Predictive Factors Research Articles

Predictors of Hospital Readmission, Institutionalization, and Mortality in Geriatric Rehabilitation Following Hospitalization According to Admission Reason.

Older adults following an inpatient geriatric rehabilitation (GR) program commonly experience adverse health outcomes such as hospital readmission, institutionalization, and mortality. Although several studies have explored factors related to these outcomes, the influence of admission reason on the predictive factors of adverse health outcomes in the rehabilitation process remains unclear. Therefore, this study aimed to identify predictive factors for adverse health outcomes in inpatients attending GR according to their admission reason. This retrospective study included patients with orthogeriatric (OG) conditions and patients with hospital-associated deconditioning (HAD) admitted to GR after an acute hospitalization between 2016 and 2020. Patients were evaluated by a comprehensive geriatric assessment at admission, including sociodemographic data, social resources, clinical data, cognitive, functional and nutritional status, and physical performance measurements. Adverse health outcomes were collected (hospital readmission, institutionalization, and mortality). Univariate analyses and multivariate backward binary logistic regressions were used to determine predictive factors. In this study, 290 patients were admitted for OG conditions, and 122 patients were admitted due to HAD. In patients with OG conditions, lower Mini-Mental State Examination (MMSE) predicted institutionalization and mortality. Lower Mini Nutritional Assessment-Short Form predicted institutionalization, whereas lower Barthel Index and lower Tinetti-Performance-Oriented Mobility Assessment scores were associated with higher mortality. In patients with HAD, higher age-adjusted comorbidity index predicted hospital readmission and mortality, and lower Short Physical Performance Battery scores predicted institutionalization and mortality. Finally, lower MMSE scores, worse values in Older Americans Resources and Services Scale and male gender were associated with a higher risk of institutionalization. Predictive factors for hospital readmission, institutionalization, and mortality in patients with OG conditions and HAD during GR were different. Some of those predictors, such as nutritional status and physical performance, are modifiable. Understanding predictive factors for adverse outcomes, and how these factors differ by admission diagnosis, improves our ability to identify patients most at risk. Early identification of these patients could assist with prevention efforts and lead to a reduction of negative outcomes.

Prediction of Stroke-Associated Hospital-Acquired Pneumonia: Machine Learning Approach.

Stroke-associated Hospital Acquired Pneumonia (HAP) significantly impacts patient outcomes. This study explores the utility of machine learning models in predicting HAP in stroke patients, leveraging national registry data and SHapley Additive exPlanations (SHAP) analysis to identify key predictive factors. We collected data from a national stroke registry covering January 2014 to July 2022, including 9,840 patients diagnosed with ischemic and hemorrhagic strokes. Five machine learning models were trained and evaluated: XGBoost, Random Forest, Support Vector Machine (SVM), Logistic Regression, and Artificial Neural Network (ANN). Performance was assessed using accuracy, precision, recall, F1-score, AUC, log loss, and Brier score. SHAP analysis was conducted to interpret model outputs. The ANN model demonstrated superior performance, with an F1-score of 0.86 and an AUC of 0.94. SHAP analysis identified key predictors: stroke severity, admission location, Glasgow Coma score (GCS), systolic and diastolic blood pressure at admission, ethnicity, stroke type, mode of arrival, and age. Patients with higher stroke severity, dysphagia, and those arriving by ambulance were at increased risk for HAP. This study enhances our understanding of early predictive factors for HAP in stroke patients and underlines the potential of machine learning to improve clinical decision-making and personalized care.

Spontaneous breathing trial in the weaning process from mechanical ventilation in pediatrics: outcome and predictive factors.

