Scale Reduction Research Articles

EFFECTIVENESS OF COGNITIVE-BASED INTERVENTIONS FOR IMPROVING BODY IMAGE OF PATIENTS HAVING BREAST CANCER

Breast cancer is one of the most common tumors among women. CBT is an algorithmic, time-bound method of treatment that concentrates on altering negative cognitive processes and behavioral patterns. Objectives: The main objective of the study is to find the effectiveness of cognitive-based interventions for improving the body image of patients with breast cancer. Methods: This quasi-experimental study was conducted at Khyber Teaching Hospital Peshawar from January 2023 to January 2024. Data were collected from 105 breast cancer patients, all of whom had undergone various treatments such as mastectomy, lumpectomy, or chemotherapy, which resulted in noticeable physical changes. All patients diagnosed with breast cancer and having undergone surgical or medical treatments and experiencing concerns related to body image post-treatment with no prior history of psychiatric disorders were included in the study. Results: Data were collected from 105 patients. The results show that the intervention group experienced a significant improvement in body image, with a 45.6% reduction in Body Image Scale (BIS) scores from 22.8 ± 3.5 pre-intervention to 12.4 ± 3.1 post-intervention (p = 0.001). In contrast, the control group showed only a minimal 3.6% improvement, with scores decreasing slightly from 22.5 ± 3.7 to 21.7 ± 3.4 (p = 0.152). Conclusion: It is concluded that cognitive-based interventions, particularly Cognitive Behavioral Therapy (CBT), are highly effective in improving body image and reducing anxiety and depression in breast cancer patients.

SMLS-YOLO: an extremely lightweight pathological myopia instance segmentation method.

Pathological myopia is a major cause of blindness among people under 50 years old and can result in severe vision loss in extreme cases. Currently, its detection primarily relies on manual methods, which are slow and heavily dependent on the expertise of physicians, making them impractical for large-scale screening. To tackle these challenges, we propose SMLS-YOLO, an instance segmentation method based on YOLOv8n-seg. Designed for efficiency in large-scale screenings, SMLS-YOLO employs an extremely lightweight model. First, StarNet is introduced as the backbone of SMLS-YOLO to extract image features. Subsequently, the StarBlock from StarNet is utilized to enhance the C2f, resulting in the creation of the C2f-Star feature extraction module. Furthermore, shared convolution and scale reduction strategies are employed to optimize the segmentation head for a more lightweight design. Lastly, the model incorporates the Multi-Head Self-Attention (MHSA) mechanism following the backbone to further refine the feature extraction process. Experimental results on the pathological myopia dataset demonstrate that SMLS-YOLO outperforms the baseline YOLOv8n-seg by reducing model parameters by 46.9%, increasing Box mAP@0.5 by 2.4%, and enhancing Mask mAP@0.5 by 4%. Furthermore, when compared to other advanced instance segmentation and semantic segmentation algorithms, SMLS-YOLO also maintains a leading position, suggesting that SMLS-YOLO has promising applications in the segmentation of pathological myopia images.

Scale reduction Transformer-based soft measurement of oil–water two-phase flow

In addressing the challenge of parameter measurement in high-water-content oil–water two-phase flow, we independently develop a dual-helix microwave sensor measurement system. Using this system, we conduct vertically upward experiments on oil–water two-phase flow and collect time-series signals characterizing microwave attenuation. Based on signal characteristics, we design a scale reduction Transformer soft measurement model (SRSM-Transformer). The time filter module effectively facilitates the aggregation and embedding of channel features with diverse physical significance. Additionally, the scale reduction temporal module models global information from a multi-resolution perspective, enabling the model to flexibly extract multi-scale feature information from fluid signals. Demonstrating pronounced superiority over existing models, our proposed model achieves recognition accuracies of 93.63% for total flow rate and 95.73% for water content. This research provides a new direction for modeling complex industrial oil–water two-phase flow systems and measuring multi-coupled key parameters.

