Individualized Treatment Plans Research Articles

Status and influencing factors of frailty in hospitalized patients with chronic heart failure: A cross-sectional study.

To investigate the frailty status of inpatients with chronic heart failure (CHF) and analyse its influencing factors, so as to provide evidence for the early identification of high-risk groups and frailty management. Early identification of frailty can guide the development and implementation of holistic and individualized treatment plans. However, at present, the frailty of patients with CHF has not attracted enough attention. A cross-sectional study. From June 2022 to June 2023, a convenience sample of 256 participants were recruited at a hospital in China. Multivariate logistic regression analysis was used to explore the influencing factors of frailty in patients with CHF, and an ROC curve was drawn to determine the cut-off values for each influencing factor. STROBE checklist guides the reporting of the manuscript. A total of 270 questionnaires were sent out during the survey, and 256 valid questionnaires were ultimately recovered, resulting in an effective recovery rate of 94.8%. The incidence of frailty in hospitalized patients with CHF was 68.75%. Multivariable logistic regression analysis showed that age, self-care ability, nutritional risk, Kinesiophobia and NT-proBNP were risk factors for frailty, while albumin and LVEF were protective factors. Multidimensional frailty was prevalent in hospitalized patients with CHF. Medical staff should take measures as early as possible from the aspects of exercise, nutrition, psychology and disease to delay the occurrence and development of frailty and reduce the occurrence of clinical adverse events caused by frailty. This study emphasizes the importance of the early identification of multidimensional frailty and measures can be taken to delay the occurrence and development of frailty through exercise, nutrition, psychology and disease treatment. Patients contributed through sharing their information required for the case report form and filling out questionnaires.

Clinical Practice Guidelines of the Latin American Federation of Endocrinology for the use of vitamin D in the maintenance of bone health: recommendations for the Latin American context

IntroductionThese guidelines aim to provide evidence-based recommendations for the supplementation of Vitamin D in maintaining bone health. An unmet need persists in Latin American regarding the availability of clinical and real-world data for rationalizing the use of vitamin D supplementation. The objective of these guidelines is to establish clear and practical recommendations for healthcare practitioners from Latin American countries to address Vitamin D insufficiency in clinical practice.MethodsThe guidelines were developed according to the GRADE-ADOLOPMENT methodology for the adaptation or adoption of CPGs or evidence-based recommendations. A search for high quality CPGs was complemented through a comprehensive review of recent literature, including randomized controlled trials, observational studies, and systematic reviews evaluating the effects of Vitamin D supplementation on bone health. The evidence to decision framework proposed by the GRADE Working Group was implemented by a panel of experts in endocrinology, bone health, and clinical research.ResultsThe guidelines recommend Vitamin D supplementation for individuals aged 18 and above, considering various populations, including healthy adults, individuals with osteopenia, osteoporosis patients, and institutionalized older adults. These recommendations offer dosing regimens depending on an individualized treatment plan, and monitoring intervals of serum 25-hydroxyvitamin D levels and adjustments based on individual results.DiscussionThe guidelines highlight the role of Vitamin D in bone health and propose a standardized approach for healthcare practitioners to address Vitamin D insufficiency across Latin America. The panel underscored the necessity for generating local data and stressed the importance of considering regional geography, social dynamics, and cultural specificities when implementing these guidelines.

A rare case of extensive hydrofluoric acid burn.

Hydrofluoric acid (HF) is a strongly corrosive, highly toxic, and highly dangerous mineral acid. Burns with over 1% total body surface area (TBSA) caused by anhydrous HF can lead to deep tissue damage, hypocalcaemia, poisoning, even death. In recent years, HF has become one of the most common substances causing chemical burns and ranks as the leading cause of death from chemical burns. Herein, we report a rare case with 91% TBSA burns caused by 35% HF. The patient developed complications such as shock, severe hypocalcaemia, metabolic acidosis, and respiratory failure. Multidisciplinary team consultation (burns, respiratory medicine, nephrology, infectious disease, and pharmacy) was performed immediately after admission. An individualized diagnosis and treatment plan was developed for the patient. The patient was given intensive care, blood volume monitoring, tracheotomy, fluid resuscitation, continuous blood purification, anti-infective and analgesic treatments, intravenous and percutaneous calcium supplementation, early rehabilitation training, psychological rehabilitation and other treatments. To prevent the wound from deepening, large-area debridement and skin grafting were performed early after injury. A large dose of 10% calcium gluconate was injected into the patient in divided doses, and the wound was continuously treated with wet dressings. Multiple surgical debridements, negative pressure wound treatment, biological dressings, and Meek skin grafting were performed. After most of the wounds (approximately 85% TBSA) healed, the patient was discharged from the hospital and continued to undergo dressing changes at a local hospital. The patient was followed up 3 months after discharge. All the wounds healed well, and the patient basically regained functional independence in daily life.

