Citations

Cardiovascular disease (CVD) remains the leading cause of death worldwide and is a major driver of critical illness, resulting in admission to cardiac intensive care units (CICUs). Patients with acute, life-threatening CVD often experience episodes of acute decompensation characterized by high symptom burden that may portend progressive loss of function, significantly impair quality of life (QOL), and involve high-intensity, technologically advanced therapies to sustain life. Despite these advances, up to 30% of patients die during CICU hospitalizations, and those who survive may subsequently face persistent functional impairment and psychosocial distress. During critical CVD (CCVD), patients often endure prognostic uncertainty and face complex decisions regarding life-sustaining therapies alongside refractory symptoms. Thus, care that focuses exclusively on disease-directed or life-prolonging therapies is often insufficient to address the full spectrum of patient and caregiver needs. When integrated alongside intensive cardiovascular care, palliative care (PC) offers a complementary and essential approach to the management of CCVD to inform therapeutic decisions, improve QOL, and address psychosocial and spiritual well-being. In this article, a multidisciplinary team featuring PC clinicians (physicians, nurse practitioners, social worker, psychologist, and chaplain), cardiologists, cardiac surgeons, cardiothoracic anesthesiologists, and intensivists present evidence-based guidance in a “Top Ten Tips” format to support PC clinicians caring for CICU patients and their caregivers.

Abstract Skeletal muscle is a major determinant of functional status. The impact of advanced prostate cancer (aPC) systemic therapies on body composition is unknown. We identified aPC patients with serial PET-CTs receiving androgen deprivation therapy (ADT), androgen receptor pathway inhibitors (ARPI), chemotherapy, and/or Lutetium-177. An artificial intelligence algorithm quantified body composition changes from PET-CT images. Linear mixed effects models examined body composition changes over time by treatment type. The algorithm examined 2,342 PET-CTs from 468 patients. On multivariable analysis, ADT was associated with a 9% reduction in muscle density (-1.91 Hounsfield units), ARPIs an additional 6% (-1.4 Hounsfield units), and Lutetium-177 a subsequent 6% (-1.3 Hounsfield units), demonstrating progressive reduction in muscle density across later stages of systemic therapy. This large longitudinal analysis of body composition in aPC patients supports the use of an automated PET-CT algorithm to identify aPC patients on systemic therapy at risk for muscle wasting.

ABSTRACT Background Prior studies in the pre‐MRI era suggest that patients with NCCN Intermediate and High Risk Grade Group 1 prostate cancer (GG1 PCa) on biopsy have increased risk for adverse oncologic outcomes. However, prostate MRI has altered patient selection for biopsy and improved prostate sampling. Herein, we examined factors associated with adverse pathologic features (APF) at radical prostatectomy (RP) and biochemical recurrence (BCR) among patients with GG1 in the MRI era. Methods A prospectively maintained institutional prostate cancer registry identified patients with GG1 PCa on biopsy who underwent RP from 2000 to 2023, stratified by MRI use. Multivariable logistic regression and Cox regression identified factors associated with APF at RP (GG3‐5, ≥ pT3a, or pN1) and BCR free survival (two consecutive PSA ≥ 0.2 ng/mL), respectively. Results Among patients without MRI ( n = 6732), NCCN risk group was associated with APF, BCR, and distant metastasis. Among 302 patients with GG1 and pre‐operative MRI, NCCN risk group was associated with neither APF nor BCR. Age (OR 1.07, 95% CI 1.01–1.14, p = 0.01), PIRADS ( p = 0.01), and % core positivity (OR 1.02, 95% CI 1.00–1.03, p = 0.04) were associated with APF. Age (HR 1.07, 95% CI 1.01–1.13, p = 0.03), APF (HR 4.36, 95% CI 2.14–8.86, p < 0.001), and positive margins (HR 4.88, 95% CI 2.39–9.98, p < 0.001) were associated with BCR. Conclusions Prior to prostate MRI, NCCN risk groups offered meaningful prognostication among patients with GG1 PCa. However, the utility of NCCN risk groups for GG1 in the MRI era appears limited. Contemporary risk stratification for GG1 should focus on biopsy and MRI characteristics rather than NCCN criteria.