Fractal model of the strength of lightweight concrete based on volcanic tuff taking into account the scale effect

The study proposes a fractal model based on B. Mandelbrot's geometry. Mandelbrot geometry to describe the scale effect in concrete. It has been experimentally established that under-loading concrete undergoes degradation of its structure, which is expressed in the sequential destruction of fractals at different scale levels. It was found that the scale reduction leads to an increase in concrete strength: 20x20x20 mm specimens showed the highest strength among all four compositions (23.3-25.3 MPa). The average density of tuff concrete was also investigated: the smallest specimens had a density of 1961.3 kg/m³, while the largest specimens had a density of 1974.2 kg/m³, which is explained by the heterogeneity of the structure and pore distribution. The water permeability of concrete, evaluated through air permeability, showed that specimens with higher air permeability (30.2-30.5 s/cm³) had better water resistance (W14). These data indicate a correlation between air permeability and water resistance, which may be due to the denser structure and improved pore distribution. The study of air permeability makes it possible to predict the durability of concrete structures when exposed to moisture, as well as to improve the quality of building materials and reduce the cost of their operation.

Combined treatment of atrophic scars using radiofrequency microneedling and hyaluronic acid fillers with subcision

Introduction. Atrophic scars may be associated with significant psychological stress and a substantial negative impact on quality of life. Despite the great relevance of the atrophic scars therapy, existing treatment methods do not always provide their complete elimination.Aim. To study the efficacy of combined therapy of atrophic scars with radiofrequency microneedling (RF-MN), subcision and hyaluronic acid filler injection.Materials and methods. Ten female patients aged 28–44 years with a clinical diagnosis of atrophic scars were randomly assigned to two groups. Group 1 received RF-MN alone, while Group 2 received a combination treatment comprising RF-MN, subcision, and hyaluronic acid injections. Clinical effectiveness was assessed using the Goodman-Baron scar rating scale and the Global Aesthetic Improvement Scale (GAIS). Ultrasound was used to determine the changes in dermal thickness. The volume of depressions and skin texture were measured using the Antera 3D®. The safety of the treatment was evaluated by recording adverse events.Results. The combined method demonstrated superior efficacy compared to RF-MN alone in the majority of efficacy parameters. In Group 2, a statistically significant reduction in Goodman-Baron scale was observed in 100% of patients (p = 0.026). 3D measurements of the face demonstrated a more pronounced improvement in skin texture in Group 2 relative to Group 1. Statistically significant changes (p = 0.027) in the Face-Q scale were exclusively observed in the group that received the combined treatment. Ultrasonic imaging demonstrated a restoration of dermal thickness following treatment. No serious adverse events were observed. Expected local adverse events (pain, erythema, swelling, and bruising) were mild and resolved spontaneously within 1–7 days.Conclusion. The combined treatment with RF-MN followed by subcision and hyaluronic acid filler injections demonstrated its efficacy in patients with atrophic scars.

Local Transplantation of Mesenchymal Stromal Cells Is Safe and Could Alleviate Kienböck Disease's Complications: A Clinical Trial Study.

Kienböck disease is a rare condition characterized by severe pain and restricted wrist movement. Various palliative methods have been proposed as therapeutic strategies for alleviating symptoms. Mesenchymal stromal cell transplantation has been suggested as an innovative and promising approach due to its potential for inducing regeneration and immunomodulation in the necrotic tissue. This study aims to evaluate the safety of autologous bone marrow derived mesenchymal stromal cells (BM-MSCs) transplantation after core decompression in Kienböck disease. In this phase I of an open-label clinical trial, three patients (one female and two males) with stage 2 Kienböck disease underwent autologous BM-MSCs transplantation following lunate core decompression. The patients were followed up for six months to assess safety as well as secondary clinical outcomes, including pain level, range of motion (ROM), and functional disability. Safety of BM-MSCs injection following the core decompression was evaluated by recording post-treatment complications during the six-month follow-up. No adverse events (AEs) or severe AEs (SAEs) were reported, indicating that BM-MSCs injection after core decompression is a safe intervention. All patients showed a remarkable reduction in visual analog scale (VAS) scores and "Disabilities of the Arm, Shoulder, and Hand" (DASH) questionnaire scores, suggesting the therapeutic potential of this intervention. Moreover, an increase in the ROM indicated that BM-MSCs transplantation can improve wrist functionality. Additionally, radiographic assessments before and after cell infusion demonstrated a reduction in lunate sclerosis after six months of follow-up. The transplantation of autologous BM-MSCs following lunate core decompression seems to be a safe clinical intervention and may lead to pain relief in patients with Kienböck disease. Furthermore, this procedure may help prevent disease progression during the follow-up period (registration number: NCT02646007).