Personalised app-based information for patients with breast cancer: A pilot study to assess the efficacy and usability of the Answers 4 Cancers app.

e13796 Background: While most Irish oncology patients (pts) report searching for information online, they encounter challenges finding accurate, illness-specific information and understanding the content. Irish oncology pts typically use international online resources due to limited dedicated Irish sources. Information from the clinic is often poorly retained, with up to 40-80% immediately forgotten. Following the development of a successful patient information podcast, Answers 4 Cancers, we launched an app providing personalised patient information to address this resource gap. To our knowledge, this is the first app for oncology pts incorporating individual patient onboarding by healthcare professionals to provide tailored patient-specific information. Supportive self-management with app-based information has been shown to save nursing hours, improving burden on resources, and is aligned with the goals of the Irish National Cancer Strategy 2017-2026. Aim: To assess the usability of our app and its efficacy in providing relevant and useful information to pts. Methods: Pts with early stage breast cancer receiving (neo)adjuvant chemotherapy, with or without immunotherapy, at 2 Irish cancer centres, were enrolled in a pilot study. Pts downloaded the app and met with a specialist nurse who onboarded the pt and streamlined the information in the app based on their individual diagnosis and treatment plan. Information available on the app is curated from reliable sources and includes mental health and sexual wellbeing resources, clinical trials information, and personalised information on diagnosis, chemotherapy regimen, planned surgery and adjuvant treatments. Pts completed an online questionnaire, which included components of the System Usability Scale, ≥1 week following app download. Results: 13 pts were enrolled and received access to the app. All pts were female. The median age was 45 yrs. Median length of time from app download to questionnaire completion was 21 days. 7 pts (54%) completed questionnaires. 100% (7/7) of patients reported that they would like to use the app frequently, felt more confident in their treatment plan after using the app, and would recommend the app to other pts. 100% (7/7) of pts found the app easy to use and found all the information in the app relevant to their treatment plan. Recruitment is ongoing. Conclusions: This pilot study confirms that an app with a personalised platform is feasible and beneficial to Irish cancer pts and may be applicable to other health jurisdictions. We plan to progress our app as a national project to support the goals of the National Cancer Strategy and facilitate empowering pts to take an active role in their care. Next phases of development include symptom tracking and in-app communication between pts to develop support networks, and assessing the impact of the app on nursing time saved.

Measure of minimal residual burden on circulating tumor cells with over-expression of programmed death-ligand 1 as a dynamic biomarker in patients with colorectal cancer.

e14553 Background: In stage III colorectal cancer (CRC) patients, the extent of oxaliplatin-combination as an adjuvant therapy is still undetermined. Approx. 25-50% Stage II-III CRC patients are known to develop recurrence and metastasis even after comprehensive treatment, attributed to occult disease and Minimal Residual Disease (MRD). Circulating Tumor Cells (CTCs) are bio-mechanistic extravasation source for micro-metastatic disease. CRC patients, with lower adjuvant therapy from 3 to 6 months are known to exhibit increased CTCs and positivity rate due to the emergence of resistant clones. Assays to detect CTCs and expression of Programmed Cell Death-Ligand 1 (PD-L1) as a dynamic biomarker simultaneously has wide clinical implications. Especially, when the tissue biopsy is not inadequate to detect molecular targets for immune checkpoint inhibitor (ICT) therapy. Methods: Retrospectively, 182 CRC cancer patients were analyzed for the presence of CTC and distribution at baseline and follow-ups (up to 0-4 follow ups). The peripheral blood 1.5 ml was analyzed using the OncoDiscover platform approved by CDSCO, India consisting multifunctional magneto-nanosystem mediated by anti-epithelial cellular adhesion molecule (EpCAM) antibody. CTCs were analyzed in patients with early stages- pre and post treatment, progressive disease, Disease Free Status (DFS) and in metastasis. The isolated cells were immune-stained to detect CK-18 +ve, CD45 -ve, DAPI +ve and PD-L1 +ve expression. PD-L1 expression in CTCs was validated by analyzing the linear intensity gradients of the fluorescence signals. CTCs were termed as PD-L1 -ve based on a weak or no detectable fluorescence signal and termed +ve based on a high fluorescence signal using automated image acquisition Zeiss microscope. Results: In a cohort of 182 CRC patient samples, n = 128 (70.3 %) showed the presence of CTCs. The fluorescence intensity for PD-L1 expression as a robust functional assay on CTCs for molecular characterization was developed. The distribution of CTCs ranged from 1-9. The mean fluorescence intensity value and cut-off for the expression of PD-L1 in CTCs was accounted to be ~1.02. Interestingly, in n = 54 (42.2 %) patients, CTCs showed positive expression of PD-L1. CTC +ve patients with PD-L1 expression were associated at all stages and even in early stage, progressive disease, and metastasis. Patients without any CTCs n = 54 (29.7%) either had clinically stable disease or were in DFS with no radio-graphical image. Conclusions: The presence of PD-L1 over-expression on CTCs is a dynamic biomarker in blood, showing the progression of disease even in patients with DFS status. CTC enumeration and assessing the PD-L1 expression on CTCs could offer highly individualized treatment plans in CRC patients.