Introduction. spontaneous breathing trial (SBT) in weaning from pediatric invasive mechanical ventilation (IMV) is an endorsed practice, its positivity is based on clinical parameters; however, its results could be better documented. Objective. To describe the results of the SBT in the IMV weaning process. Population and methods. Retrospective analysis. Patients with ≥48 h in IMV from March 1, 2022 to January 31, 2024. Results. A total of493 SBT were analyzed in 304 patients; 71% (348) were positive, and 87% (302) resulted in successful extubations. The causes of negative SBT were increased work of breathing (70%), respiratory rate (57%), and heart rate (27%). In univariate analysis, respiratory distress as the reason for admission, peak inspiratory pressure before SBT and T-tube use, were predictors of negative SBT. In multivariate analysis, this association persisted for admission for respiratory cause, the higher programmed respiratory rate in IMV, as the T-tube modality. Those with negative SBT stayed more days in IMV (9 [7-12] vs. 7 [4-10]) and in PICU (11 [9-15] vs. 9 [7-12]). Conclusion. Positive SBT predicted successful extubation in a high percentage of cases. Respiratory distress on admission, higher programmed respiratory rate, and a higher proportion of T-tube mode were negative predictors of the test. Negative SBT was associated with more extended stays in IMV and PICU.

Management trends and outcomes of appendiceal cancers: A National Cancer Database study.

810 Background: Appendiceal tumors encompass a variety of histological types that exhibit different behaviors. The current study aimed to investigate and compare overall survival, predictive factors for overall survival, and management of histological variations of appendiceal tumors. Methods: The National Cancer Data Bank (NCDB) database (2004–2020) was evaluated to include patients with appendiceal tumors histologies including goblet cell adenocarcinoma (GCA), neuroendocrine neoplasm (NEN), non-mucinous adenocarcinoma (NMA), and mucinous adenocarcinoma (MA). Univariate and multivariable analyses were conducted. Results: The GCA, MA, NEN, and NMA groups consist of 6,111, 16,471, 19,199, and 11,065 patients, respectively. The NMA and NEN groups had significantly lowest and higher overall survival compared to other types (p<0.001 for both) (GCC: 143.27 (140.23-146.30), MA: 111.91 (109.996-113.832), NEN: 170.88 (168.56-173.20), and NMA: 101.399 (99.132-103.666) months). The independent predicting factors of worse overall survival were age (HR: 1.03 (1.03-1.04)), black race (HR: 1.24 (1.08-1.43), ref: white race), fourth median income (HR: 0.84 (0.74-0.96), ref: first median), Charleson index comorbidity score (HR: 1.3 (1.22-1.38)), lymphovascular invasion (HR: 1.28 (1.15-1.42)), pathologic stage 2 (HR: 1.32 (1.12-1.57)), stage 3 (HR: 1.99 (1.66-2.40)), stage 4 (HR: 4.20 (3.47-5.07)), ref: stage 1, intraoperative systemic therapy (HR: 0.52 (0.39-0.70)), positive surgical margin (1.55 (1.39-1.73)), number of positive lymph nodes (HR:1.06 (1.05-1.07)), moderately differentiated tumors (HR:1.43 (1.25-1.63)), poorly differentiated (HR: 1.94 (1.69-2.24)), undifferentiated (HR: 1.48 (1.14-1.91)), ref: well differentiated, and NMA type (HR:1.30 (1.10-1.55)). Furthermore, in terms of type of surgery, significantly higher patients of GCA (54.6%) and NMA (55.2%) groups underwent subtotal colectomy compared to other groups. Regarding systemic therapy, significantly higher patients of MA group received intraoperative, and both neoadjuvant and adjuvant therapy compared to other groups. Also, NEN group had significantly higher patients who underwent surgery with laparoscopic approach compared to others. Conclusions: This study reveals that different types of appendiceal tumors have distinct characteristics in regard to overall survival outcomes and treatment approaches. NENs showed the highest survival rates, while NMAs had the lowest. These results underscore the need for personalized treatment strategies for each tumor type to improve patient outcomes.

Evolving treatment paradigms of cerebral aneurysm stasis in flow diversion.