A double-blinded randomised control study to compare the effectiveness and safety of intralesional vitamin D3 with intralesional triamcinolone and its correlation with tissue expression of vitamin D receptors in patients with keloid.

Intralesional steroids commonly used for keloid treatment have adverse effects like cutaneous atrophy and telangiectasias. Safer and more effective therapies are needed. Preliminary studies suggest intralesional vitamin D as a potential alternative treatment. The aim of this study was to compare efficacy and safety of intralesional vitamin D with triamcinolone for keloids, and correlate tissue expression of vitamin D receptors (VDRs) with treatment outcomes. Sixty patients were randomly assigned to two groups: Group A (intralesional vitamin D) and Group B (intralesional triamcinolone). Four injections were given at 4-week intervals, with an 8-week follow-up. Biopsies were taken pre- and post-treatment to examine VDR expression levels and treatment response correlation. The primary outcome of interest was the proportion of patients achieving a 50% reduction in Vancouver Scar Scale (VSS). Secondary outcomes included incidence of adverse effects, and changes in VDR expression before and after treatment. Baseline VSS scores were 9.73 ± 1.01 (vitamin D group) and 10.13 ± 1.07 (triamcinolone group). After treatment, mean VSS decreased to 5.17 ± 0.59 (vitamin D group, p < 0.001) and 4.77 ± 0.77 (triamcinolone group, p < 0.001), with significantly better response in latter (p = 0.03). More than 50% reduction in VSS score was higher in the triamcinolone group (76.7% vs. 50%, p = 0.032). No recurrences were noted during the 8-week follow-up. Hypopigmentation (80% vs. 36.7%, p < 0.001) and atrophy (73.3% vs. 40%, p = 0.009) were more common in the triamcinolone group. No significant difference in pre- and post-treatment VDR receptor expression was observed in either group. Both triamcinolone acetonide and vitamin D were effective for keloids. Triamcinolone was more efficacious, whereas vitamin D was safer, suggesting it as a viable alternative for keloid management.

Multimodal Analgesia Approach in Acute Low Back Pain Management: A Phase III Study of a Novel Analgesic Combination of Etoricoxib/Tramadol.

Pain and disability management are crucial for a speedy recovery. Combining analgesics with different mechanisms of action provides greater pain relief with lower doses, promoting efficient multimodal analgesia. This study evaluated the efficacy and safety between two fixed-dose combinations (FDC): etoricoxib/tramadol compared to paracetamol/tramadol for the management of acute low back pain (LBP) in a 7-day treatment. We conducted a phase IIIb, prospective, randomized, and multicenter study in patients with acute LBP treated with etoricoxib 90mg/tramadol 50mg (one packet of granules diluted in 100ml of water, once a day [QD], for 7 days) or paracetamol 975mg/tramadol 112.5mg (one tablet of 325mg/37.5mg, three times a day [TID], for 7 days) to assess the efficacy (in terms of pain and disability improvement) and safety. One hundred and twenty-four patients were randomized to receive either etoricoxib/tramadol QD (n = 61) or paracetamol/tramadol TID (n = 63). From the magnitude of change in pain evaluations, differences were observed between the treatment groups at 3 [p = 0.054, CI 95% -0.648 (-0.010 to 1.306)] and 5days (p = 0.041). The proportion of patients with a 30% reduction in Visual Analogue Scale (VAS) score was statistically significant when comparing the treatment groups on the third day of follow-up [p = 0.008, CI 95% 0.241 (0.061-0.421)]. An improvement in LBP's disability to perform activities of daily routine (Oswestry and Roland-Morris questionnaires) was observed in both treatment groups. A total of 79 adverse events (AEs) (38 [48.1%] with etoricoxib/tramadol and 41 [51.9%] with paracetamol/tramadol) were reported. The most frequent AEs were nausea (17.7%) and dizziness (16.4%). The results show the clinical benefits of etoricoxib/tramadol FDC, such as the sparing effect of tramadol dose per day, early therapeutic response rate compared with paracetamol/tramadol; which translates into faster pain relief, better adherence, less tramadol drug dependency, and a reduction of related AEs incidence. ClinicalTrials.gov identifier, NCT04968158.

