Impact Patient Outcomes Research Articles

Clinician-reported challenges associated with delivery of exposure with response prevention for patients with obsessive-compulsive disorder

Exposure with response prevention (E/RP) within cognitive behavior therapy (CBT) is recognized as a critical therapeutic element that drives clinical improvement in the behavioral treatment of obsessive-compulsive disorder (OCD). However, many clinicians encounter a number of barriers when implementing E/RP for patients with OCD, negatively impacting patient outcomes. To understand and better address these challenges, we conducted a survey with 228 clinicians to capture the experiences of mental health providers that use E/RP to treat patients with OCD, and identify challenges they may experience when implementing this form of evidence-based care. We found that the majority of clinicians sampled endorsed facing barriers in implementing E/RP for patients with OCD. Additionally, we found that specific OCD symptom domains were identified by clinicians as difficult to complete exposures for within and between treatment sessions. Ultimately, this investigation identifies some of the challenges faced by clinicians using E/RP to treat patients with OCD, and offers several future research directions to pave the way toward addressing these barriers and improving treatment outcomes.

The impact of injuries at the time of cardiac arrest on the prognosis of extracorporeal cardiopulmonary resuscitation (ECPR) in out-of-hospital cardiac arrest patients

AimExtracorporeal cardiopulmonary resuscitation (ECPR) is an effective treatment for out-of-hospital cardiac arrest and refractory ventricular fibrillation. Despite the success of this intervention, trauma is a potential complication that may adversely impact patient outcomes. This study assessed the incidence and impact of trauma in patients who underwent ECPR. We hypothesized that all trauma incurred until the conclusion of ECPR would have a significant negative effect on survival and neurological outcomes. MethodsThis retrospective observational study examined all ECPR patients admitted to a tertiary emergency medical center between January 2015 and December 2021. All patients underwent pan-scan computed tomography (CT) before admission to the intensive care unit. The head and body trauma were assessed from CT images taken after ECPR. Trauma was defined as all trauma affecting post-ECPR management. In other words, all trauma caused by collapse, trauma caused by resuscitative actions such as chest compressions, and vascular injuries associated with ECPR were included. Univariate analysis of neurological prognosis and 30-day survival due to complicated trauma was performed. ResultsA total of 189 patients (mean age 55.2 ± 13.4 years; 85.2% male) were included in this study. Four patients (2.1%) had head trauma, and 31 patients (16.4%) had torso trauma. All patients with head trauma died during extracorporeal membrane oxygenation management. In patients with torso trauma, 30-day survival was not significantly different compared with that in those without trauma (31.5% vs. 41.9%, P = 0.60); good neurological outcomes were almost the same (26.0% vs. 25.8%, P = 1.00). Approximately half of the patients with torso trauma (48%) underwent transarterial embolization. ConclusionPatients treated with ECPR can suffer a variety of traumatic injuries from the time of collapse to the establishment of ECMO. Head trauma may be lethal and warrants caution. With appropriate treatment, patients with torso trauma may have an equivalent prognosis to those without traumatic complications.

Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostatectomy (RARP), early in their training. VUA assessment and training significantly impact patient outcomes and have high educational value. This study aimed to develop objective prediction models for the Robotic Anastomosis Competency Evaluation (RACE) metrics using electroencephalogram (EEG) and eye-tracking data. Data were recorded from 23 participants performing robot-assisted VUA (henceforth ‘anastomosis’) on plastic models and animal tissue using the da Vinci surgical robot. EEG and eye-tracking features were extracted, and participants’ anastomosis subtask performance was assessed by three raters using the RACE tool and operative videos. Random forest regression (RFR) and gradient boosting regression (GBR) models were developed to predict RACE scores using extracted features, while linear mixed models (LMM) identified associations between features and RACE scores. Overall performance scores significantly differed among inexperienced, competent, and experienced skill levels (P value < 0.0001). For plastic anastomoses, R2 values for predicting unseen test scores were: needle positioning (0.79), needle entry (0.74), needle driving and tissue trauma (0.80), suture placement (0.75), and tissue approximation (0.70). For tissue anastomoses, the values were 0.62, 0.76, 0.65, 0.68, and 0.62, respectively. The models could enhance RARP anastomosis training by offering objective performance feedback to trainees.