Flow diversion is an effective first-line treatment for intracranial aneurysms; however, the rate of incomplete occlusion is not insignificant. Data in neuroendovascular literature is limited regarding the implications of persistent incomplete occlusion despite flow diversion. We conducted a retrospective analysis of a prospectively maintained database and identified 125 consecutive patients with treatment naïve intracranial aneurysms who underwent flow diversion with the PED from April 2014 - November 2022. Patients were divided into 3 groups based on the duration of stasis: venous, capillary, and no stasis. Comparative and multivariate analyses were performed between the three groups. At latest follow-up, complete occlusion occurred in 69.6% and 82.4% showed progression of occlusion. Retreatment was required in 2.4%. There was no significant difference in retreatment (p=0.667), complete occlusion (p=0.774) or progression of occlusion (p=0.848) at latest follow up. No patients experienced subarachnoid hemorrhage post-treatment. On multivariate analysis, hypertension was a negative predictor for complete occlusion (p=0.006) and progression of occlusion (p=0.017), while duration of stasis was noncontributory. The mean latest follow up was 12.55months. Flow diversion is a safe and effective first line treatment for intracranial aneurysms with a relatively low complication rate. Hypertension was a negative predictor of complete occlusion and progression of occlusion, while the degree of occlusion post-flow diversion may not be predictive of future rupture risk and the Raymond Roy Occlusion classification may not apply. The degree of stasis after initial treatment was not predictive of future occlusion, retreatment, nor aneurysm rupture risk. However, stasis degree may be worth additional analysis given this studies sample size, lack of long-term follow-up, and the lack of predictive factors in current literature to guide post-flow diversion management.

Identification and validation of key predictive factors for heart attack diagnosis using machine learning and fuzzy clustering

Identification and validation of key predictive factors for heart attack diagnosis using machine learning and fuzzy clustering

Prognostic prediction for inflammatory breast cancer patients using random survival forest modeling.

Inflammatory breast cancer (IBC) is an aggressive and rare phenotype of breast cancer, which has a poor prognosis. Thus, it is necessary to establish a novel predictive model of high accuracy for the prognosis of IBC patients. Clinical information of 1,230 IBC patients from 2010 to 2020 was extracted from the Surveillance, Epidemiology and End Results (SEER) database. Cox analysis was applied to identify clinicopathological characteristics associated with the overall survival (OS) of IBC patients. Random survival forest (RSF) algorithm was adopted to construct an accurate prognostic prediction model for IBC patients. Kaplan-Meier analysis was performed for survival analyses. Race, N stage, M stage, molecular subtype, history of chemotherapy and surgery, and response to neoadjuvant therapy were identified as independent predictive factors for the OS of IBC patients. The top five significant variables included surgery, response to neoadjuvant therapy, chemotherapy, breast cancer molecular subtypes, and M stage. The C-index of RSF model was 0.7704 and the area under curve (AUC) values for 1, 3, 5 years in training and validation datasets were 0.879-0.955, suggesting the excellent predictive performance of RSF model. IBC patients were divided into high-risk group and low-risk group according the risk score of RSF model, and the OS of patients in the low-risk group was significantly longer than those in the high-risk group. In this study, we constructed a prognosis prediction model for IBC patients through RSF algorithm, which may potentially serve as a useful tool during clinical decision-making.

Prevalence of Stress, Anxiety, Depression, and Sleep Quality Among Young Adults in Turkiye: A Cross-Sectional Study.

The current study was conducted to measure the prevalence of stress, anxiety, depression, and sleep quality and identify predisposing factors of psychological distress among young adults during the pandemic. A cross-sectional design was adopted. The target population consisted of students studying at an associate degree health services school at a university in Turkiye. Overall, 704 students were included in the sample. Multiple logistic regression was implemented to predict risk factors. The prevalence of moderate to extremely severe stress, anxiety, and depression was found to be 39%, 48.4% and 47.6%, respectively. There was a strong positive association between stress and anxiety (r = 0.869, p < 0.001), stress and depression (r = 0.912, p < 0.001), and between anxiety and depression (r = 0.857, p < 0.001). A moderate positive relationship was found between sleep quality and stress (r = 0.484, p < 0.001), sleep quality and anxiety (r = 0.484, p < 0.001), and sleep quality and depression (r = 0.481, p < 0.001). Young adults with poor sleep quality, those who find safety measures for the pandemic outbreak insufficient, those who use alcohol, and those who feel despair were more likely to have stress, anxiety, and depression risk. Age and gender did not affect their stress, anxiety, or depression risk. Nearly half of the young adults experienced varying degrees of stress, anxiety, and depression, and most had poor sleep quality. The insufficiency of outbreak measures, poor sleep quality, using alcohol, and feelings of despair were mutual predictive factors of stress, anxiety, and depression.