„Der Reha-Gedanke muss bei dieser Erkrankung völlig neu gedacht werden“ – Qualitative Ergebnisse einer Online-Befragung zu Erfahrungen Betroffener mit stationärer Rehabilitation bei Long/Post-COVID

BackgroundIn Germany, an estimated number of 70,000 people diagnosed with long COVID or post-COVID syndrome (PCS) had received inpatient medical rehabilitation by the end of 2022. Due to the heterogeneity of the clinical picture, the variability of interventions and inconsistent endpoints, previous studies on the effectiveness of rehabilitation are of limited value. It therefore remains unclear whether and to what extent rehabilitation measures established for, e.g., pulmonary, cardiovascular, or neurological diseases are suitable for patients with PCS. ObjectivesTo identify the experiences and perspectives of those affected by PCS, in relation to inpatient rehabilitation and to describe patients’ values and wishes with respect to evidence-based medicine. MethodsIn January/February 2023, the German initiative “Long COVID Deutschland” conducted a retrospective online survey (39 closed items, two open answer fields) among adult PCS sufferers on their experiences with inpatient rehabilitation. Recruitment was carried out via social media and websites of patient initiatives. The open answers were analyzed using a structuring and summarizing qualitative content analysis according to Mayring, supplemented by descriptive representations of the distribution of standardized information. ResultsOf 1,191 participants in the survey, 733 used open response formats to additionally explain their experiences and the effects of individual measures on their general condition. 366 (50%) reported that their state of health deteriorated, mainly because of strength or endurance training and too extensive treatment plans. The presence of a post-exertional malaise (PEM) or its insufficient consideration during rehabilitation was described as the main barrier. Recognition and acceptance of individual performance limits, flexible and coordinated individual treatment plans tailored to the patient’s limitations, and support in coping with the disease were described as supportive factors. From the participants’ perspective, learning strategies to avoid deterioration in their state of health due to overexertion, the so-called pacing, should be the core treatment goal for patients affected by PEM. DiscussionThe results are not statistically representative but ensure systematic insights into the subjective perspectives of those affected, the consideration of which represents one of the three principles of evidence-based medicine. The results show that for PCS patients with PEM, even minimum requirements for rehabilitation measures can lead to overexertion and aggravation. ConclusionsCommon subject-specific rehabilitation concepts appear to be only partially suitable for dealing with the symptoms and the heterogeneity of the disease. Aims and interventions should be individually adapted, and the focus should be on pacing, disease coping and management. A reliable test for PEM and rehabilitation ability before the start of rehabilitation is needed to ensure safety for those affected. To adequately classify studies on the effectiveness of rehabilitation, risks and side effects should be disclosed.

Pre-treatment CT radiomics for predicting immunotherapy response in non-small cell lung cancer(NSCLC): RECIST vs. irRECIST criteria.

e20613 Background: Accurate prediction of how patients with non-small cell lung cancer (NSCLC) will respond to immunotherapy is essential for customizing individual treatment plans. This research explores the use of radiomics analysis from pre-treatment CT scans as a method to predict the effectiveness of immunotherapy in individuals with NSCLC. Methods: This IRB-approved retrospective study investigated radiologic and clinical data from 159 patients with stage III-IV NSCLC treated with immunotherapy. Imaging responses were assessed according to RECIST 1.1 and immune-related RECIST (irRECIST) criteria at least twice during a 24-week period. Responses were categorized as complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). 3D radiomics features were extracted from both the tumor and a 1 cm thick peritumoral region. A linear mixed-effect harmonization model was employed to correct for scanner-associated variations. A Random Forest algorithm was used to develop a classification model to predict response according to RECIST 1.1 or irRECIST. The dataset was split into training (70%) and test (30%) sets. The accuracy of predictions was evaluated using confusion matrix statistics and bootstrapping with 1,000 iterations for median and 95% confidence interval (CI). Results: Using RECIST 1.1 criteria, 41 patients (25.2%) achieved PR and CR(0.6), 62 (39.0%) achieved SD, and 56 (35.2%) achieved PD. IrRECIST criteria yielded slightly higher CR/PR rates with 52 patients (32.7%), while SD decreased to 65 (41.0%) and PD remained at 42 (26.4%). For predicting CR/PR and SD responses, the models achieved a sensitivity of 0.45 (95% CI: 0.38-0.50) and 0.64 (0.60-0.68) for irRECIST, compared to 0.34 (0.28-0.38) and 0.55 (0.52-0.60) for RECIST 1.1. The corresponding specificity was 0.85 (0.83-0.87) and 0.63 (0.59-0.67) for irRECIST, compared to 0.91 (0.89-0.93) and 0.67 (0.63-0.72) for RECIST 1.1. For predicting PD response, the models achieved a sensitivity of 0.49 (0.45-0.56) for irRECIST and 0.57 (0.52-0.62) for RECIST 1.1. The models' balanced accuracy for predicting CR/PR, SD, and PD were 0.65 (0.61-0.68), 0.64 (0.61-0.67), and 0.65 (0.63-0.69) for irRECIST, compared to 0.62 (0.59-0.64), 0.61 (0.59-0.64), and 0.62 (0.59-0.64) for RECIST 1.1, respectively. Conclusions: This study demonstrates the potential of pre-treatment CT radiomics to predict immunotherapy responses in NSCLC patients, offering insights into personalized treatment approaches. However, larger studies are needed to validate our findings.