Advancing arrhythmia education through the CDIO approach: a new paradigm in nursing student training

BackgroundThe accurate diagnosis and effective management of arrhythmias are crucial, with nurses playing a key role in the early detection and treatment, significantly impacting patient outcomes. Improving education on arrhythmias among nurses, especially in critical care and perioperative settings, can enhance patient safety and the quality of care.MethodsA total of 116 trainee nurses were randomly divided into two groups: one utilizing the conceive-design-implement-operate (CDIO) model and the other employing a traditional lecture-based learning (LBL) method, to undergo arrhythmia training. The studyassessed the effects of the two teaching methods and investigated the students’ attitudes toward these educational practices, with all participants completing pre- and post-course tests.ResultsThe CDIO model significantly enhances nursing students’ arrhythmia proficiency, yielding higher test scores and sustained improvement after 24-week compared to the traditional LBL method, alongside markedly better self-learning enthusiasm, understanding, satisfaction with the teaching approach and effectiveness, and interest in learning arrhythmia. The CDIO model in nursing arrhythmia courses boosts theoretical knowledge and application, showing potential in clinical skill enhancement.ConclusionsOur study introduces the CDIO model in nursing arrhythmia courses, with improvement in knowledge and skills, and promise for broader application.

Bayesian process mapping for intraoperative decision making in laparoscopic cholecystectomy

Aim: Surgeon’s intraoperative decisions significantly impact patient outcomes. In the reconciliation cycle, interoperative decisions are guided by probabilistic reasoning, which is informed by the evolving intraoperative features. This paper aims to compare the utility of a traditional logistic regression (LR) model for critical view of safety (CVS) achievement to Bayesian network (BN) maps using intraoperative features. It hypothesizes that BN mapping better integrates with surgeon heuristics. Methods: Using prospectively gathered intraoperative data, BN maps were developed and tested to determine their ability to predict critical view of safety achievement. Performance was compared to traditional logistic regression models to consider their utility in practice. Results: In total, 4,663 patients were identified. Of these patients, 2,837 (61%) presented acutely and 3,122 (67%) were female. CVS was achieved in 4,131 (92%) of patients. In total, four BN were developed. Optimal performance was seen in model 2 with an AUC of 0.879 (0.798-0.960) (P &lt; 0.001). Selecting a cut-off of 0.6 gave an optimized sensitivity of 99% and a specificity of 45% for CVS achievement. In comparison to this, for the combined acute LR model, ROC curve analysis gave an AUC of 0.829 (0.787-0.872 ) (P &lt; 0.001). A cut-off of 75% probability resulted in a sensitivity of 95% and a specificity of 38% for CVS achievement. Conclusion: The present study illustrates how BN modeling can map to surgeon decision making to facilitate reasoning in complex environments. Further work is needed to facilitate data capture and implementation. Despite this, they represent a promising avenue for intuitive decision support tools.

Nursing Teamwork: An in-Depth Concept Analysis with Walker &amp; Avant’s Framework

Background: Nursing teamwork is fundamental for delivering high-quality patient care. Successful teamwork includes communication, collaboration, trust, respect, shared decision-making, accountability, and flexibility among healthcare professionals. Objective: The purpose of this concept analysis is to clarify and define the concept of teamwork in nursing, providing nurses with a comprehensive understanding to enhance healthcare delivery. Methods: This study employed a concept analysis using Walker and Avant’s model (1986) to elucidate the significance, characteristics, antecedents, consequences, and empirical referents of teamwork in nursing. Data collection involved a comprehensive literature review of peer-reviewed journals, books, and authoritative online resources. Data were synthesized to identify core themes and patterns related to defining attributes, antecedents, and consequences of teamwork. The ethical considerations were aligned with the Declaration of Helsinki. Data analysis was conducted using SPSS version 25.0, with descriptive statistics summarizing the defining attributes, antecedents, and consequences. Frequencies and percentages were calculated for categorical variables, while means and standard deviations were used for continuous variables. Results: The analysis identified seven key attributes of effective nursing teamwork: communication, collaboration, trust, respect, shared decision-making, accountability, and flexibility. Antecedents included clear roles and responsibilities, open communication, mutual trust and respect, shared goals, cultural competence, and adequate resources. Positive consequences included improved patient outcomes (e.g., 20% reduction in hospital stays), enhanced patient satisfaction (increased by 30%), increased efficiency (20% faster service delivery), and improved staff satisfaction (25% decrease in burnout rates). Negative consequences of poor teamwork included poor patient outcomes, reduced patient satisfaction, increased healthcare costs (by 15%), and staff burnout. Empirical referents included teamwork assessment tools, patient outcomes, reduced healthcare costs, reduced medical errors (by 10%), and improved quality of care. Conclusion: Effective teamwork is integral to nursing practice and significantly impacts patient outcomes, staff satisfaction, and healthcare delivery. Fostering communication, collaboration, and mutual respect among healthcare professionals is essential. Education and training, supportive work environments, patient-centered care, and inter-professional collaboration are critical for enhancing teamwork. Healthcare policies should emphasize quality improvement, patient safety, and workforce development to promote effective teamwork in nursing.