Efficacy of a Religious-Based Slow Deep Breathing Technique in Reducing Postoperative Pain: A Quasi-Experimental Study

Non-pharmacological methods offer a noninvasive solution for postoperative pain reduction, enhancing patient quality of life, and expediting recovery post-surgery. The aim of this study was to analyze differences in pain scale reduction in postoperative patients after administering slow deep breathing distraction-relaxation techniques with a religious approach. The design was experimental with pre- and post-tests by providing treatment to respondents using slow deep breathing exercises with a religious approach (the activity related to relaxation using sentences and special treatment explained in the data collection section) to postoperative patients. Pain scale scores ranged from 0 to 10. The total number of participants was 60 (laparotomy, mastectomy, or fracture surgery). A dependent t-test was used to analyse data . The pain scale score for patients after slow deep breathing surgery with a religious approach ranged from 4 to 10 on a numerical rating scale. The average reduction in pain scale score for patients after slow deep breathing surgery with a religious approach was 2.17 with a standard deviation of 0.994. The results of the statistical tests with the dependent t-test obtained a p-value of 0.000. This shows a significant reduction in pain levels among postoperative patients who perform slow deep breathing exercises with a religious approach. These findings suggest that this method is an effective and accessible way to manage postoperative pain. In conclusion, slow deep breathing with a religious approach is effective in reducing postoperative pain

What do we learn from impurities and disorder in high-Tc cuprates?

A series of experimental studies established that the differing morphologies of the phase diagrams versus hole doping nh of the various cuprate families are mostly controlled by defects and disorder. In the minimally disordered cuprate Yttrium Baryum Copper Oxide (YBCO) we introduced controlled detfects that allowed us to probe the metallic and superconducting states. We demonstrate that the extent of the spin glass phase and the superconducting dome can be controlled by the concentration of spinless (Zn, Li) impurities substituted on the planar Cu sites. NMR frequency shift measurements establish that these defects induce, in their vicinity, a cloud with a Kondo-like paramagnetic behavior. Its “Kondo” temperature and spatial extent differ markedly between the pseudogap and strange metal regimes. We have performed transport measurements on single crystals with a controlled content of in-plane vacancies introduced by electron irradiation. At high T, the inelastic scattering of the carriers has been found independent of disorder and completely governed by the excitations of the correlated electronic state. The low T upturns in the resistivity associated with single-site Kondo-like scattering are qualitatively in agreement with local magnetism induced by spinless impurities. The apparent metal insulator crossover is only detected for a very large defect content, and part of the large resistivity upturn remains connected with Kondo-like paramagnetism. In the superconducting state, the defect-induced reduction of Tc scales linearly with the increase in residual resistivity induced by disorder. High-field magnetoresistance experiments permit us to determine the paraconductivity due to superconducting fluctuations. The latter vanishes beyond a temperature T’c and a field H’c that both decrease with increasing in-plane defect content. In the pseudogap regime, the weaker decrease of T’c with respect to that of Tc reveals a large loss of superconducting phase coherence in the presence of disorder. In light of our experimental results, we initiate a discussion of its interplay with pair breaking. Our data also permit us to confirm that the differing phase diagrams are due to competing orders or disorders that are family-specific. In the ideal phase diagram of a disorder-free cuprate, 2D superconductivity should persist at low doping. This ensemble of experimental results provides serious challenges for the theoretical understanding of superconductivity in these correlated electron systems.

Intradermal Injection of a Thermoresponsive Polymeric Dexamethasone Prodrug (ProGel-Dex) Ameliorate Dermatitis in an Imiquimod (IMQ)-Induced Psoriasis-like Mouse Model.

Psoriasis is a chronic immune-mediated inflammatory skin disease, affecting ∼ 3% of the US population. Although multiple new systemic therapies have been introduced for the treatment of psoriatic skin disease, topical and intralesional glucocorticoids (GCs) continue to be used as effective psoriasis therapies. Their clinical utility, however, has been hampered by significant adverse effects, including skin atrophy and pigmentation as well as elevated blood glucose levels and hypertension. To mitigate these limitations, we have developed a N-(2-hydroxypropyl) methacrylamide (HPMA) copolymer-based thermoresponsive dexamethasone (Dex) prodrug (ProGel-Dex) and assessed its therapeutic efficacy and safety in an imiquimod (IMQ)-induced psoriasis-like (PL) mouse model. ProGel-Dex was intradermally administered once at three dosing levels: 0.5, 1.0, and 2.0 mg/kg/day Dex equivalent at the beginning of the study. PL mice were also treated with daily topical saline or Dex, which were used as control groups. Treatment of PL mice with ProGel-Dex dosed at 0.5 mg/kg/day resulted in a significant reduction in scaling and erythema. Improvement in gross pathology scores, skin histological scores, and serum cytokine levels was also observed. Interestingly, for mice treated with ProGel-Dex at 1.0 and 2.0 mg/kg/day Dex equivalent, only improvement in skin erythema was observed. GC-associated side effects, such as elevation of serum alanine aminotransferase (ALT) and amylase levels and body weight loss, were not observed in mice treated with ProGel-Dex at 0.5 and 1.0 mg/kg/day Dex equivalent. Collectively, these results demonstrate the efficacy and improved safety of ProGel-Dex in treating psoriatic skin lesions when compared to topical Dex treatment, supporting its translational potential for clinical management of lesional skin psoriasis.