Exploring predictive factors for detecting KRAS mutations in pancreatic cancer using liquid biopsy.

782 Background: Liquid biopsy offers an alternative to tissue specimens for comprehensive genetic profiling. However, circulating tumor DNA is sometimes insufficient to detect genomic alterations in pancreatic cancer (PC). The detection rate of KRAS mutations was reportedly increased in PC with liver metastasis. In contrast, the predictive value of CA19-9 levels, the timing of liquid biopsy, or the type of liquid biopsy for detecting KRAS mutations remains unclear. We investigated whether these factors could be predictive of detecting KRAS mutations in PC. Methods: From September 2021 to August 2024, we retrospectively reviewed patients with PC who underwent liquid biopsy. Results: A total of 106 patients were enrolled (median age: 64 years, male: 66). Patient characteristics were as follows: tumor status: locally advanced: 10, metastatic: 90, recurrence: 6; metastatic site: liver: 51, lung: 26, lymph nodes: 20, peritoneum: 38, others: 7; number of metastatic sites: 1: 63, 2: 25, ≥3: 8; treatment line at liquid biopsy: 1: 21, 2: 77, 3:8; median CA19-9 level: 1053.4 U/mL; type of liquid biopsy: FoundationOne Liquid CDx (FL): 75 or Guardant360 (G): 31. The overall rate of KRAS mutations was 47%, with a median variant allele frequency of 0.83 [range:0.1-71.0]. The patterns of KRAS mutations were as follows: G12D: 23, G12V: 18, G12R: 4, and others: 14. The detection rate of KRAS mutations varied by the follows factors: metastatic site: liver: 65%, other organs: 44%; number of metastatic sites: ≥2: 47%, &lt;2: 48%; CA19-9 level: ≥2,000 U/mL: 68%, &lt;2,000: 38%; timing of liquid biopsy: 1st line: 42%, ≥2nd line: 67%; types of liquid biopsy: FL: 49%, G: 42%. In multivariate analysis, liver metastasis and CA19-9 level ≥2,000 U/mL were identified as independent factors associated with improved detection of KRAS mutations. In PC with these two factors, the detection rate of KRAS mutation increased to 76%. Conclusions: Our findings indicate that liver metastasis and CA19-9 levels above 2,000 U/mL are predictive factors for detecting KRAS mutations in PC through liquid biopsy.

Tumor lysis syndrome in colorectal cancer: A systematic review of clinical characteristics.

122 Background: Tumor lysis syndrome (TLS) is an oncologic emergency resulting from the release of potassium, phosphorus, and nucleic acids from tumor cells. While rare in colorectal cancer (CRC), TLS is linked with high mortality, and literature is limited. This study aims to summarize the clinical characteristics of patients with TLS in CRC. Methods: We conducted a systematic review of TLS in CRC through a comprehensive literature search in PubMed and manual searches from January 1st, 1993, up to September 13th, 2024. Keywords included "Tumor Lysis Syndrome," "Colorectal Cancer," and "Colon Cancer." 32 studies were found, identifying 11 spontaneous and 22 therapy-related TLS cases. Quantitative and qualitative data were extracted for descriptive analysis. Results: A total of 33 patients (16 males and 15 females) had a mean age of 56.5 ± 17.8 years at TLS diagnosis. The mean ages for males and females were 58.3 ± 7.1 and 55.8 ± 13.7 years, respectively (p=0.59). The primary histology was adenocarcinoma (92%) followed by neuroendocrine (8%) (data unavailable for 9 patients). Among 15 patients with grading information, Grade 2 tumors were most common (53%), followed by Grade 3 (40%) and Grade 1 (7%). Staging data was available for 32 patients. Most patients had Stage IV disease (94%), with frequent metastases to the liver (93%), lungs (30%), and bones (10%). Hyperuricemia is present in all patients (1 patient without data). Acute kidney injury (AKI) was present in all patients (4 patients without data). Hyperphosphatemia was found in 82% of patients (5 patients without data). Hypocalcemia was noted in 52% (10 patients without data), and hyperkalemia was found in 74% (6 patients without data). Out of the 33 patients, 11 experienced spontaneous TLS (33%) and 22 had therapy-related TLS (67%). Duration of TLS onset following therapy was available for 17 patients, including one outlier at 30 days on Capecitabine. The mean duration for therapy-related TLS, excluding the outlier, was 3.8 ± 2.5 days. Among the 22 patients on therapy, 59% received 5-Fluorouracil (5-FU)-based treatment. 31% of those receiving 5-FU had combination therapy with Bevacizumab. Death occurred in 59% of patients, with data missing for 4 patients. Conclusions: TLS in colorectal cancer (CRC) is associated with a mortality rate of up to 59% and shows no gender preference. Identifying predictive factors is crucial for TLS prophylaxis. Patients with TLS in CRC often present with Stage IV disease, liver metastasis, hyperuricemia, and acute kidney injury (AKI).

