Treatment Process Of Patients Research Articles

Upskilling the cell therapy manufacturing workforce: design, implementation, and evaluation of a massive open online course.

Cell therapies have gained prominence as a promising therapeutic modality for treating a range of diseases. Despite the recent clinical successes of cell therapy products, very few formal training programs exist for cell therapy manufacturing. To meet the demand for a well-trained workforce, we assembled a team of university researchers and industry professionals to develop an online course on the principles and practice of cell therapy manufacturing. The course covers the basic cell and systems physiology underlying cell therapy products, in addition to explaining end-to-end manufacturing from cell acquisition through to patient treatment, industrialization, and regulatory processes. As of September 2023, >10,000 learners have enrolled in the course, and >90% of respondents to the course exit survey indicated that they were "very likely" or "likely" to recommend the course to a peer. In this article, we discuss our experience in the collaborative design and implementation of the online course as well as lessons learned from quantitative and qualitative student feedback. We believe that this course can serve as a model for how academia and industry can collaborate to create innovative, scalable training programs to meet the demands of the modern biotechnology workforce.NEW & NOTEWORTHY We assembled a team of university researchers and industry professionals to develop an online course on the principles and practice of cell therapy manufacturing. We believe that this course can serve as a model for how academia and industry can collaborate to create innovative, scalable training programs to meet the demands of the modern biotechnology workforce.

Sex Differences in the Pre- and In-Hospital Setting of Patients With Stroke Are Driven by Higher Age and Stroke Severity.

Sex critically determines stroke pathophysiology and recovery. To reveal potential gaps in stroke care, we analyzed sex-specific differences in the stroke patient hospital admission and treatment process. In this single-center retrospective analysis, we screened all patients referred to our stroke center between 2014 and 2020 with suspicion of stroke (n=7112). Patients with different cerebrovascular events and stroke mimics were included. We collected demographic hospitalization and 90-day follow-up data and stratified results according to sex. In a logistic regression analysis for 90-day functional outcome, we estimated the effect of sex corrected for the clinically most relevant confounders. Of 7102 patients, 56.7% were male and 43.3% female. Women were older (median, 76.3 years; interquartile range (IQR), 64-84, versus 70.7; IQR, 59-79; P<0.001), and lived more often in nursing homes before the event (10.5% versus 3.8%; P<0.001). Among patients with acute ischemic stroke (n=4515), women had more often a large vessel occlusion (38.6% versus 34.8%; P=0.015), a higher stroke severity (National Institutes of Health Stroke Scale score, 4; IQR, 1-12 versus 3; IQR, 1-8; P<0.001), and were treated more often with endovascular treatment (21.4% versus 17.3%; P=0.001). Onset-to-door, onset-to-treatment, and door-to-treatment times were significantly longer in women. A favorable 90-day functional outcome (modified Rankin Scale score 0-2) occurred more often in men (73.9% versus 64.9%; P<0.001). When correcting for confounders in a multivariable logistic regression, age, admission National Institutes of Health Stroke Scale, and prestroke modified Rankin Scale remained highly (P<0.001), large vessel occlusion and arterial hypertension moderately significant predictors for 90-day functional outcome (P<0.05), whereas female sex was not. This could be confirmed when analyzing different patient age groups separately in multivariable logistic regression subgroup analyses. An interaction-term analysis revealed no additional association between age and female sex (OR, 0.99; P=0.815). Although treatment and outcome parameters seem to be in favor of men, most can be explained by older age, poorer prestroke independence, higher stroke severity, and more large vessel occlusion in women. Sex was not independently associated with worse 90-day functional outcome in women.

Increased cerebellar vermis volume following repetitive transcranial magnetic stimulation in drug-resistant epilepsy: a voxel-based morphometry study.