Carbon trading mechanism and industrial pollution behavior: A study based on regression discontinuity design analysis

This study investigates the impact of environmental regulations, specifically the carbon trading mechanism, on industrial pollution reduction. Framed within a comprehensive theoretical framework, the research hypotheses explore the influence of the carbon trading mechanism and its interaction with carbon emission trading scale on pollution reduction in industrial enterprises. The study employs Regression Discontinuity Design (RDD) and introduces control variables to provide a nuanced understanding of the relationships.Results indicate a significant impact of the carbon trading mechanism on pollution reduction. This study contributes to understanding the intricate relationships between policy implementation, trading scale, and industrial pollution reduction.

A Bisimulation-Based Foundation for Scale Reductions of Continuous-Time Markov Chains

A Bisimulation-Based Foundation for Scale Reductions of Continuous-Time Markov Chains

Optimization of indirect wastewater characterization using led spectrophotometry: a comparative analysis of regression, scaling, and dimensionality reduction methods

LED spectrophotometry is a robust technique for the indirect characterization of wastewater pollutant load through correlation modeling. To tackle this issue, a dataset with 1300 samples was collected, from both raw and treated wastewater from 45 wastewater treatment plants in Spain and Chile collected over 4 years. The type of regressor, scaling, and dimensionality reduction technique and nature of the data play crucial roles in the performance of the processing pipeline. Eighty-four pipelines were tested through exhaustive experimentation resulting from the combination of 7 regression techniques, 3 scaling methods, and 4 possible dimensional reductions. Those combinations were tested on the prediction of chemical oxygen demand (COD) and total suspended solids (TSS). Each pipeline underwent a tenfold cross-validation on 15 sub-datasets derived from the original dataset, accounting for variations in plants and wastewater types. The results point to the normalization of the data followed by a conversion through the PCA to finally apply a Random Forest Regressor as the combination which stood out These results highlight the importance of modeling strategies in wastewater management using techniques such as LED spectrophotometry.

A data-driven probabilistic evaluation method of hydrogen fuel cell vehicles hosting capacity for integrated hydrogen-electricity network

The growing demand for hydrogen in hydrogen fuel cell vehicles (HFCVs) will present challenges for the safe operation of the integrated distributed hydrogen supply network (DHSN) and power distribution network (PDN). This paper proposes a data-driven probabilistic evaluation method for determining the hosting capacity of hydrogen fuel cell vehicles (HVHC). Firstly, a directional mapping method is proposed to model the maximum safety boundaries of critical electrolyzers. It integrates the thermal-electrical and dynamic operating characteristics while maintaining the full boundaries in dimension reduction to ensure accuracy and efficiency. A probabilistic HVHC evaluation model is developed to consider uncertain factors of high dimensions despite data deficiency, such as HFCV refueling demand and renewable power. The proposed model determines the maximum network tolerance for the HFCV number, constrained by the safety constraints of the PDN integrated with DHSN, on-site and off-site hydrogen supplies coupled by tube trailers. Finally, a cross-term decoupled data-driven polynomial chaos expansion is proposed to efficiently solve the developed probabilistic HVHC model. It is established based on raw and small samples without extracted probability distribution information. The solution approach also combines the cross-terms in expansions using Taylor expansion, making it efficient for high-dimensional problems. Furthermore, the accuracy and scale reduction effect of the solution algorithm are proven based on Wasserstein ambiguity sets. Numerical studies on three systems show that the proposed method has only a 0.01% error in HVHC results and an 8.38% computation time of the Monte Carlo method.