Discoid meniscus: Treatment considerations and updates.

A discoid meniscus is a morphological abnormality wherein the meniscus loses its normal 'C' shape. Although most patients are asymptomatic, patients might still present with symptoms such as locking, pain, swelling, or giving way. Magnetic resonance imaging is usually needed for confirmation of diagnosis. Based on a constellation of factors, including clinical and radiological, different approaches are chosen for the management of discoid meniscus. The purpose of this review is to outline the treatment of discoid meniscus, starting from conservative approach, to the different surgical options for this condition. The PubMed and Google Scholar databases were used for this review. Studies discussing the treatment of discoid meniscus from 2018 to 2023 were searched. Initially there were 369 studies retrieved, and after removal of studies using the exclusion criteria, 26 studies were included in this review. Factors such as stability, presence of tear, and morphology can help with surgical planning. Many approaches have been used to treat discoid meniscus, where the choice is tailored for each patient individually. Postoperatively, factors that may positively impact patient outcomes include male sex, body mass index < 18.5, age at symptom onset < 25 years, and duration of symptoms < 24 months. The conventional approach is partial meniscectomy with or without repair; however, recently, there has been an increased emphasis on discoid-preserving techniques such as meniscoplasty, meniscopexy, and meniscal allograft transplantation.

Children's Hospital Resource Utilization During the 2022 Viral Respiratory Surge.

Multiple viral respiratory epidemics occurred concurrently in 2022 but their true extent is unclear. To aid future surge planning efforts, we compared epidemiology and resource utilization with prepandemic viral respiratory seasons in 38 US children's hospitals. We performed a serial cross-sectional study from October 2017 to March 2023. We counted daily emergency department (ED), inpatient, and ICU volumes; daily surgeries; viral tests performed; the proportion of ED visits resulting in revisit within 3 days; and proportion of hospitalizations with a 30-day readmission. We evaluated seasonal resource utilization peaks using hierarchical Poisson models. Peak volumes in the 2022 season were 4% lower (95% confidence interval [CI] -6 to -2) in the ED, not significantly different in the inpatient unit (-1%, 95% CI -4 to 2), and 8% lower in the ICU (95% CI -14 to -3) compared with each hospital's previous peak season. However, for 18 of 38 hospitals, their highest ED and inpatient volumes occurred in 2022. The 2022 season was longer in duration than previous seasons (P < .02). Peak daily surgeries decreased by 15% (95% CI -20 to -9) in 2022 compared with previous peaks. Viral tests increased 75% (95% CI 69-82) in 2022 from previous peaks. Revisits and readmissions were lowest in 2022. Peak ED, inpatient, and ICU volumes were not significantly different in the 2022 viral respiratory season compared with earlier seasons, but half of hospitals reached their highest volumes. Research on how surges impact boarding, transfer refusals, and patient outcomes is needed as regionalization reduces pediatric capacity.

Standardizing clinician training and patient care in the neonatal neurocritical care: A step-by-step guide

Neonatal neurocritical care (NNCC) has emerged as an important specialty to address neurological conditions affecting newborns including a wide spectrum of brain injuries and developmental impairment. Despite the discipline's growth, variability in NNCC service delivery, patient care, and clinical training poses significant challenges and potentially adversely impacts patient outcomes. Variations in neuroprotective strategies, postnatal care, and training methodologies highlight the urgent need for a unified approach to optimize both short- and long-term neurodevelopmental outcomes for these vulnerable population. This paper presents strategic blueprints for establishing standardized NNCC clinical care and training programs focusing on collaborative effort across medical and allied health professions. By addressing these inconsistencies, the paper proposes that standardizing NNCC practices can significantly enhance the quality of care, streamline healthcare resource utilization, and improve neurodevelopmental outcome, thus paving the way for a new era of neonatal neurological care.

Early Postoperative Small Bowel Obstruction after Colorectal Surgery: Incidence and Exploratory Analysis of Potential Risk Factors.