Voxel-based morphometry (VBM) was applied to explore structural changes induced by repetitive transcranial magnetic stimulation (rTMS) and the relationship with clinical outcomes. Moreover, the relationship between each segmented regional gray matter (GM) volume was investigated to identify circuits involved in the rTMS treatment process in patients with drug-resistant epilepsy (DRE). Nineteen patients with DRE were finally included in the analysis. A session of rTMS was applied for 5 consecutive days. Participants received either 1,000 or 3,000 pulses, at a frequency of 0.5 Hz and the intensity was set at 90% of the individual's resting motor threshold. VBM analysis was performed to explore regional GM volume changes 2 months after rTMS application. The regional volume change was correlated with seizure reduction rate. Relationships between changes in GM volume in each anatomically parcellated region were analyzed using a fully-automated segmentation pipeline. Compared to the baseline, seizure frequency was reduced, and quality of life was improved after rTMS treatment. Regional volume was increased in the cerebellar vermis 2 months after rTMS application. The increased cerebellar vermis volume correlated with the reduced seizure frequency. Regional volume changes in the cerebellar vermis were correlated with changes in the subcortical and cortical GM regions including the thalamus, caudate, and frontal cortex. These results indicate that rTMS treatment effectively reduced seizure frequency in patients with DRE. Increased volume in the cerebellar vermis and activations of the cerebello-thalamo-cortical circuit may be a crucial mechanism underlying the effectiveness of rTMS application in patients with DRE.

MANIFESTAÇÕES ORAIS DAS LEUCEMIAS EM PACIENTES PEDIÁTRICOS

Leukemias can be described as blood dyscrasias resulting from the disordered multiplication of hematopoietic tissue cells. The manifestations of the disease occur systemically and have a major impact on the oral cavity, with repercussions in response to the disease itself and to elective treatment, whether surgical, chemo- or radiotherapy. The objective of this study is to discuss the oral alterations of greatest clinical value in pediatric patients, discussing the role of the dentist in the diagnosis and treatment of these manifestations. The study was carried out from the perspective of an integrative bibliographic review, following the previously established inclusion and exclusion criteria. The results emphasize the correlation between oral health and the integrity of all systems, demonstrating that the most prevalent alterations are oral mucositis, gingival enlargement followed by spontaneous bleeding and petechiae, opportunistic infections, cavities, xerostomia and hyposalivation. It is therefore concluded that there is a need for the dentist to evaluate and monitor the treatment process of pediatric patients with leukemia who are the target of antineoplastic therapy.

CHANGES IN LIPID AND CARBOHYDRATE METABOLISM IN PATIENTS WITH OSTEOARTHRITIS WITH ACCOMPANYING ARTERIAL HYPERTENSION AND TYPE 2 DIABETES, DEPENDING ON BSMI VDR GENE POLYMORPHISM

It is known that Osteoarthritis (OA) is a common chronic disease of the musculoskeletal system, which leads to a significant loss of working capacity and disability of people of working age, which worsens the quality of life of the population and causes economic burden and losses to all countries of the world. In addition, OA is known as a disease with an inherent high level of comorbidity. Scientists single out diseases of cardiovascular diseases, digestive systems and metabolic disorders as those that are most often combined with OA and complicate the course of each other in manifestations, diagnostic and treatment processes. Today, modern science needs to understand the presence of a common genetic origin. It is known that the polymorphic variant of the VDR vitamin D receptor gene has a predisposition to common osteochondral diseases. However, the issue of participation in pathogenetic mechanisms of development and progression remains controversial. A polymorphic variant of the VDR gene has a predisposition to osteochondral diseases. However, its involvement in the pathogenetic mechanisms of the development and progression of osteoarthritis remains controversial, therefore The aim of the study is to investigate the specifics of the impact of comorbid pathology on carbohydrate and lipid metabolism and the state of the vascular wall in patients with osteoarthritis, taking into account the polymorphic variant of the VDR gene (Bsml, rs1544410). Object and research methods. 100 patients were examined and also divided into groups: 1st group – patients with OA; II – OA with arterial hypertension; ІІІ – OA, arterial hypertension (AG) and type 2 diabetes mellitus, a blood sample was taken and, depending on age, comorbidity, the presence of the polymorphic variant BsmI (rs1544410) of the VDR gene, indicators of carbohydrate and lipid metabolism, the level of end metabolites of nitric oxide and endothelin-1 were studied and the impact on radiological changes and the functional state of the knee joints was evaluated. Control – 30 people. Results of the study and their discussion. It has been established that osteoarthritis is characteristic of persons of working age. With increasing age, it is characteristic to be burdened by comorbid pathologies with worsening of the course of the main disease. Expected violation of carbohydrate metabolism was observed in the III group of patients, although dynamic probable changes were also in the II group (p&lt;0.05). Lipid metabolism in the I group was probably higher than the group of control, but was within the physiological norm, while groups II and III had significant pathological changes compared to the indicators of the I group and practically healthy persons. Hypercholesterolemia became a trigger for a decrease in the total level of stable total nitrogen monoxide metabolites and an increase in endothelin-1, which forms endothelial dysfunction and leads to the progression of AG and worsening of the course of OA. After the genotyping and division into genotypes of the polymorphic variant BsmI of the VDR gene, conclusions were obtained about the unfavorable allele A in the exchange processes of the above indicators. Conclusions. Features of violations of carbohydrate and lipid metabolism, the condition of the endothelium, against the background of comorbidity and the presence of an unfavorable allele A of the BsmI polymorphic variant of the VDR gene should be taken into account in the complex diagnostic and treatment process of patients with OA.