Does Electroencephalography Seizure Duration Account for an Adequate Treatment of Magnetic Seizure Therapy for Schizophrenia?

A seizure lasting >15 s has been considered to indicate treatment for magnetic seizure therapy (MST), a modification of electroconvulsive therapy (ECT), without much validation. This study aimed to investigate whether this seizure duration was suitable for the treatment of schizophrenia. Altogether, 34 and 33 in-patients with schizophrenia received 10 sessions of MST and ECT, respectively. Clinical symptoms were assessed using the Positive and Negative Symptom Scale at baseline and at the 4-week follow-up. Electroencephalogram (EEG) was monitored during each MST or ECT treatment using bifrontal electrodes. The proportion of participants who achieved the 15-second threshold was only 28.6% in the MST group, with a significant difference between responders and nonresponders. For patients receiving MST, the average EEG seizure duration correlated with the percentage of Positive and Negative Symptom Scale reduction (t(32) = 2.51, P = 0.017, uncorrected; t(32) = 2.00, P = 0.055, corrected with clinical characteristics). The average EEG seizure duration predicted the clinical response at a trend level (Z = 1.76, P = 0.078) with an optimal cutoff of 11.3 seconds. All patients in the ECT group achieved the 15-second threshold. However, their average EEG seizure duration was uncorrelated with clinical improvement. The duration of EEG seizures may be associated with the antipsychotic effects of MST. This association may have been influenced by various clinical and technical factors. More research is needed to define the specific criteria for adequate MST in schizophrenia in order to achieve personalized dosing.

Alzheimer's disease with depressive symptoms: Clinical effect of intermittent theta burst stimulation repetitive transcranial magnetic stimulation

BACKGROUND Alzheimer's disease (AD), characterized by the ongoing deterioration of neural function, often presents alongside depressive features and greatly affects the quality of life of individuals living with the condition. Although several treatment methods exist, their efficacy is limited. In recent years, repetitive transcranial magnetic stimulation (rTMS) utilizing the theta burst stimulation (TBS) mode, specifically the intermittent TBS (iTBS), has demonstrated promising therapeutic potential in the management of neuropsychiatric disorders. AIM To examine the therapeutic efficacy of iTBS mode of rTMS for treating depressive symptoms in patients with AD. METHODS This retrospective study enrolled 105 individuals diagnosed with AD with depressive symptoms at Huzhou Third Municipal Hospital, affiliated with Huzhou University, between January 2020 and December 2023. Participants received standard pharmacological interventions and were categorized into control (n = 53) and observation (n = 52) groups based on treatment protocols. The observation group received iTBS mode of rTMS, while the control group received pseudo-stimulation. A comparative analysis evaluated psychological well-being, adverse events, and therapeutic at initiation of hospitalization (T0) and 15 days post-treatment (T1). RESULTS At T1, both groups exhibited a marked reduction in self-rating depression scale and Hamilton depression scale scores compared to T0. Furthermore, the observation group showed a more pronounced decrease than the control group. By T1, the Mini-mental state examination scores for both groups had increased markedly from their initial T0 assessments. Importantly, the increase was particularly more substantial in the observation group than in the control group. Fourteen patients in the control group had ineffective treatment effects, while five patients in the observation group experienced the same. Additionally, the observation group experienced a substantially reduced incidence of ineffective treatment as compared to the control group (both P &lt; 0.05); there were no recorded serious adverse events in either group. CONCLUSION The iTBS model of rTMS effectively treated AD with depression, improving depressive symptoms and cognitive function in patients without serious adverse reactions, warranting clinical consideration.

Protocol for the development and validation of a machine-learning based tool for predicting the risk of hypertriglyceridemia in critically-ill patients receiving propofol sedation.