Early postoperative small bowel obstruction (EPSBO) is a common complication following colorectal surgery, which can significantly impact patient outcomes. This study aimed to investigate the incidence of EPSBO and identify potential risk factors among patients who underwent colorectal surgery. A descriptive study was conducted on a cohort of 100 patients who underwent colorectal surgery at a tertiary center at SKIMS, Srinagar, Jammu & Kashmir, India. Descriptive, bivariate, and predictive screening analyses were performed to examine patient characteristics, assess association between different relevant variables and EPSBO, and identify significant predictors, respectively. Our study included a total of 100 patients, with a mean age of 50.39 years. Postsurgery, 11% of the individuals in the cohort developed EPSBO. Early postoperative small bowel obstruction developed around 4.30 days after surgery, and radiographic data revealed dilated gut loops in 72.70% of EPSBO cases. Bivariate analysis revealed significant association between EPSBO and variables such as previously operated, medical comorbidities, smoking status, anemia, neoadjuvant chemoradiotherapy (NACRT), bowel preparation, operative procedure, surgery duration, and type of anastomosis (p < 0.05). History of previous bowel habits, previously operated, perioperative bowel preparation, and blood transfusion were identified as the most influential predictors of EPSBO in the predictive screening study. This study provides insights into the incidence of EPSBO and its potential risk factors for postcolorectal surgery among patients. The findings emphasize the need to take the patient's history of past bowel habits and other factors into account when determining the risk of EPSBO. Future studies should go deeper into these correlations and consider treatments to reduce the occurrence of EPSBO in this patient population. Ahmad B, Ul Hag MF, Shah MA, et al. Early Postoperative Small Bowel Obstruction after Colorectal Surgery: Incidence and Exploratory Analysis of Potential Risk Factors. Euroasian J Hepato-Gastroenterol 2024;14(1):70-74.

3D printed dosimeter incorporating leuco-crystal violet and PMMA

This paper describes the development of 3D-printed dosimeters made from radiochromic materials. Incorporating polymethyl methacrylate (PMMA) as a transparent polymer matrix and leuco-crystal violet as a radiochromic dye, these dosimeters exhibit a color change when exposed to radiation. This change provides a way to visualize and measure three-dimensional dose distributions, which is important for the accurate verification of radiation doses in radiotherapy. The use of 3D printing technology allows these dosimeters to approximate human organ geometries, which may contribute to safer and more effective radiotherapeutic applications. The dosimeters can be customized into various shapes and sizes, are lightweight, and cost-effective, making them appropriate for use in both clinical and research settings in radiotherapy. The fabrication process is detailed, and the dosimeters have been tested at doses up to 100 Gy in X-ray irradiation and analyzed for dose distribution. Bragg-peak measurements from carbon beam irradiation illustrate the dosimeters' capability to detect peak radiation doses with a spatial resolution of approximately 1 mm. These findings indicate the potential of these 3D printed dosimeters to improve the accuracy of radiation delivery, which could positively impact patient outcomes in radiotherapy.

Romiplostim for chemotherapy induced thrombocytopenia in solid tumors: A meta-analysis.

e24137 Background: Chemotherapy-induced thrombocytopenia (CIT), defined as platelets &lt; 100,000/mcL persisting for ≥3-4 weeks post-chemotherapy affects 20-25% of cases necessitating platelet transfusions or dose reductions leading to treatment delays and impacting patient outcomes. (1,2) Despite multiple studied agents, there are no established guidelines. Romiplostim, a thrombopoietin receptor agonist approved for immune thrombocytopenic purpura, stands out. NCCN suggests its use, but pooled analyses are lacking. Our meta-analysis addresses this gap, exploring romiplostim's efficacy in CIT management. Methods: We performed a systematic search of PUBMED, EMBASE, and COCHRANE databases for studies that evaluate the use of romiplostim in the setting of CIT for solid tumors. The primary endpoint was the proportion of patients that showed improvement in platelet counts in response to romiplostim. Secondary endpoints were the proportion of patients that continued full dose chemotherapy dose on romiplostim and incidence of thromboembolic events. Pooled proportions were calculated along with 95% confidence intervals (CI) using a random-effects model. I2 statistic was used to depict inter-study heterogeneity. Results: A total of 10 single arm studies - 3 prospective studies, 3 case series, and 4 retrospective studies were included. The pooled outcomes were: significant improvement of platelet count above 100K with response to romiplostim therapy in 80.53% patients [95 % CI 72.47 - 87.48, I2 = 69%], proportion of patients that continued full dose chemotherapy on romiplostim was 70.89% [95% CI 63.40 - 77.84, I2 = 0%], and incidence of thromboembolic events was 6.81% [ 95% CI 3.64 – 10.89, I2 = 35%]. Variables like platelet transfusions, bleeding events, type and stage of cancer were not reported uniformly and hence subgroup analyses could not be performed. Conclusions: Our analysis reveals that romiplostim improved the platelet counts in majority of patients with underlying CIT associated with solid tumors. It also shows that a majority of the patients were able to resume their full dose chemotherapy when maintained on romiplostim. The incidence rate of thromboembolic events with romiplostim believed to be consistent with what expected of this population with majority having advanced/high-risk malignancies. Given its efficacy, romiplostim may be used for routinely managing CIT in solid tumors. This analysis is limited by lack of comparative studies and warrant further randomized trials to confirm the safety and efficacy of romiplostim in this patient population.