Recurrent Visceral Leishmaniasis in a Case With Interleukin-12 Receptor Beta-1 Deficiency.

In this study, we present the case of a children who was followed up for recurrent visceral leishmaniasis and diagnosed with IL-12Rβ1 deficiency. A female patient who received Bacille Calmette-Guérin (BCG) vaccine 2 months after birth and developed visceral leishmaniasis at the age of 91 months was subsequently diagnosed with IL-12Rβ1 deficiency. The patient's diagnosis and treatment process were examined retrospectively. IL-12Rβ1 deficiency is an autosomal recessive disease characterized by susceptibility to recurrent and/or severe infections caused by weakly pathogenic mycobacteria and salmonella. Infections with other intramacrophagic organisms may also occur, although rarely. Based on this information, it is believed that the mutation in the IFN-γ/IL-12 axis in our patient predisposed her to recurrent Leishmania infections. This study adds to the limited literature on IL12RB1 deficiency as a cause of VL. Patients diagnosed with VL should be evaluated immunologically, as recurrent Leishmania infections may occur in those with IL-12Rβ1 defects.

Vitamin D involves in the treatment process of ici-treated tumor patients: A meta-analysis

Vitamin D involves in the treatment process of ici-treated tumor patients: A meta-analysis

Evaluation of Immuno-Hematological Parameters of Severe and Mild COVID-19 Cases in Babylon Province, Iraq

The hematopoietic system plays a very important role in contracting the corona virus infection. Hematology indicators are among the factors related to the clinical results of patients with covid-19 due to their cost-effectiveness, availability, speed and convenience of testing. The aim of this study was comparing hematological parameters including the number of Red Blood Cells (RBC), hemoglobin, hematocrit, and platelet count among mild and severe COVID-19 patients. Methods: The study was conducted on 100 Iraqi patients COVID-19 patients. Subjects were classified into two groups with mild (n= 50) and severe (n=50) COVID-19 infection symptoms based on the clinical criteria. The hematological parameters measurement included Red Blood Cell (RBC) count, Hemoglobin (Hb) levels, White Blood Cell (WBC) count, Platelet count (PLT), Hematocrit (HCT) levels, Platelet Distribution Width (PDW), and Mean Platelet Volume (MPV). An independent sample T-test was used to compare the means of hematological parameters between two groups. Results: The RBC count was significantly lower in severe group compared to mild group (P ≤ 0.05). HCT levels were significantly reduced in the severe group compared to mild group (P ≤ 0.05). The severe patients had a significantly lower PLT than mild patients (P ≤ 0.05). No significant difference in Hb levels was observed between severe and mild patients. The severe patients had a significantly higher PDW than mild patients (P ≤ 0.05). Additionally, the severe patients had a significantly higher MPV than mild patients (P ≤ 0.05). Conclusion: The findings of this study indicate that complete blood count measurements can be used as useful biomarkers to assess the severity of Covid-19. Early identification of severe COVID-19 patients using these markers can help to better manage and accelerate the treatment process for COVID-19 patients.