The lowest HU value on transverse planes: a predictive factor for cranial adjacent vertebral fracture risk after percutaneous vertebroplasty

The lowest HU value on transverse planes: a predictive factor for cranial adjacent vertebral fracture risk after percutaneous vertebroplasty

Proteinuria and tubular cells: Plasticity and toxicity.

Proteinuria is the most robust predictive factors for the progression of chronic kidney disease (CKD), and interventions targeting proteinuria reduction have shown to be the most effective nephroprotective treatments to date. While glomerular dysfunction is the primary source of proteinuria, its consequences extend beyond the glomerulus and have a profound impact on tubular epithelial cells. Indeed, proteinuria induces notable phenotypic changes in tubular epithelial cells and plays a crucial role in driving CKD progression. This comprehensive review aims to elucidate the mechanisms involved in the tubular handling of proteins and explore the potential effects of proteinuria on the function of tubular epithelial cells. This paper is a narrative review. Litterature review was performed on PubMed from its inception until 2024, focusing on the effects of proteinuria on tubular cells. The review highlights the toxic effects of plasma proteins on tubular epithelial cells through signal transduction pathways, as well as endoplasmic reticulum stress activation, oxidative stress, and metabolic alterations. Additionally, it provides an updated understanding of the dynamic phenotypic changes occurring within the nephron in response to proteinuria. By examining the intricate interplay between proteinuria and tubular epithelial cells, this review sheds light on key factors contributing to CKD progression and unveils potential targets for therapeutic interventions.

Source Characteristics Influence AI-Enabled Orthopaedic Text Simplification: Recommendations for the Future.

This study assesses the effectiveness of large language models (LLMs) in simplifying complex language within orthopaedic patient education materials (PEMs) and identifies predictive factors for successful text transformation. We transformed 48 orthopaedic PEMs using GPT-4, GPT-3.5, Claude 2, and Llama 2. The readability, quantified by the Flesch-Kincaid Reading Ease (FKRE) and Flesch-Kincaid Grade Level (FKGL) scores, was measured before and after transformation. Analysis included text characteristics such as syllable count, word length, and sentence length. Statistical and machine learning methods evaluated the correlations and predictive capacity of these features for transformation success. All LLMs improved FKRE and FKGL scores (p < 0.01). GPT-4 showed superior performance, transforming PEMs to a seventh-grade reading level (mean FKGL, 6.72 ± 0.99), with higher FKRE and lower FKGL than other models. GPT-3.5, Claude 2, and Llama 2 significantly shortened sentences and overall text length (p < 0.01). Importantly, correlation analysis revealed that transformation success varied substantially with the model used, depending on original text factors such as word length and sentence complexity. LLMs successfully simplify orthopaedic PEMs, with GPT-4 leading in readability improvement. This study highlights the importance of initial text characteristics in determining the effectiveness of LLM transformations, offering insights for optimizing orthopaedic health literacy initiatives using artificial intelligence (AI). This study provides critical insights into the ability of LLMs to simplify complex orthopaedic PEMs, enhancing their readability without compromising informational integrity. By identifying predictive factors for successful text transformation, this research supports the application of AI in improving health literacy, potentially leading to better patient comprehension and outcomes in orthopaedic care.

National Implementation of a Crisis Resolution Home Treatment (CRHT) Team in Malta: Insights From the First Two Years of Operation.