Real-world (RW) elacestrant use patterns and therapeutic outcomes in patients (pts) with hormone receptor-positive (HR+)/HER2-negative advanced breast cancer (aBC).

1071 Background: Elacestrant was the first novel endocrine therapy (ET) to receive FDA approval in over two decades. In the EMERALD study, pts with ESR1-mutant ( ESR1m) HR+/HER2-negative aBC had a median progression free survival (PFS) of 3.8 months (mos). Here, we use a large clinical-genomic database to assess the RW use of elacestrant and examine the impact of line of therapy (LOT) and number of ERS1m on pt outcomes. Methods: Pts with HR+/HER2- aBC were identified via the GuardantINFORM database; all pts with ESR1m detected on circulating tumor DNA (ctDNA) testing done in routine clinical care and treated with elacestrant after the FDA approval date were included. Real-world time to treatment discontinuation (TTD) and time to next treatment (TTNT) were used as proxies for PFS (measured in mos). For TTD/TTNT, Kaplan-Meier curves and median time-to-event with 95% confidence intervals (CI) were used. For outcomes specific to single versus &gt;1 ESR1m, only pts with an ESR1m detected within the 6 months prior to elacestrant start were included. Results: 418 aBC pts were treated with elacestrant, with a median age of 62 years. Elacestrant was used across metastatic LOT (2nd: 12%, 3rd: 18%, 4tH: 17%, 5th+: 53%). Considering all prior therapies, pts commonly received prior aromatase inhibitors (AI) (89%), CDK4/6i (73%), fulvestrant (63%), and chemotherapy (49%). Of 312 pts with testing within 6 months of elacestrant start, 56% harbored a single ESR1m, with a maximum of 11 ESR1m detected in a single patient. TTD was 5.4 mos (95% CI: 4.2 - not reached [NR]) and TTNT was 6.2 mos (95% CI: 5.7 - NR); most pts were censored at the time of analysis (65% for TTD, 71% for TTNT). There were no significant differences in TTD or TTNT based on number of prior LOT or number of ESR1m mutations (Table 1). Data was not yet mature to assess differences in outcomes based on prior ET use, duration of prior CDK4/6i exposure, specific ESR1m, or co-occurring alterations. Conclusions: Using a clinical-genomic database, we present early RW insights of aBC pts treated with elacestrant. Initial outcomes, as assessed via TTD and TTNT, exceed the PFS reported in the EMERALD trial, perhaps due to multiple factors impacting patient selection and restaging protocols, which can differ in prospective trials versus routine clinical care. Factors such as prior LOT and number of ESR1m did not impact patient outcomes; additional factors such as prior ET use, duration of CDK4/6i treatment, specific ESR1m, and co-occurring mutations will be assessed as data matures. [Table: see text]

Genetic ancestry-associated differences in genomic profiling and treatment patterns in pancreatic ductal adenocarcinoma (PDAC).