Evolving Standards of Care in the Management of Localized Colorectal Cancer.

The treatment of patients with localized rectal cancer is complex and requires input from a multidisciplinary team. Baseline local staging and mismatch repair protein testing are vital to develop individualized treatment plans. There are multiple options in terms of treatment modalities and sequencing, including transanal excision, short-course radiation, long-course chemoradiation, chemotherapy doublet or triplet, nonoperative management, and immune checkpoint blockade for patients with mismatch repair deficient tumors. While localized colon cancer is typically treated with surgical resection and consideration of adjuvant chemotherapy, emerging data suggest that neoadjuvant chemotherapy may be beneficial in patients with higher-risk disease. Quality-of-life considerations are imperative to prevent potential chronic effects on psychosocial health, neuropathy, fertility, and bowel, bladder, and sexual function. The omission of radiation or surgery can mitigate these toxicities without diminishing oncologic outcomes. The optimal treatment plan and sequence is not a one-size-fits-all approach but rather should be personalized to the patient's disease burden, tumor location, comorbidities, and preferences.

Treatment of late left bronchopleural fistula after left pneumonectomy through right thoracic approach assisted by extracorporeal membrane oxygenation

BackgroundBronchopleural fistula (BPF) is a rare but fatal complication after pneumonectomy. When a BPF occurs late (weeks to years postoperatively), direct resealing of the bronchial stump through the primary thoracic approach is challenging due to the risks of fibrothorax and injury to the pulmonary artery stump, and the surgical outcome is generally poor. Here, we report a case of late left BPF following left pneumonectomy successfully treated using a right thoracic approach assisted by extracorporeal membrane oxygenation (ECMO).Case presentationWe report the case of a 57-year-old male patient who underwent left lower and left upper lobectomy, respectively, for heterochronic double primary lung cancer. A left BPF was diagnosed at the 22nd month postoperatively, and conservative treatment was ineffective. Finally, the left BPF was cured by minimally invasive BPF closure surgery via the right thoracic approach with the support of veno-venous extracorporeal membrane oxygenation (VV-ECMO).ConclusionsAdvanced BPF following left pneumonectomy can be achieved with an individualized treatment plan, and the right thoracic approach assisted by ECMO is a relatively simple and effective method, which could be considered as an additional treatment option for similar patients.

Knowledge mapping of disease-modifying therapy (DMT) in multiple sclerosis (MS): A bibliometrics analysis

BackgroundMultiple sclerosis (MS) is a heterogeneous autoimmune disease, with a rapidly evolving body of literature on disease-modifying therapy (DMT) that urgently needs to be synthesized and regularized. MethodsThe original material used for the analysis was obtained from the Web of Science Core Collection (WoSCC) in the Science Citation Index Expanded Edition (SCI-E). The data material was accessed through VOSviewer, Citespace, R package “Bibliometrix”, and Scimago Graphica for data analysis and visualization. Among them, the clustering algorithm based on the Largest Likelihood Ratio (LLR) and the burst citation algorithm is the key. ResultsAs of November 6th, 2022, 4142 publications related to emerging disease-modifying therapies (e-DMT) for MS, 6521 publications related to traditional disease-modifying therapies (t-DMT) for MS, and 1793 publications in cross-cutting disease-modifying therapies (I-DMT) for MS were included in the analysis, respectively. Publications related to DMT in MS were analyzed descriptively (for three subjects: country, institution, and author) and predictively (for two subjects: keywords and references) separately according to three sections: e-DMT, t-DMT, and I-DMT. Topics that still have relevant reference output as of 2022 include the safety of Coronavirus disease 2019 (COVID-19) mRNA vaccination, therapeutic inertia (TI), cladribine tablets, autologous hematopoietic stem cell transplantation (aHSCT), progressive multiple sclerosis, and pediatric multiple sclerosis. ConclusionThe future research focus for MS DMT is the combination trial or cross-trial of various treatment methods to improve the development of individualized treatment plans for MS patients. The exact contents of the research frontiers are included but not limited to ocrelizumab, fingolimod and other monoclonal antibodies, fumaric acid ester, cladribine tablet, aHSCT, and other interventions of randomized controlled trials (RCTs); the impact of mRNA COVID-19 vaccination on MS patients; TI, patient adherence, and other medical management issues; and continued exploration of biomarkers for more accurate disease classification based on the existing clinical indication classification.