Introduction Propofol is a widely used sedative-hypnotic agent for critically-ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical benefits, propofol is associated with increased risks of hypertriglyceridemia. Early identification of patients at risk for propofol-associated hypertriglyceridemia is crucial for optimizing sedation strategies and preventing adverse outcomes. Machine learning (ML) models offer a promising approach to predict individualized patient risks of propofol-associated hypertriglyceridemia. Methods and analysis We propose the development of a ML model aimed at predicting the risk of propofol-associated hypertriglyceridemia in ICU patients receiving IMV. The study will utilize retrospective data from four Mayo Clinic sites. Nested cross-validation (CV) will be employed, with a 10-fold inner CV loop for model tuning and selection as well as an outer loop using leave-one-site-out CV for external validation. Feature selection will be conducted using Boruta and LASSO-penalized logistic regression. Data preprocessing steps include missing data imputation, feature scaling, and dimensionality reduction techniques. Six ML algorithms will be tuned and evaluated. Bayesian optimization will be used for hyperparameter selection. Global model explainability will be assessed using permutation importance, and local model explainability will be assessed using SHAP. Ethics and dissemination The proposed ML model aims to provide a reliable and interpretable tool for clinicians to predict the risk of propofol-associated hypertriglyceridemia in ICU patients. The final model will be deployed in a web-based clinical risk calculator. The model development process and performance measures obtained during nested cross-validation will be described in a study publication to be disseminated in a peer-reviewed journal. The proposed study has received ethics approval from the Mayo Clinic Institutional Review Board (IRB #23-007416).

Effects of Statistical Practices for Longitudinal Group Comparison of the Penetration-Aspiration Scale on Power and Effect Size Estimation: A Monte Carlo Simulation Study.

Multiple bolus trials are administered during clinical and research swallowing assessments to comprehensively capture an individual's swallowing function. Despite valuable information obtained from these boluses, it remains common practice to use a single bolus (e.g., the worst score) to describe the degree of dysfunction. Researchers also often collapse continuous or ordinal swallowing measures into categories, potentially exacerbating information loss. These practices may adversely affect statistical power to detect and estimate smaller, yet potentially meaningful, treatment effects. This study sought to examine the impact of aggregating and categorizing penetration-aspiration scale (PAS) scores on statistical power and effect size estimates. We used a Monte Carlo approach to simulate three hypothetical within-subject treatment studies in Parkinson's disease and head and neck cancer across a range of data characteristics (e.g., sample size, number of bolus trials, variability). Different statistical models (aggregated or multilevel) as well as various PAS reduction approaches (i.e., types of categorizations) were performed to examine their impact on power and the accuracy of effect size estimates. Across all scenarios, multilevel models demonstrated higher statistical power to detect group-level longitudinal change and more accurate estimates compared to aggregated (worst score) models. Categorizing PAS scores also reduced power and biased effect size estimates compared to an ordinal approach, though this depended on the type of categorization and baseline PAS distribution. Multilevel models should be considered as a more robust approach for the statistical analysis of multiple boluses administered in standardized swallowing protocols due to its high sensitivity and accuracy to compare group-level changes in swallowing function. Importantly, this finding appears to be consistent across patient populations with distinct pathophysiology (i.e., PD and HNC) and patterns of airway invasion. The decision to categorize a continuous or ordinal outcome should be grounded in the clinical or research question with recognition that scale reduction may negatively affect the quality of statistical inferences in certain scenarios.

The efficacy of the 5E rehabilitation nursing model combined with mindfulness training on alleviating psychological distress and modulating coping styles in patients with acute myocardial infarction post-PCI: An observation study.

To explore the influence of the 5E rehabilitation nursing model integrated with mindfulness training on mitigating psychological distress and adjusting coping styles in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI). The clinical data of 94 patients with AMI who underwent PCI from August 2020 to January 2022 were retrospectively analyzed. Patients were divided into 2 groups based on different nursing modes. Among them, 47 cases received routine interventions were categorized into the control group, and 47 cases received the 5E rehabilitation nursing model integrated with mindfulness training on the basis of routine interventions were categorized into the study group. After 3 months of intervention, both groups exhibited a significant reduction in Self-Rating Anxiety Scale and Depression Scale scores compared to the pre-intervention period, with the study group demonstrating lower scores than the control group (P < .05). Herth Hope Index scores significantly improved in both groups after intervention, with the study group exhibiting higher scores than the control group (P < .05). After 3 months of interventions, Self-Care Agency scores significantly elevated in both groups, with the study group demonstrating higher scores than the control group (P < .05). WHO Quality of Life-BREF scores significantly improved in both groups, with the study group demonstrating higher scores than the control group (P < .05). The study group exhibited higher compliance and satisfaction levels and lower complication rate compared to the control group (P < .05). Integrating the 5E rehabilitation nursing model with mindfulness training effectively alleviates psychological distress, ameliorates quality of life, and improves satisfaction in AMI patients after PCI.