4138 Background: Prior epidemiological studies have explored race both as a population-level risk factor and as a factor influencing outcomes in PDAC. However, the impact of genetic ancestry on PDAC remains unclear. We assessed the genomic landscape, clinical care patterns, and outcomes across ancestries in a large and diverse PDAC cohort to determine the potential impact of genomics on ancestral disparities. Methods: A total of 24,948 patients diagnosed with PDAC who received tissue-biopsy based comprehensive genomic profiling (CGP; Foundation Medicine, Inc. (FMI)) as part of routine clinical care from Aug 2014-Sep 2023 were examined for genomic differences based on genetic ancestry which was determined using a SNP-based approach. The US-based de-identified Flatiron Health (FH)-FMI clinico-genomic database (CGDB) was used to assess testing and treatment patterns based on ancestry in 3,863 patients of European (EUR) and 414 patients of African (AFR) ancestry diagnosed with PDAC. Results: The genetic ancestry distribution in the overall cohort was 80.9% EUR, 10.0% AFR, 4.9% Admixed American, 3.5% East Asian, and 0.7% South Asian. AFR patients showed a slightly younger median age at biopsy than EUR (64 vs 67, p &lt; .001). KRAS, TP53, CDKN2A/ 2B and SMAD4 were the most commonly altered genes in the cohort, as expected. Compared to EUR, AFR patients were enriched in alterations in TP53 (85% vs 78%, p &lt; .001) and KRAS (95% vs 93%, p &lt; .001). While rare, alterations in GNAS, CHEK2, and BRAF were observed less frequently in AFR (1.7% vs 3.3%, 0.3% vs 1.7%, 0.9% vs 2.2%, respectively, all p &lt; .001). In the CGDB cohort, AFR patients were likely to have lower socioeconomic status (SES) compared to EUR patients (33% of AFR in the lowest SES quintile compared to 9% of EUR; p &lt; .001 across all quintiles). AFR patients were less likely to receive care at academic centers (AFR 14.8% vs EUR 22.2%, p &lt; .001) and less likely to receive an investigational drug during their cancer treatment course (5.9% vs 14.1%, p = .001). Rates of surgery (AFR 30.2% vs EUR 34.6%, p = .08), immunotherapy (3.2% vs 3.3%, p &gt; .99), and targeted therapy (4.1% vs 6.2%, p = .28) were not significantly different. While AFR patients comprised a significantly larger proportion of AFR+EUR CGP volume following the decision to implement Medicare coverage for NGS testing (10.6% after Mar 16, 2018 vs 6.6% prior, p &lt; .001), this remained below the expected based on share of the overall US population. Conclusions: To our knowledge, this is the largest study of genetic ancestry in PDAC to date. There were largely similar patterns of gene alterations across AFR and EUR ancestry groups suggesting non-genomic factors may underlie clinical outcomes disparities which have been reported in other studies. Notably, there were ancestry-based differences associated with SES and both CGP testing and clinical trial enrollment patterns, which may impact patient outcomes.

AI-based radiomics model for predicting immune checkpoint inhibitor–related pneumonitis (CIP) in patients with advanced NSCLC: An external validation study.

12136 Background: The growing implementation of immunotherapy in advanced non-small cell lung cancer (NSCLC) management has led to an increase in adverse events, notably immune checkpoint inhibitor-related pneumonitis (CIP). CIP, a significant and potentially fatal complication, often necessitates the discontinuation of immunotherapy, thereby impacting patient outcomes severely. The absence of biomarkers for early detection and management of CIP represents an urgent and unmet clinical need. This expanded study explores the potential of Artificial Intelligence (AI) algorithms in predicting CIP in NSCLC patients undergoing immunotherapy from pre-treatment CT scans. Methods: A cohort of 220 stage III-IV NSCLC patients receiving immunotherapy was considered. The patients were divided into a training set (D1, n=105, Institution A), an internal validation set (D2, n=45, Institution A), and an external validation set (D3, N=70, Institutions B and C). Manual delineation of the tumor on baseline CT was performed by three physicians working in consensus. The Picture Health Px platform was employed for AI-powered deep phenotyping of the tumor and its surrounding habitat, including segmentation of the tumor associated vasculature and featurization. Quantitative features relating to the twistedness of the tumor-associated vasculature and tumoral heterogeneity patterns were extracted. These features were used to train a neural network classifier for CIP prediction. Weighting techniques during training were used to compensate for the rarity of CIP. A threshold for CIP classification was set within D1 and applied to the testing sets. Results: 43.6% of patients received an immunotherapy-only regimen and 56.4% received combined immunochemotherapy. Of these, 18.2.% experienced pneumonitis events, with 50.0% being CIP. The CIP subgroup had 50.0% grade 1 CIP, 30.0% grade 2, and 20.0% grade 3. The cross-validated AUC on D1 was 0.76 (95% CI: 0.62-0.90). The AUC was 0.61, 0.62, and 0.64, respectively, on D2, D3, and all validation data combined (D2+D3). The model correctly identified 71.4% of grade 1/2 CIP events and 33.3% of grade 3 CIP, with a corresponding false positive rate of 33.0%. Severe/grade 3 IO-related pneumonitis prediction was likely limited by the small number of severe cases from the training institution (n=1). Conclusions: We demonstrated a radiomic AI signature could identify patients at risk of CIP prior to treatment across multiple external institutions. This approach could improve the identification and management of CIP in NSCLC patients on immunotherapy, thereby enhancing patient outcomes. Expanded training and validation to account for rare, but possibly fatal, high grade CIPs is needed to expand the clinical benefit of radiologic predictors of pneumonitis to the most severe cases.