PERSONALIZED HEALTHCARE AS AN INDICATOR OF PATIENT RESILIENCE

Personalized healthcare, tailored to individual characteristics, has gained prominence in the modern healthcare systems. This comprehensive review explores the various aspects of personalized healthcare and its impact on patient resilience.The review incorporates a synthesis of literature from multiple disciplines, including genetics, psychology, nutrition, and environmental factors. It analyzes the role of personalized health care in enhancing patient resilience, considering genetic predisposition, psychological aspects, nutrition, environmental influences, individualized treatment plans, treatment outcomes, challenges, and future directions.Genetic analysis is crucial for identifying patients' predispositions and making personalized treatment decisions. Psychological factors significantly influence patient resilience, with adaptable therapeutic approaches to enhance psychological resilience. Personalized dietary recommendations, based on individual needs and genetic factors, improve overall health. Environmental factors, such as air quality and stress, impact patient well-being, and personalized care involves monitoring and reducing these risks. Integrating these aspects into individualized treatment plans leads to improved outcomes and quality of life. Real-world examples confirm the effectiveness of personalized healthcare in strengthening patient resilience.Personalized health care plays a vital role in enhancing patient resilience. It offers tailored treatment plans that address individual characteristics, resulting in improved treatment outcomes and quality of life. Keywords:personalized health care, indicator, resilience, patient

Automated machine learning for predicting liver metastasis in patients with gastrointestinal stromal tumor: a SEER-based analysis

Gastrointestinal stromal tumors (GISTs) are a rare type of tumor that can develop liver metastasis (LIM), significantly impacting the patient's prognosis. This study aimed to predict LIM in GIST patients by constructing machine learning (ML) algorithms to assist clinicians in the decision-making process for treatment. Retrospective analysis was performed using the Surveillance, Epidemiology, and End Results (SEER) database, and cases from 2010 to 2015 were assigned to the developing sets, while cases from 2016 to 2017 were assigned to the testing set. Missing values were addressed using the multiple imputation technique. Four algorithms were utilized to construct the models, comprising traditional logistic regression (LR) and automated machine learning (AutoML) analysis such as gradient boost machine (GBM), deep neural net (DL), and generalized linear model (GLM). We evaluated the models' performance using LR-based metrics, including the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA), as well as AutoML-based metrics, such as feature importance, SHapley Additive exPlanation (SHAP) Plots, and Local Interpretable Model Agnostic Explanation (LIME). A total of 6207 patients were included in this study, with 2683, 1780, and 1744 patients allocated to the training, validation, and test sets, respectively. Among the different models evaluated, the GBM model demonstrated the highest performance in the training, validation, and test cohorts, with respective AUC values of 0.805, 0.780, and 0.795. Furthermore, the GBM model outperformed other AutoML models in terms of accuracy, achieving 0.747, 0.700, and 0.706 in the training, validation, and test cohorts, respectively. Additionally, the study revealed that tumor size and tumor location were the most significant predictors influencing the AutoML model's ability to accurately predict LIM. The AutoML model utilizing the GBM algorithm for GIST patients can effectively predict the risk of LIM and provide clinicians with a reference for developing individualized treatment plans.

Balancing the mind: The critical role of carbamazepine as a mood stabilizer in bipolar and schizoaffective disorders

This case study explores the therapeutic application and associated challenges of using carbamazepine as a mood stabilizer in the management of schizoaffective disorder. The patient, a 42-year-old male with a history of schizoaffective disorder, exhibited acute manic symptoms exacerbated by substance use and non-compliance with medication. The introduction of carbamazepine initially showed promise in stabilizing mood and reducing psychotic symptoms. However, the treatment course was complicated by a significant adverse dermatological reaction. This necessitated a switch to valproic acid, which was better tolerated. The case underscores the importance of careful monitoring and readiness to adjust treatment in response to carbamazepine-induced side effects. This study highlights the critical need for individualized treatment plans and emphasizes the role of pharmacogenetic testing in predicting adverse drug reactions, ensuring safer and more effective management of psychiatric conditions.