Crisis Resolution Home Treatment (CRHT) teams have become a widespread alternative to psychiatric hospitalisation. Despite their popularisation, Malta has only recently introduced a CRHT team. The aims of the current study were to investigate (i) patient characteristics, (ii) factors influencing patients' length of follow-up (LoFU) and (iii) predictors of clinical outcomes. Descriptive and quantitative non-identifiable data were collected and analysed for patients utilising the CRHT service within its first 2 years of operation (n = 643). One-way ANOVA tests investigated influencing factors for LoFU, whereas binary logistic regressions deduced predictive factors for clinical outcomes. Patients without acute psychiatric disorders had the shortest LoFU, indicating that the team received inappropriate referrals. Patients were most likely to have extended LoFU if they were diagnosed with OCD & related disorders and were most likely to be diagnosed with an underlying personality disorder if they were diagnosed with anxiety & phobic disorders. Continuity of care facilitates discharge planning. Patients receiving the CRHT service in Malta are most comparable with health systems that prefer to hospitalise patients with a higher risk profile. The high occurrence of personality disorders necessitates staff to have interdisciplinary knowledge and an appropriate skill mix.

Predictive factors for the efficacy of nal-IRI + 5FU/LV therapy in patients previously treated with conventional irinotecan.

737 Background: There were some reports that nal-IRI + 5FU/LV (NAPOLI) therapy was effective for patients with unresectable pancreatic cancer who had a history of treatment containing conventional irinotecan (IRI) though the others did not. We aimed to investigate the factors that contribute to the effectiveness of NAPOLI therapy for patients who have already received IRI-containing treatment. Methods: We retrospectively enrolled the consecutive patients who had previously treated with IRI-containing treatment and started NAPOLI therapy at our hospital between June 2020 and December 2022. We compared the patient backgrounds of patients who achieved CR, PR, or SD according to RECISTv1.1 (effective group) and those who did not (ineffective group). Continuous variables were divided into two groups by the median of the entire population, and factors contributing to the effectiveness of NAPOLI therapy were determined by logistic regression analysis. Results: The subjective were 52 patients. The reason for discontinuation of IRI-containing treatment was refractory and intolerant in 45 and 7 patients, respectively. The median age was 65 years. Twenty-three patients (44%) had ECOG PS of 0, and 41 patients (79%) had metastatic disease. The median albumin, CRP, CEA and CA 19-9 was 3.8 g/dL, 0.3 mg/dL, 8.5 ng/mL and 2082 U/mL, respectively. Twenty-one patients (40%) showed SD and they were allocated in the effective group whereas 31 patients were in the ineffective group. Of the 21 patients in the Effective Group, 16 patients(76%) were refractory, while of the 31 patients in the Ineffective Group, 29 patients (94%) were refractory. The factors contributing to disease control were PS of 0 (odds ratio, 5.79; 95% confidence interval, 1.34–25.0), CA 19-9 &lt;1000 U/mL (odds ratio, 5.53; 95% confidence interval, 1.26–24.3), and Alb &gt;3.8 g/dL (odds ratio, 5.19; 95% confidence interval, 1.14–23.7). Age, sex, disease stage, serum level of CRP, and CEA did not affect the effectiveness of NAPOLI therapy. Conclusions: Even in patients who have already received IRI treatment, the NAPOLI regimen is expected to be effective in patients with PS of 0, Alb &gt;3.8 g/dL, and CA 19-9 &lt;1000 U/mL.

Determinants of Problem-Solving Skills of Nursing Students: Solution-Focused Thinking Skills and Emotional Intelligence.

Problem-solving skills are some of the leading strategies for dynamism in the content and quality of nursing care. The present study is aimed at determining nursing students' problem-solving, solution-focused thinking, and emotional intelligence levels and investigating the relationship between their problem-solving skills and these variables. The study comprised 305 nursing students in Turkey. Data were collected between May and June 2021, using the personal information form, problem-solving inventory, solution-focused inventory and Schutte emotional intelligence scale. One-way ANOVA, t-test and multiple regression were used for data analysis. The mean age of the participants was 21.81 ± 5.93 years, 75.7% of them were women, 35.1% were senior students and 58.0% perceived their academic achievement as moderate. The mean scores from the overall problem-solving inventory, solution-focused inventory, and emotional intelligence scale were 92.93 ± 19.30, 50.26 ± 8.43 and 128.22 ± 14.11, respectively. Variables such as sex, perceived academic achievement, emotional intelligence and solution-focused thinking levels affected problem-solving skills (p < 0.01). The effective predictive factors accounted for 50.2% of the change in participants' problem-solving skill levels. For this reason, revising the national nursing curriculum with programmes that develop emotional intelligence and solution-focused thinking skills will enable nursing students to better manage the nursing process in clinical and field practices.