Analysis of 5 patients with acute glyphosate poisoning clinical characteristics and metabolic concentration

Objective: To analyze the correlation between changes in the concentration of glyphosate (GLY) and its metabolites (AMPA) in patients with acute glyphosate poisoning and clinical symptoms, and to provide reference for the study of glyphosate toxicity. Methods: Urine samples from 5 patients with oral glyphosate poisoning admitted to the Emergency Department of Yangzhou Third Class A General Hospital from February to July 2021 were collected. Urine concentrations of GLY and AMPA were measured using derivatization gas chromatography-mass spectrometry, and analyzed based on the patient's clinical manifestations and treatment process. Results: The main symptoms of the patient after poisoning were acute gastrointestinal symptoms, such as nausea, vomiting, abdominal pain, etc. The concentration of GLY in the patient's urine reached its maximum on the first day and gradually decreased over time. On the day of discharge, the final concentration of GLY was 10% lower than the initial concentration. At discharge, the clearance rates of GLY in cases 1, 2, 3, and 4 were 96.97%, 95.91%, 96.87% and 92.87%, respectively. Conclusion: The glyphosate has a shorter maintenance time after entering the human body; There is no correlation between the concentration of glyphosate and its metabolites admitted to the hospital, the dose of poisoning, and clinical symptoms in poisoned patients.

Radiographic imaging and diagnosis of spinal bone tumors: AlexNet and ResNet for the classification of tumor malignancy

ObjectiveThis study aims to explore the application of radiographic imaging and image recognition algorithms, particularly AlexNet and ResNet, in classifying malignancies for spinal bone tumors. MethodsWe selected a cohort of 580 patients diagnosed with primary spinal osseous tumors who underwent treatment at our hospital between January 2016 and December 2023, whereby 1532 images (679 images of benign tumors, 853 images of malignant tumors) were extracted from this imaging dataset. Training and validation follow a ratio of 2:1. All patients underwent X-ray examinations as part of their diagnostic workup. This study employed convolutional neural networks (CNNs) to categorize spinal bone tumor images according to their malignancy. AlexNet and ResNet models were employed for this classification task. These models were fine-tuned through training, which involved the utilization of a database of bone tumor images representing different categories. ResultsThrough rigorous experimentation, the performance of AlexNet and ResNet in classifying spinal bone tumor malignancy was extensively evaluated. The models were subjected to an extensive dataset of bone tumor images, and the following results were observed. AlexNet: This model exhibited commendable efficiency during training, with each epoch taking an average of 3 s. Its classification accuracy was found to be approximately 95.6 %. ResNet: The ResNet model showed remarkable accuracy in image classification. After an extended training period, it achieved a striking 96.2 % accuracy rate, signifying its proficiency in distinguishing the malignancy of spinal bone tumors. However, these results illustrate the clear advantage of AlexNet in terms of proficiency despite a lower classification accuracy. The robust performance of the ResNet model is auspicious when accuracy is more favored in the context of diagnosing spinal bone tumor malignancy, albeit at the cost of longer training times, with each epoch taking an average of 32 s. ConclusionIntegrating deep learning and CNN-based image recognition technology offers a promising solution for qualitatively classifying bone tumors. This research underscores the potential of these models in enhancing the diagnosis and treatment processes for patients, benefiting both patients and medical professionals alike. The study highlights the significance of selecting appropriate models, such as ResNet, to improve accuracy in image recognition tasks.

AB077. An evaluation of prognostic scoring systems for survival in a surgically treated cohort of 318 metastatic spine tumour surgery patients.

Survival prognostication plays a key role in the decision-making process for the surgical treatment of patients with spinal metastases. In the past traditional scoring systems such as the modified Tokuhashi and Tomita scoring systems have been used extensively, however in recent years their accuracy has been called into question. This has led to the development of machine learning algorithms to predict survival. In this study, we aim to compare the accuracy of prognostic scoring systems in a surgically treated cohort of patients. This is a retrospective review of 318 surgically treated spinal metastases patients between 2009 and 2021. The primary outcome measured was survival from the time of diagnosis. Predicted survival at 3 months, 6 months and 1 year based on the prognostic scoring system was compared to actual survival. Predictive values of each scoring system were measured via area under receiver operating characteristic curves (AUROC). The following scoring systems were compared, Modified Tokuhashi (MT), Tomita (T), Modified Bauer (MB), Van Den Linden (VDL), Oswestry (O), New England Spinal Metastases score (NESMS), Global Spine Study Tumor Group (GSTSG) and Skeletal Oncology Research Group (SORG) scoring systems. For predicting 3 months survival, the GSTSG 0.980 (0.949-1.0) and NESM 0.980 (0.949-1.0) had outstanding predictive value, while the SORG 0.837 (0.751-0.923) and O 0.837 (0.775-0.900) had excellent predictive value. While for 6 months survival, only the O 0.819 (0.758-0.880) had excellent predictive value and the GSTSG 0.791(0.725-0.857) had acceptable predictive value. For 1 year survival, the NESM 0.871 (0.822-0.919) had excellent predictive value and the O 0.722 (0.657-0.786) had acceptable predictive value. The MT, T and MB scores had an area under the curve (AUC) of <0.5 for 3-month, 6-month and 1-year survival. Increasingly, traditional scoring systems such as the MT, T and MB scoring systems have become less predictive. While newer scoring systems such as the GSTSG, NESM and SORG have outstanding to excellent predictive value, there is no one survival scoring system that is able to accurately prognosticate survival at all 3 time points. A multidisciplinary, personalised approach to survival prognostication is needed.