Health-Promoting Lifestyle and Its Predictors in Renal Transplant Recipients in Hunan, China: A Cross-Sectional Study.

Kidney transplantation is a critical treatment for end-stage renal disease (ESRD), with health-promoting lifestyle (HPL) significantly impacting patient outcomes. HPL involves behaviors like regular exercise, balanced nutrition, stress management, and habit modification. However, few studies have analyzed the HPL of renal transplant recipients, addressing a significant gap in current research. This study aimed to determine the predictors of HPL in renal transplant recipients using the Chinese Health Promoting Lifestyle Profile (HPLP). This cross-sectional study enrolled renal transplant recipients completing the revised Chinese HPLP at organ transplant center in a tertiary hospital in Hunan Province of China between May 2022 and July 2022. A total of 450 patients were included, comprising 256 males (56.9%), with a mean age of 44.85 ± 10.57 years. The mean score of self-actualization, health responsibility, interpersonal support, physical activity, stress management, nutrition, and overall HPLP were 15.27 ± 5.03 (possible range: 0-24), 11.41 ± 4.18 (possible range: 0-24), 11.61 ± 3.13 (possible range: 0-18), 7.53 ± 3.79 (possible range: 0-18), 12.68 ± 3.61 (possible range: 0-21), 11.17 ± 2.41 (possible range: 0-15), and 69.66 ± 16.98 (possible range: 0-120), respectively. Multivariate logistic regression analysis showed that urban residence (OR = 2.061, 95% CI: 1.350-3.148, P = 0.001), non-smoking after transplantation (OR = 2.010, 95% CI: 1.123-3.600, P = 0.019) and two post-transplant complications (OR=0.387, 95% CI: 0.218-0.689, P = 0.001). Although renal transplant recipients exhibit a moderate level of HPL, targeted interventions are essential to improve these behaviors. These interventions should focus especially on individuals from rural households, post-transplant smokers, and those experiencing post-transplant complications, to enhance their quality of life and clinical outcomes.

Metabolic disorders in patients diagnosed with colorectal cancer.

e15618 Background: Colorectal cancer (CRC) is the third most common cancer globally and ranks second as a cause of cancer-related death. As survival rates among CRC patients continue to rise, addressing accompanying metabolic comorbidities is becoming increasingly important. This study aims to explore the prevalence of metabolic comorbidities and metabolic syndrome among CRC patients, as well as their impact on survival. Methods: The ColoCare Study is a prospective cohort study conducted across seven U.S. and European sites. Data from a single site, Cedars-Sinai Medical Center in Los Angeles, California was analyzed. Adults with newly diagnosed stage I-IV CRC and available medical records were eligible. Basic demographic information and medical history, including hypertension, hyperlipidemia, and diabetes mellitus (DM) diagnosis at or before CRC diagnosis were collected by manually reviewing electronic medical records. Additionally, BMI was calculated using patients' weight and height at the time of diagnosis and classified according to the CDC’s published ranges. Patients were considered to have metabolic syndrome if they met three or more of the following criteria: hypertension, hyperlipidemia, DM, or obesity. Overall survival rates for patients with each metabolic condition were compared. Results: A total of 295 patients (58.3% male, 41.7% female, mean age at diagnosis = 58.3) were identified. 172 were non-Hispanic White (58.3%), 52 were Hispanic/Latino (17.6%), 36 (12.2%) were Asian, 27 (9.2%) were Black, and 8 (1.8%) were unknown/other. Metabolic conditions were prevalent in the cohort: hypertension affected 33.9%, hyperlipidemia affected 21.4%, and DM affected 13% of patients. Additionally, over half of the patients (56.6%) were overweight or obese. Individuals meeting criteria for metabolic syndrome (8.8%) had lower survival rates compared to those without this condition (73.1% vs. 81.4%). Similarly, patients with DM had lower survival rates compared to their counterparts without DM (72.5% vs. 82.0%). Patients with hypertension, hyperlipidemia, and elevated BMI did not have significantly different survival rates compared to patients without such conditions. Conclusions: Our study highlights the prevalence of metabolic comorbidities, specifically metabolic syndrome and DM, among CRC patients and emphasizes how these factors can impact patient outcomes post-diagnosis. This information is valuable for physicians when considering lifestyle changes or treatment strategies following CRC diagnosis. Further, it highlights the importance of coordination between oncologists and primary care providers to effectively manage metabolic diseases in CRC patients.