BACKGROUND The authors aimed to evaluate the feasibility/safety of stereo-electroencephalography (SEEG) and SEEG-guided radiofrequency thermocoagulation (RFTC) in patients with drug-resistant epilepsy previously implanted with neuromodulation devices, using a retrospective cohort design evaluating patients treated at the Mayo Clinic Florida Epilepsy Center. OBSERVATIONS Nine patients (mean age 36.3 ± 10.9 years, 33% female) with prior implantation of neuromodulation devices were included. A vagus nerve stimulator was present in 8 of 9 patients, and 4 patients had undergone previous intracranial neuromodulation. Five patients underwent SEEG-RFTC. The mean SEEG monitoring duration was 6.5 ± 2.9 days. No intraoperative or procedural complications occurred, including hardware-related issues. No permanent or significant neurological/cognitive deficits occurred. One patient experienced transient postoperative neurological symptoms attributed to perilesional edema. Seizure reduction ranged from 50% to 75% following SEEG-RFTC. LESSONS SEEG and SEEG-RFTC are feasible in patients who have implanted neuromodulation devices, including intracranial implants. These procedures may be performed without interference with existing hardware and provide meaningful seizure reduction in highly refractory populations. Further studies with larger cohorts and longer follow-up are needed to better define efficacy and patient selection. https://thejns.org/doi/10.3171/CASE26376

Abstract Background aneurysmal subarachnoid hemorrhage (aSAH) is neurological emergency associated with substantial mortality and disability. Current grading systems such as the modified Fisher Scale (mFS) and World Federation of Neurological Societies (WFNS) score, rely on semiquantitative and examination based assessments. Hence, they demonstrate limited predictive precision. The enhanced subarachnoid hemorrhage (eSAH) score is a simplified quantitative model integrating age, Glasgow Coma Scale (GCS), and cisternal subarachnoid hemorrhage volume (SAHV) to predict clinical outcomes after aSAH. Methods We performed a retrospective multicenter cohort study that included 1088 patients across three tertiary-care centers the United States. Predictive performance for unfavorable functional outcome, in-hospital mortality and delayed cerebral ischemia (DCI) was evaluated using receiver operating characteristic (ROC) analysis and area under the curve (AUC). Comparative analyses were performed and compared to the WFNS and mFS grading systems. Results the eSAH score demonstrated excellent discrimination for unfavorable functional outcome at discharge ( AUC 0.89 ) and in-hospital mortality (AUC 0.87). The DCI subscore demonstrated good discriminatory performance for predicting DCI (AUC 0.77). Compared with conventional grading systems, this was superior to both the WFNS (AUC 0.75) and the mFS ( AUC 0.70). increasing eSAH scores were additionally associated with progressively higher rates of mortality and unfavorable functional outcomes. Conclusion the eSAH score demonstrates strong external validity, reproducibility and superior predictive performance compared with conventional grading systems in a large multicenter cohort. These findings support the clinical utility of quantitative hemorrhage burden integration for early risk stratification in patients with aSAH.

