results: PCC prevalence was higher in females (53.9%) than males (39.1%). Overall predictive performance was modest across all models, with AUC values ranging approximately 0.50–0.61. Graph-based models achieved the highest discrimination, with the best AUC reaching approximately 0.61, while classical approaches provided limited predictive value. Cross-sex validation showed minor asymmetry: models trained on male data performed slightly better on female cases than vice versa. Adversarial testing revealed sensitivity of all models to input perturbations. Conclusions: Demographics and comorbidities alone provide insufficient information for reliable PCC prediction. Modest sex-specific differences in model generalizability suggest distinct, sex-associated PCC phenotypes, but richer multimodal data—including clinical biomarkers, wearable-derived measures, and patient-reported outcomes—will be required to develop clinically useful and equitable predictive models. Sex-stratified approaches should be considered in future post-viral syndrome prediction studies.

Background: The COVID-19 pandemic has led to widespread long-term complications, known as post-COVID conditions (PCC), particularly affecting vulnerable populations such as cancer patients. This study aims to predict the incidence of PCC in hospitalised cancer patients using the data from a longitudinal cohort study conducted in four major university hospitals in Moscow, Russia. Methods: Clinical data have been collected during the acute phase and follow-ups at 6 and 12 months post-discharge. A total of 49 clinical features were evaluated, and machine learning classifiers including logistic regression, random forest, support vector machine (SVM), k-nearest neighbours (KNN), and neural network were applied to predict PCC. Results: Model performance was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. KNN demonstrated the highest predictive performance, with an AUC of 0.80, sensitivity of 0.73, and specificity of 0.69. Severe COVID-19 and pre-existing comorbidities were significant predictors of PCC. Conclusions: Machine learning models, particularly KNN, showed some promise in predicting PCC in cancer patients, offering the potential for early intervention and personalised care. These findings emphasise the importance of long-term monitoring for cancer patients recovering from COVID-19 to mitigate PCC impact.

The 20^th century was the time of large-scale discoveries and their widespread recognition. Metabolism studies and their role in living organisms deserve special attention. The chemical, physical, and biological metabolic reactions are the basis of life. Known details of these reactions are the key to understanding energy processes occurring in living organisms. Many scientists have devoted their scientific careers to the study different metabolic processes, and their most fundamental and landmark discoveries have been awarded with the Nobel Prize in Physiology or Medicine. This award, the most iconic achievement for any scientist, has been given since the beginning of the 20^th century for the most outstanding discoveries for all mankind. This review of the literature highlights the most important metabolic discoveries of the 20^th century that have played a key role in understanding how all living organisms work: the catalytic conversion of glycogen (Cori cycle), the tricarboxylic acid cycle (Krebs cycle), and cholesterol and the role of adenohypophysis hormones in glucose metabolism.