Impact of Diagnostic-Related Groups Healthcare Payment Reform on Public Hospitals

The increasing reform of diagnosis-related groups (DRG) healthcare payment plays a crucial role in the reform of the medical and healthcare system, accelerating the high-quality development of public hospitals and serving as a critical path for their reform. The innovation of DRG healthcare payment methods can balance the financial income and expenditure of public hospitals, while also achieving a more harmonized balance of interests among hospitals, patients, and health insurance. This reform effectively controls the operating costs of hospitals, strictly regulates medical behaviors and quality management, and optimizes the patient treatment process. To quickly adapt to this reform trend, public hospitals need to seize the opportunities of healthcare system reform, adopt corresponding strategies to address the impact of DRG payment reform and achieve their own sustainable development goals in health.

Automated identification of thrombectomy amenable vessel occlusion on computed tomography angiography using deep learning.

We developed and externally validated a fully automated algorithm using deep learning to detect large vessel occlusion (LVO) in computed tomography angiography (CTA). A total of 2,045 patients with acute ischemic stroke who underwent CTA were included in the development of our model. We validated the algorithm using two separate external datasets: one with 64 patients (external 1) and another with 313 patients (external 2), with ischemic stroke. In the context of current clinical practice, thrombectomy amenable vessel occlusion (TAVO) was defined as an occlusion in the intracranial internal carotid artery (ICA), or in the M1 or M2 segment of the middle cerebral artery (MCA). We employed the U-Net for vessel segmentation on the maximum intensity projection images, followed by the application of the EfficientNetV2 to predict TAVO. The algorithm's diagnostic performance was evaluated by calculating the area under the receiver operating characteristics curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The mean age in the training and validation dataset was 68.7 ± 12.6; 56.3% of participants were men, and 18.0% had TAVO. The algorithm achieved AUC of 0.950 (95% CI, 0.915-0.971) in the internal test. For the external datasets 1 and 2, the AUCs were 0.970 (0.897-0.997) and 0.971 (0.924-0.990), respectively. With a fixed sensitivity of 0.900, the specificities and PPVs for the internal test, external test 1, and external test 2 were 0.891, 0.796, and 0.930, and 0.665, 0.583, and 0.667, respectively. The algorithm demonstrated a sensitivity and specificity of approximately 0.95 in both internal and external datasets, specifically for cases involving intracranial ICA or M1-MCA occlusion. However, the diagnostic performance was somewhat reduced for isolated M2-MCA occlusion; the AUC for the internal and combined external datasets were 0.903 (0.812-0.944) and 0.916 (0.816-0.963), respectively. We developed and externally validated a fully automated algorithm that identifies TAVO. Further research is needed to evaluate its effectiveness in real-world clinical settings. This validated algorithm has the potential to assist early-career physicians, thereby streamlining the treatment process for patients who can benefit from endovascular treatment.

The relationship between personality traits and coping strategies with permanence in the treatment process in patients undergoing methadone maintenance treatment

ABSTRACT Background The increasing tendency to use drugs, especially with the lowering of the age of addiction and its prevalence among young people, is one of the major social problems, and many efforts have been made to investigate the relationship between drug use and personality structures. Methods This cross-sectional study was conducted in 2020–2022 on opioid-addicted men who were referred to an addiction treatment clinic undergoing maintenance treatment with methadone for at least 6 months. Demographic information, the NEO personality characteristics questionnaire, and Lazarus’s coping strategies were completed by the patients. Results 150 patients with an average age of 36.78 ± 9.03 years were investigated. The results showed that the score of the personality dimension of conscientiousness had a significant relationship with the rate of persistence in treatment (P-value < .05). The score of accepting responsibility had a significant inverse relationship with the rate of persistence in treatment (P-value < .05). However, other components of personality traits and coping strategies didn’t have a significant relationship with the rate of persistence in treatment (P-value > .05). Conclusion Different personality dimensions and different levels of self-efficacy and the choice and pattern of coping style are effective factors in the tendency or non-tendency of people to use drugs and addiction.