Survival benefit of postoperative radioiodine therapy among patients with intermediate-risk differentiated thyroid carcinoma.

The 2015 American Thyroid Association (ATA) guidelines proposed the use of the ATA Risk Stratification System and American Joint Committee on Cancer Tumor-Node-Metastasis (AJCC/TNM) Staging System for postoperative radioiodine decision-making. However, the management of patients with intermediate-risk differentiated thyroid carcinoma (DTC) is not well defined. In this study, we aimed to evaluate the therapeutic efficacy of radioactive iodine therapy (RAIT) among various subgroups of patients with intermediate-risk DTC after surgery. This was a retrospective study based on the Surveillance, Epidemiology, and End Results (SEER) database (2010-2015). The DTC patients with intermediate risk of recurrence were divided into two groups (treated or not treated with radioactive iodine (RAI)). As the treatment was not randomly assigned, stabilized inverse probability treatment weighting (sIPTW) was used to reduce selection bias. We used the Kaplan-Meier method and log-rank test to analyze overall survival (OS) and cancer-specific survival (CSS). Kaplan-Meier analysis after sIPTW found a significant difference in OS and CSS between no RAIT and RAIT (log-rank test, P < 0.0001; P = 0.0019, respectively). The Kaplan-Meier curves of CSS in age cutoff of 55 years showed a significant association between no RAIT and RAIT (log-rank test, P = 0.0045). Univariate and multivariate Cox regression showed RAIT was associated with a reduced risk of mortality compared with no RAIT (hazard ratio [HR] 0.59, 95% confidence interval [95% CI 0.44-0.80]). Age (≥ 55) years showed a worse CSS regardless of whether or not a patient was treated or not treated with RAI ([HR] 8.91, 95% confidence interval [95% CI 6.19-12.84]). RAIT improves OS and CSS in patients with intermediate-risk DTC after surgery. 55 years is a more appropriate prognostic age cutoff for the relevant classification systems and is a crucial consideration in RAI decision-making. Therefore, we need individualized treatment plans.

Results of esketamine administration in a Greek population: a case series.

Esketamine is a non-selective, competitive antagonist of the N-methyl-D-aspartate (NMDA) receptor in the brain. Through NMDA receptor antagonism, esketamine causes a transient increase in glutamate release, leading to increases in neurotrophic signaling and restoration of synaptic function in brain regions involved in mood regulation and emotional behavior. Several randomized clinical trials have shown its effectiveness in reducing the symptoms of depression in some people, despite its short-term side effects that include mainly disorientation, dizziness, nausea, and increased blood pressure. In 2019, the United States Food and Drug Administration (FDA) as well as the European Medicines Agency approved the use of esketamine nasal spray in combination with an oral antidepressant for treatment-resistant depression in adults. Our study aimed to evaluate the effectiveness of this new therapeutic proposal in a case series of five Greek patients with treatment- resistant depression. Intranasal esketamine was administered under medical supervision in combination with an oral antidepressant. Depressive symptoms were evaluated at three time points (baseline, end of treatment, and one-year post-treatment) using the Montgomery-Åsberg Depression Rating Scale (MADRS), the Patient Health Questionnaire (PHQ-9), the CGI Clinical Global Impression Scale, and the Perceived Deficits Questionnaire for Depression (PDQ-D). Possible side effects were assessed using the Richmond Suppression Agitation Scale (RASS), the Sheehan Disability Scale (SDS), the CADSS Disruptive States Scale, and a predefined list of adverse events (AEs) and serious adverse events (SAEs). Patients followed an individualized treatment plan for seven to twelve months depending on the achievement of an adequate response. Statistical analysis of the results revealed a significant improvement (p<0.05) on all scales used. All participants maintained their level of improvement at follow-up after twelve months. Adverse effects were found to be mild and tolerable. It is worth noting that significant side effects were reported only by the two patients with comorbid personality disorder. The results, despite limited to a small sample, indicate the positive effect of esketamine on the stable reduction of depressive symptoms among patients with resistant depression, even after the completion of treatment.

Multi-omics research progress in early-onset colorectal cancer

Globally, the incidence of early-onset colorectal cancer (EOCRC) among individuals younger than 50 is escalating. Compared to late-onset colorectal cancer, EOCRC exhibits distinct clinical, pathological, and molecular features, with a higher prevalence in the left colon and rectum. However, the occurrence and development of EOCRC is a multi-factor and multi-stage evolution process, which is the result of the mutual effect of environmental, genetic and biological factors, and involves the multi-level regulation mechanism of other organisms. With the development and improvement of high-throughput sequencing technology, the application of multi-omics analysis has become an important development direction to resolve the pathogenesis of complex diseases and individualized treatment plans. This article aims to review the research progress of EOCRC at the multi-omics level, providing a theoretical foundation for earlier diagnosis and more precise treatment of this diseases.