Preoperative Diffusion Tensor Imaging and Neurite Dispersion and Density Imaging in Isocitrate Dehydrogenase-Mutant Grade 2 and 3 Gliomas: Definition of Tumor-Related Epilepsy and Predictive Factors of Seizure Outcomes Based on a Single-Center Retrospective Case Series.

Understanding and managing seizure activity is crucial in neuro-oncology, especially for highly epileptogenic lesions like isocitrate dehydrogenase (IDH)-mutant gliomas. Advanced MRI techniques such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) have been used to describe microstructural changes associated with epilepsy. However, their role in tumor-related epilepsy (TRE) remains unclear. This study aims to investigate the role of DTI and NODDI tumor-derived metrics in defining TRE and predicting postoperative seizure outcomes in patients undergoing surgical resection for IDH-mutant grade 2 and 3 gliomas. This was a single-center retrospective study. Preoperative DTI parameters included fractional anisotropy and mean diffusivity. NODDI parameters included neurite density index (NDI), orientation dispersion index, and free-water fraction (FWF). These metrics were calculated within three volumes of interest (fluid-attenuated inversion recovery [FLAIR] tumor volume, FLAIR peripheral zone, and FLAIR central zone [Fcz]) and correlated with seizure presentation, type, and postoperative control, which was reported according to the Engel classification system. Fifty-seven patients were included in this study. Increased NODDI-derived FWF-Fcz (P = .031) and NDI-Fcz (P = .046) values correlated with preoperative generalized seizure presentation, although only the FWF-Fcz confirmed its statistical significance (P = .047) in the multivariate analysis. Lower mean diffusivity-FLAIR tumor volume correlated with poor postoperative seizure control both in the univariate (P = .015, P = .026) and multivariate analyses (P = .024, P = .036), while a trend toward significance was found between higher NDI-FLAIR peripheral zone and worse seizure control (P = .055). DTI and NODDI tumor-derived quantitative parameters may define TRE and predict postoperative seizure outcomes in patients with IDH-mutant gliomas. Notably, DTI metrics were found to be independent predictors of postoperative seizure outcomes, while preoperative NODDI parameters correlated with seizure presentation. Further research is warranted to validate our findings and to better understand the underlying mechanisms driving TRE.

Incidence, risk factors and endoscopic retrieval of proximally migrated pancreatic stents: 25 years of experience in a high-volume center - a case controlled study.

Proximal migration is one of the complications after pancreatic stenting. This study aims to determine the incidence, risk factors and endoscopic treatment of proximally migrated pancreatic stents. A retrospective search of all the endoscopic retrograde cholangiopancreatography (ERCP) records was conducted from 1997 to 2022 in our tertiary center. Proximal migration of the pancreatic stent was defined as when the stent shifted completely into the pancreatic duct and the distal end of the stent was no longer visible at the duodenal papilla. A total of 9017 pancreatic duct stentings of 6083 patients were performed. The proximal migration rate was 0.2% (17/9017). Three predictive factors for proximal migration were identified: pancreatic duct stones (OR, 0.107), residual pancreatic duct stones (OR, 8.290) and straight-shape stent (OR, 4.725). After including 19 patients transferred from other hospitals, 46 ERCPs were performed to retrieve the proximally migrated stents in 36 patients. The success rate of endoscopic removal was 80.6% (29/36). 1 (2.8%) patient was referred to surgery, and 6 patients had new pancreatic stents placed for conservative treatment. 21.7% (10/46) cases developed post-ERCP pancreatitis and 2.2% (1/46) developed infection. Proximal migration of pancreatic stents is less common, but deserves more attention. Endoscopy is efficient in retrieving proximally migrated stents. In patients with residual pancreatic duct stones and straight stent, the risk of proximal migration is significantly increased.