Complications and Health-Related Quality of Life in Children with Various Etiologies of Early-Onset Scoliosis Treated with Magnetically Controlled Growing Rods-A Multicenter Study.

Background: Early-onset scoliosis (EOS) refers to spinal deformities that develop and are diagnosed before the age of 10. The most important goals of the surgical treatment of EOS are to stop the progression of curvature, achieve the best possible correction, preserve motion, and facilitate spinal growth. The objectives of this multicenter study were to analyze the risk of complications among patients with EOS treated using magnetically controlled growing rods (MCGRs) and assess the patients' and their parents' quality of life after diagnosis and treatment with a minimum two-year follow-up. Methods: Patients given an ineffective nonoperative treatment qualified for surgery with MCGRs. This study involved 161 patients (90 females and 71 males) who were classified according to the etiology of curvature. The intraoperative and postoperative complications and those that occurred during the continuation of treatment with MCGRs were recorded and analyzed. The 24-item Early-Onset Scoliosis Questionnaire (EOSQ-24) was used to evaluate the patients' quality of life and satisfaction with the treatment. Results: Implant-related complications requiring instrumentation revision were recorded in 26% of the patients. Medical complications occurred in 45% of the population. The EOSQ-24 revealed a significant improvement in the average scores during the follow-up. Conclusions: The treatment of early-onset scoliosis with MCGRs carries 66% risks of incurring medical and mechanical complications, the latter 26% of patients requiring revision procedures. Children with neuromuscular scoliosis, females, and with curvature greater than 90 degrees are at a higher risk of developing complications. Limiting the number of elective surgeries necessitated to prolong the instrumentation and treatment process for patients with MCGRs can greatly enhance their quality of life and satisfaction throughout the follow-up period.

Evaluation of risk factors and survival rates of patients with early-stage breast cancer with machine learning and traditional methods

BackgroundThis article is aimed to make predictions in terms of prognostic factors and compare prediction methods by using Cox proportional hazards regression analysis (CPH), some machine learning techniques and Accelerated Failure Time (AFT) model for post-treatment survival probabilities according to clinical presentations and pathological information of early-stage breast cancer patients. Material and methodsThe study was carried out in three stages. In the first stage, the CPH method was applied. In the second stage, the AFT model and in the last stage, machine learning methods were applied. The data set consists of 697 breast cancer patients who applied to Marmara University Hospital oncology clinic between 01.01.1994 and 31.12.2009. The models obtained by using various parameters of the patients were compared according to the C index, 5-year survival rate and 10-year survival rate. Results and conclusionAccording to the models obtained as a result of the analyses applied, MetLN and age were obtained as a significant risk factor as a result of CPH method and AFT methods, while MetLN, age, tumor size, LV1 and extracapsular involvement were obtained as risk factors in machine learning methods. In addition, when the c-index values of the handheld models are examined, it is obtained as 69.8 for the CPH model, 70.36 for the AFT model, 72.1 for the random survival forest and 72.8 for the gradient boosting machine. In conclusion, the study highlights the potential of comparing conventional statistical methods and machine-learning algorithms to improve the precision of risk factor determination in early-stage breast cancer prognosis. Additionally, efforts should be made to enhance the interpretability of machine-learning models, ensuring that the results obtained can be effectively communicated and utilized by clinical practitioners. This would enable more informed decision-making and personalized care in the treatment and follow-up processes for early-stage breast cancer patients.

Systemic therapeutic strategies for hepatocellular carcinoma: current status and prospects

Hepatocellular carcinoma (HCC) is a common type of poorly prognosticated malignant tumor. Surgical resection is the preferred treatment method for early-stage HCC. However, at the time of the initial diagnosis, fewer than 30% of patients with liver cancer are suitable for radical therapy. Systemic therapy plays an important role in the treatment process of patients with intermediate- to advanced-stage HCC, as it can effectively extend patients' survival time. With an emphasis on the status and role of systemic therapy for comprehensive management of HCC, this article summarizes the latest progress at home and abroad in the past five years, including first-line combined immunotherapy for advanced-stage HCC, second-line therapy selection, perioperative systemic therapy application, and combined therapy of systemic and local. Currently, the treatment model combined with local therapy has already become a new research hotspot in the treatment of advanced-stage HCC. Nevertheless, in the future, individualized and precise systemic therapeutic strategies will need further exploration.