#426 “Predict-PD”: a machine learning tool to predict patient survival in peritoneal dialysis patients

Abstract Background and Aims With the rising prevalence of chronic kidney disease (CKD), particularly among the elderly, the need for effective renal replacement therapy has become increasingly crucial. Peritoneal dialysis (PD), recognized as a gentler alternative to haemodialysis, offers advantages in cognitive preservation and overall quality of life. Patient survival on PD, a tangible outcome measure, gains particular importance, especially in an aging demographic confronting end-stage kidney disease. Predicting survival thus becomes vital in facilitating individualized treatment planning and has implications on resource allocation and patient counseling. Method Our study analysed data from the UK Renal Registry and included 22 711 incident dialysis patients choosing PD between 2007 and 2022. Our objective was to employ Artificial Intelligence (AI) algorithms in developing an advanced risk stratification indicator with high predictive capabilities, specifically tailored for use in the United Kingdom's transplant selection procedure. We conducted experiments using three distinct machine learning models and evaluated their performance in terms of calibration and discrimination, utilizing metrics such as the integrated Brier score (IBS) and Harrell's concordance index. We assessed the potential clinical utility using decision curve analysis. Results The XGBoost model demonstrated excellent predictive efficacy for patient survival, with a concordance of 0.78. Further scrutiny revealed AUC values at 1 year (0.81), 3 years (0.78), and 5 years (0.77). The integrated Brier score, a comprehensive measure of predictive accuracy, was 0.09. There was no statistical difference between the actual and predicted survival probabilities (P = 0.72). Decision curve analysis accentuated the model's clinical applicability. Conclusion This study illustrates the potential of machine learning in prognosticating patient survival in PD, offering a pathway towards individualized patient-centric management in nephrology. The findings advocate for the integration of data-driven methodologies in clinical decision-making, paving the way for enhanced personalized care in CKD management and can serve as a guide for future research.

Orthodontic Management of Dental Anomalies in Patients with Cleft Lip and Palate- A Case Series

Introduction: Orthodontic management of patients with cleft lip and palate is a tedious process requiring meticulous treatment planning. However, in patients with a fairly good facial profile, non-surgical management using orthodontic treatment alone can produce astounding results in correction of malocclusion and to achieve a pleasing smile. A properly executed orthodontic treatment enhances not only the smile, but also the masticatory efficiency, speech and overall quality of life of the patients with cleft lip and palate. Methods: This case series describes orthodontic management of three patients with cleft lip and palate who have been treated by distinct treatment modalities. Results: An outline of the different orthodontic treatments along with possible interdisciplinary management has been explained in this case series. Conclusion: We therefore understand that in patients with cleft lip and palate who have a reasonably good facial profile, complete orthodontic therapy with individualized treatment plan is vital to provide good physiological, functional and aesthetic outcomes.

Cluster Analysis and Ablation Success Rate in Atrial Fibrillation Patients Undergoing Catheter Ablation