Abstract Objective Shunt-dependent hydrocephalus is a common and costly complication of aneurysmal subarachnoid hemorrhage (aSAH), affecting up to 28% of survivors. Existing prediction tools, including the Chronic Hydrocephalus Ensuing from SAH Score (CHESS), have limited discriminative accuracy. We developed the CHECKMATE score, a clinically practical tool to improve prediction of ventriculoperitoneal shunt dependency after aSAH. Methods In this multicenter retrospective cohort of 486 patients with aSAH from Mayo Clinic (January 1, 2006-December 31, 2021), we used multivariable logistic regression and machine learning to identify independent predictors of ventriculoperitoneal shunt placement. The CHECKMATE score was derived from 5 weighted variables: symptomatic hydrocephalus (10 points), intraventricular hemorrhage (5 points), SAH volume greater than 10 mL (3 points), neutrophil-to-lymphocyte ratio greater than 12 (2 points), and 10-year incremental age thresholds starting at older than 60 years (1 point each). Results Of 486 patients (mean age, 56.3 years; 64.6% female), 137 (28.2%) required ventriculoperitoneal shunt placement. The CHECKMATE score achieved an area under the curve of 0.808 (compared to 0.737 for CHESS), with a sensitivity of 0.85, specificity of 0.67, and negative predictive value of 0.92 at the optimal cutoff of 14 points. Conclusions The CHECKMATE score outperforms CHESS for predicting ventriculoperitoneal shunt dependency after aSAH and is easily used at the bedside. Its high negative predictive value helps identify low-risk patients who may benefit from earlier external ventricular drain weaning and shorter hospital stays.

Background: Artificial intelligence (AI), particularly generative and large language models, is being used in nursing education, practice, and scholarly writing. Generative AI applications have been specifically examined for their use in conducting literature reviews with evidence supporting reduced production time of scholarly work. However, there has been limited investigation of their levels of accuracy with identifying references for a literature review. Objective: The purpose of this study was to compare human-generated citations of literature reviews with AI literature-review generated citations. Methods: Using a comparative exploratory design, references from 4 human-written literature reviews, 2 published and 2 unpublished, on 4 different topics, were compared to references derived from 2 AI literature applications, Consensus and Elicit. Three prompting strategies were utilized, including prompts generated using ChatGPT-4. Agreement between the AI and human references was evaluated. Results: The percent of agreement between AI and human generated reference lists ranged from 0% to 63.6%. The Consensus application had a greater overall mean rate of match (21.3%) as compared to Elicit (3.7%). The use of a ChatGPT-4 prompt did not significantly impact results, and there were no differences based on published or unpublished literature reviews. Conclusion: The 2 literature-based applications examined in this study offered a glimpse of their potential use and limitations. The use of an AI literature review application may support but not replace human work.

ABSTRACT Background While guidelines state that patients with NCCN favorable intermediate risk (FIR) prostate cancer (PCa) may consider active surveillance (AS), there is a relative lack of longer term follow up data informing AS inclusion criteria of patients with Grade Group (GG) 2 prostate cancer in the MRI era. Here we evaluate patient outcomes from a MRI‐screened AS‐eligible cohort of FIR GG2 PCa receiving radical prostatectomy (RP). Methods Patients with prostate MRI, NCCN FIR GG2 PCa (PSA < 10 ng/mL, ≤ cT2a, < 50% core positivity), and no prior treatments who underwent RP from 2015 to 2023 were included from a prospectively maintained prostatectomy registry. Primary outcomes were adverse pathologic features (APF) at RP (GG3‐5, ≥ pT3a, or pN1) and biochemical recurrence (BCR). Logistic regression and Cox regression identified factors associated with APF at RP and time to BCR, respectively. Results Of 522 patients, 110 (21%) had APF at RP and 45 (9%) developed BCR with median follow up 2.4 years (IQR 1.3–2.8). On multivariable logistic regression, % Gleason pattern 4 (%GP4, %GP4 > 25% OR 2.14, 95% CI 1.28–3.58, p = 0.004) was independently associated with APF. On multivariable Cox regression for time to BCR, PSAD (HR 1.06, 95% CI 1.04–1.09, p < 0.001) and positive surgical margins (HR 1.06, 95% CI 1.09–3.78, p = 0.03) were independently associated with BCR. PIRADS, % core positivity, and specimen involvement were associated with neither APF nor BCR. Conclusions % Gleason pattern 4 > 25% and PSAD are the primary factors associated with adverse outcomes and should be considered for patients with FIR GG2 PCa considering active surveillance. PIRADS and measures of biopsy cancer volume were not associated with APF or BCR. These results may inform patient selection for active surveillance among patients with FIR GG2 PCa.