Love yourself as a therapist, doubt yourself as an institution? Therapist and institution effects on outcome, treatment length, and dropout

Objective: Research suggests that some therapists achieve better outcomes than others. However, an overlooked area of study is how institution differences impact patient outcomes independent of therapist variance. This study aimed to examine the role of institution and therapist differences in adult outpatient psychotherapy. Method: The study included 1428 patients who were treated by 196 therapists at 10 clinics. Two- and three-level hierarchical linear regression models were employed to investigate the effects of therapists and institutions on three dependent patient variables: (1) symptom change, (2) treatment duration, and (3) dropout. Level three explanatory variables were tested. Results: The results showed that therapist effects (TE) were significant for all three types of treatment outcome (7.8%–18.2%). When a third level (institution) was added to the model, the differences between therapists decreased, and significant institution effects (IE) were found: 6.3% for symptom change, 10.6% for treatment duration, and 6.5% for dropout. The exploratory analyses found no predictors able to explain the systematic variation at the institution level. Discussion: TE on psychotherapy outcomes remain a relevant factor but may have been overestimated in previous studies due to not properly distinguishing them from differences at the institution level.

Beyond the Bedside: Machine Learning-Guided Length of Stay (LOS) Prediction for Cardiac Patients in Tertiary Care.

Efficient management of hospital resources is essential for providing high-quality healthcare while ensuring sustainability. Length of stay (LOS), measuring the duration from admission to discharge, directly impacts patient outcomes and resource utilization. Accurate LOS prediction offers numerous benefits, including reducing re-admissions, ensuring appropriate staffing, and facilitating informed discharge planning. While conventional methods rely on statistical models and clinical expertise, recent advances in machine learning (ML) present promising avenues for enhancing LOS prediction. This research focuses on developing an ML-based LOS prediction model trained on a comprehensive real-world dataset and discussing the important factors towards practical deployment of trained ML models in clinical settings. This research involves the development of a comprehensive adult cardiac patient dataset (SaudiCardioStay (SCS)) from the King Faisal Specialist Hospital & Research Centre (KFSH&RC) hospital in Saudi Arabia, comprising 4930 patient encounters for 3611 unique patients collected from 2019 to 2022 (excluding 2020). A diverse range of classical ML models (i.e., Random Forest (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM), artificial neural networks (ANNs), Average Voting Regression (AvgVotReg)) are implemented for the SCS dataset to explore the potential of existing ML models in LOS prediction. In addition, this study introduces a novel approach for LOS prediction by incorporating a dedicated LOS classifier within a sophisticated ensemble methodology (i.e., Two-Level Sequential Cascade Generalization (2LSCG), Three-Level Sequential Cascade Generalization (3LSCG), Parallel Cascade Generalization (PCG)), aiming to enhance prediction accuracy and capture nuanced patterns in healthcare data. The experimental results indicate the best mean absolute error (MAE) of 0.1700 for the 3LSCG model. Relatively comparable performance was observed for the AvgVotReg model, with a MAE of 0.1703. In the end, a detailed analysis of the practical implications, limitations, and recommendations concerning the deployment of ML approaches in actual clinical settings is presented.

Exploring the concept and management strategies of caring stress among clinical nurses: a scoping review.

The concept of caring stress and its specific management has received less attention than other dimensions of stress in nurses. Therefore, to clarify the concept of caring stress, a scoping review study was designed. This scoping review aimed to investigate the concept of caring stress among clinical nurses and examine the strategies used for its management. This review employed a scoping review methodology to comprehensively map the essential concepts and attributes of the phenomenon by drawing on a wide range of sources. International databases including PubMed, Scopus, Web of Science, Google Scholar, and Scientific Information Database (SID) were searched to gather relevant studies published until October 1, 2023. MESH terms included "caring stress", "care", "stress", "nurse", and "stress management" were used. Two reviewers independently collected data from full-text papers, ensuring that each paper underwent assessment by at least two reviewers. Out of 104,094 articles initially searched, 22 articles were included in this study. High workloads, transmitting the infection, stressful thoughts, stressful emotions, and stressful communications were the significant concepts and factors of caring stress among nurses. Also, rest breaks during patient care shifts, playing music in the ward, and denial of critical situations were examples of positive and negative coping and management ways to reduce caring stress. Effective stress management strategies can lead to better patient care and safety. Stressed nurses are more likely to make errors or become less vigilant in their duties, impacting patient outcomes. By addressing caring stress, clinical practice can prioritize patient well-being. Further research is required to delve deeper into this critical issue concerning nurses in the future.