ASSESSMENT OF THE TREATMENT QUALITY OF PATIENTS WITH FUNCTIONAL DISORDERS OF THE DENTO-MAGULAR APPARATUS COMBINED WITH THE DENTOALVEOLAR FORM OF DEEP BITE

Introduction. Patients with a deep bite and dental restorations are at increased risk of unfixing of fixed appliances and other complications due to occlusal defects. The problem of the volume of dental interventions and rational choice of the type, as well as the elimination of complications after their implementation, is relevant and unsolved, especially in patients with disorders of the dental and jaw apparatus, combined with the dentoalveolar form of a deep bite. The aim of the research was to improve the quality of orthodontic treatment of patients with a deep bite, existing reconstructive restorations and occlusal disorders by developing a scientifically based clinical algorithm for fixation of fixed orthodontic equipment. Materials and methods. The main group – 29 patients who were treated according to the scheme of fixation of non-removable equipment developed by us and the use of myorelaxation methods, and the research group – 22 people who were treated with generally accepted method. Methods: questionnaires, clinical and radiological, instrumental and statistical. The results of our experimental study of patients illustrated that the scheme of the proposed algorithm for fixing fixed appliances in the future will have the opportunity to increase the efficiency of providing dental care and will be implemented in the treatment process in patients with a deep bite, because they are in the group of increased risk of unpredicted debonding of fixed orthodontic appliances. Conclusions. The results of our experimental study of patients illustrated that the scheme of the proposed algorithm for fixing fixed appliances in the future will have the opportunity to increase the efficiency of dental care and will be implemented in the treatment process in patients with a deep bite, because they are in the group of increased risk of unpredicted debonding of fixed orthodontic appliances.

Patients' perspectives on the use of artificial intelligence and robots in healthcare.

We aimed to evaluate the opinions of individuals aged 18 and above in our country regarding the use of artificial intelligence (AI) and robots in the field of healthcare. The growing population and patient load, coupled with increasing data, can expedite the diagnosis and treatment process for patients through faster, easier, and more accurate interpretation of information. The study encompasses voluntary participants aged 18 and above, who have either undergone surgery in ahospital or have accompanied afamily member during asurgical procedure and possess internet access as well as the capability to participate in online surveys. Atotal of 725 individuals participated in our study 61% (n=442) of respondents expressed trust in the operation of AI and robots in the hospital setting. 64.1% (n=465) of participants expressed trust in AI's contribution to disease diagnosis and laboratory tests. The confidence in AI's use in radiological examinations and its contribution reached 71.6% (n=519). This study demonstrates that the use of AI and robots in healthcare services is accepted by our society and would be appropriate in our society (Tab. 5, Fig. 1, Ref. 24).

A Framework of Digital Twins for Improving Respiratory Health and Healthcare Measures

The investigation describes an inventive use of digital twin technology and LSTM-based machine learning models for real-time patient lung disease monitoring and nutrition planning. The suggested application uses various patient healthcare data, treatment processes, dietary habits, and real-time sensor information to construct digital twins, which are virtual reproductions of specific patients. The LSTM model is trained on this large dataset to predict patient health improvements and dietary needs. For each patient’s digital twin, the program provides personalized treatment plans and nutritional advice, enabling proactive interventions and optimizing patient care. Using performance measures, the trained LSTM model achieves high scores for accuracy (92%), precision (89%), recall (93%), and F1 score (91%), proving its usefulness in generating credible health predictions. Patient feedback on the program shows that patients (98.8%) agree on the accuracy and importance of health feedback, as well as the convenience of access to health information (95.4%). The application’s response rate study reveals an average response rate of 85.87%, assuring prompt feedback. To secure patient information, the study emphasizes data privacy and security, adopting multilayered authentication and data encryption. The outcomes of this study demonstrate the application’s potential to revolutionize patient-centered healthcare by providing data-driven, personalized solutions to patients and healthcare professionals.