Atrial fibrillation (AF) is a disease of high heterogeneity, and the association between AF phenotypes and the outcome of different catheter ablation strategies remains unclear. Conventional classification of AF (e.g. according to duration, atrial size, and thromboembolism risk) fails to provide reference for the optimal stratification of the prognostic risks or to guide individualized treatment plan. In recent years, research on machine learning has found that cluster analysis, an unsupervised data-driven approach, can uncover the intrinsic structure of data and identify clusters of patients with pathophysiological similarity. It has been demonstrated that cluster analysis helps improve the characterization of AF phenotypes and provide valuable prognostic information. In our cohort of AF inpatients undergoing radiofrequency catheter ablation, we used unsupervised cluster analysis to identify patient subgroups, to compare them with previous studies, and to evaluate their association with different suitable ablation patterns and outcomes. The participants were AF patients undergoing radiofrequency catheter ablation at West China Hospital between October 2015 and December 2017. All participants were aged 18 years or older. They underwent radiofrequency catheter ablation during their hospitalization. They completed the follow-up process under explicit informed consent. Patients with AF of a reversible cause, severe mitral stenosis or prosthetic heart valve, congenital heart disease, new-onset acute coronary syndrome within three months prior to the surgery, or a life expectancy less than 12 months were excluded according to the exclusion criteria. The cohort consisted of 1102 participants with paroxysmal or persistent/long-standing persistent AF. Data on 59 variables representing demographics, AF type, comorbidities, therapeutic history, vital signs, electrocardiographic and echocardiographic findings, and laboratory findings were collected. Overall, data for the variables were rarely missing (<5%), and multiple imputation was used for correction of missing data. Follow-up surveys were conducted through outpatient clinic visits or by telephone. Patients were scheduled for follow-up with 12-lead resting electrocardiography and 24-hours Holter monitoring at 3 months and 6 months after the ablation procedure. Early ablation success was defined as the absence of documented AF, atrial flutter, or atrial tachycardia >30 seconds at 6-month follow-up. Hierarchical clustering was performed on the 59 baseline variables. All characteristic variables were standardized to have a mean of zero and a standard deviation of one. Initially, each patient was regarded as a separate cluster, and the distance between these clusters was calculated. Then, the Ward minimum variance method of clustering was used to merge the pair of clusters with the minimum total variance. This process continued until all patients formed one whole cluster. The "NbClust" package in R software, capable of calculating various statistical indices, including pseudo t2 index, cubic clustering criterion, silhouette index etc, was applied to determine the optimal number of clusters. The most frequently chosen number of clusters by these indices was selected. A heatmap was generated to illustrate the clinical features of clusters, while a tree diagram was used to depict the clustering process and the heterogeneity among clusters. Ablation strategies were compared within each cluster regarding ablation efficacy. Five statistically driven clusters were identified: 1) the younger age cluster (n=404), characterized by the lowest prevalence of cardiovascular and cerebrovascular comorbidities but the highest prevalence of obstructive sleep apnea syndrome (14.4%); 2) a cluster of elderly adults with chronic diseases (n=438), the largest cluster, showing relatively higher rates of hypertension, diabetes, stroke, and chronic obstructive pulmonary disease; 3) a cluster with high prevalence of sinus node dysfunction (n=160), with patients showing the highest prevalence of sick sinus syndrome and pacemaker implantation; 4) the heart failure cluster (n=80), with the highest prevalence of heart failure (58.8%) and persistent/long-standing persistent AF (73.7%); 5) prior coronary artery revascularization cluster (n=20), with patients of the most advanced age (median: 69.0 years old) and predominantly male patients, all of whom had prior myocardial infarction and coronary artery revascularization. Patients in cluster 2 achieved higher early ablation success with pulmonary veins isolation alone compared to extensive ablation strategies (79.6% vs. 66.5%; odds ratio [OR]=1.97, 95% confidence interval [CI]: 1.28-3.03). Although extensive ablation strategies had a slightly higher success rate in the heart failure group, the difference was not statistically significant. This study provided a unique classification of AF patients undergoing catheter ablation by cluster analysis. Age, chronic disease, sinus node dysfunction, heart failure and history of coronary artery revascularization contributed to the formation of the five clinically relevant subtypes. These subtypes showed differences in ablation success rates, highlighting the potential of cluster analysis in guiding individualized risk stratification and treatment decisions for AF patients.

STATISTICAL ANALYSIS OF THE PREVALENCE OF INTERNAL TEMPOROMANDIBULAR JOINT DISORDERS IN FEMALE PATIENTS BASED ON C. H. WILKES CLASSIFICATION

Introduction. Severity levels of temporomandibular joint dysfunction can be assessed by certain parameters based on images obtained using magnetic resonance imaging. In order to assess the condition of the joint and choose the optimal treatment plan depending on the detected changes on the magnetic resonance imaging images, the most common classification according to C. H. Wilkes was chosen. This study aimed to assess the severity of temporomandibular joint dysfunction symptoms in women of child-bearing and post-menopausal age according to the C. H. Wilkes classification. Participants and methods. 63 patients were selected: reproductive period n=45 and post-menopausal n=17. Magnetic resonance imaging is described in detail and the diagnosis according to the C. H. Wilkes classification is made. Statistical analysis was carried out by calculating the χ2 test in order to analyze the independence between categorical variables; Kendall's correlation coefficient was applied to assess the correlation between age and disease stages. Results. Diseases of the temporomandibular joint are more common among women of child-bearing age compared to women of postmenopausal age. This may be related to hormonal changes characteristic of the reproductive period: in the group of child-bearing age, there is a greater variety of stages of the disease, while in the group of post-menopausal age, stage IV prevails. This may indicate the influence of age factors on TMJ development. The relationship between age and diseases of the temporomandibular joint has a statistically significant correlation. The results of the χ2 test show a statistically significant relationship between age and TMJ disease stages. In addition, Kendall's correlation coefficient confirms the presence of a moderate degree of relationship between age and stages of the disease. Conclusion. The results of the analysis of the distribution of temporomandibular joint disease stages between age groups can serve as important data for optimizing clinical practice, improving treatment outcomes, and increasing patients' quality of life. For example, our study indicates that stage Ⅱ according to the classification of C. H. Wilkes is more common in women of reproductive age, and stage Ⅳ is more common in women of postmenopausal age. Clinicians should take this dada into account when developing individual treatment plans.