Segmentation of coronary artery and calcification using prior knowledge based deep learning framework.

Computed tomography angiography (CTA) is used to screen for coronary artery calcification. As the coronary artery has complicated structure and tiny lumen, manual screening is a time-consuming task. Recently, many deep learning methods have been proposed for the segmentation (SEG) of coronary artery and calcification, however, they often neglect leveraging related anatomical prior knowledge, resulting in low accuracy andinstability. This study aims to build a deep learning based SEG framework, which leverages anatomical prior knowledge of coronary artery and calcification, to improve the SEG accuracy. Moreover, based on the SEG results, this study also try to reveal the predictive ability of the volume ratio of coronary artery and calcification for rotational atherectomy (RA). We present a new SEG framework, which is composed of four modules: the variational autoencoder based centerline extraction (CE) module, the self-attention (SA) module, the logic operation (LO) module, and the SEG module. Specifically, the CE module is used to crop a series of 3D CTA patches along the coronary artery, from which the continuous property of vessels can be utilized by the SA module to produce vessel-related features. According to the spatial relations between coronary artery lumen and calcification regions, the LO module with logic union and intersection is designed to refine the vessel-related features into lumen- and calcification-related features, based on which SEG results can be produced by the SEGmodule. Experimental results demonstrate that our framework outperforms the state-of-the-art methods on CTA image dataset of 72 patients with statistical significance. Ablation experiments confirm that the proposed modules have positive impacts to the SEG results. Moreover, based on the volume ratio of segmented coronary artery and calcification, the prediction accuracy of RA is 0.75. Integrating anatomical prior knowledge of coronary artery and calcification into the deep learning based SEG framework can effectively enhance the performance. Moreover, the volume ratio of segmented coronary artery and calcification is a good predictive factor forRA.

Factors affecting the prolongation of mechanical ventilation in patients after cardiac surgery

BackgroundThis study aimed to investigate the major predictive factors associated with prolonged mechanical ventilation(PMV) following cardiac surgery.MethodsThis retrospective, cross-sectional, descriptive-analytical study was conducted from September 2021 to March 2022, involving 244 patients who underwent cardiac surgery. PMV was defined as mechanical ventilation for more than 24 h. Potential risk factors before, during, and after surgery were examined and recorded. Logistic regression analysis was performed to assess the relationship between demographic, clinical variables, and prolonged mechanical ventilation. A significance level of 0.05 was used for data analysis.ResultsThe study population consisted of 68.4% male and 31.6% female patients, with 86.9% undergoing CABG surgery. PMV was observed in 13.1% of the patients. The findings revealed that the incidence of postoperative pneumonia increased the likelihood of PMV by more than 7 times [OR = 7.24, 95% CI=(5.12,8.14), P-value = 0.001]. Similarly, respiratory failure was associated with a 7.5-fold increase in the odds of PMV [OR = 7.56, 95% CI=(4.48,8.77), P-value = 0.042]. Drainage of one liter of blood on the first postoperative day increased the risk of PMV by 2.2 times [OR = 2.21, 95% CI=(1.98,2.46), P-value = 0.032], and the use of epinephrine was associated with a 2.73-fold increase in the odds [OR = 2.73, 95% CI=(2.24,3.11), P-value = 0.022]. Risk of PMV in the patients who had cardiac dysfunctin increased by more than 2 times.[OR = 2.58, 95%; CI = (1.33.2.87); P-value = 0.042]. In the patients need an Intra Aortic Balloon Pump(IABP) risk of PMV increased by more than 2 times. (OR = 2.74,95%,CI = 1.36,5.47: Pvalue = 0.03). The risk of PMV in the patients who had cerebrovascular accident(CVA) increased by more than three times [OR = 3.75, 95% CI = 1.26,4.84; P-value = 0.044]. For each unit increase in Euro Score 2 the chance of PMV increased by 1.38 TIMES. Furthermore ICU Mortality had a significant relationship with PMV.(Pvalue < 0.001).ConclusionThe study identified postoperative complications, such as pneumonia, respiratory failure, high drainage, need to an IABP, higher EURO Score 2, Cardiac dysfunction, CVA and the use of epinephrine, as independent risk factors for PMV following cardiac surgery.