Understanding the association between fatigue and neurocognitive functioning in patients with glioma: A cross-sectional multinational study.

Background: Fatigue and neurocognitive impairment are highly prevalent in patients with glioma, significantly impacting health-related quality of life. Despite the presumed association between these two factors, evidence remains sparse. Therefore, we aimed to investigate this relationship using multinational data. Methods: We analyzed data on self-reported fatigue and neurocognitive outcomes from postoperative patients with glioma from the University of California San Francisco (n = 100, UCSF) and Amsterdam University Medical Center (n = 127, Amsterdam UMC). We used multiple linear regression models to assess associations between fatigue and seven (sub)domains of neurocognitive functioning and latent profile analysis to identify distinct patterns of fatigue and neurocognitive functioning. Results: UCSF patients were older (median age 49 vs. 43 years, P = .002), had a higher proportion of grade 4 tumors (32% vs. 18%, P = .03), and had more neurocognitive deficits (P = .01). While the number of clinically fatigued patients was similar between sites (64% vs. 58%, P = .12), fatigue and the number of impaired neurocognitive domains were not correlated (P = .16-.72). At UCSF, neurocognitive domains were not related to fatigue, and at Amsterdam UMC attention and semantic fluency explained only 4-7% of variance in fatigue. Across institutions, we identified four distinct patterns of neurocognitive functioning, which were not consistently associated with fatigue. Conclusions: Although individual patients might experience both fatigue and neurocognitive impairment, the relationship between the two is weak. Consequently, both fatigue and neurocognitive functioning should be independently assessed and treated with targeted therapies.

Frequency and burden of potentially treatable symptoms in glioma patients with stable disease.

Background & aims: Glioma patients experience a multitude of symptoms that negatively affect their health-related quality of life. Symptoms vary greatly across disease phases, and the patients' stable phase might be particularly suitable for assessing and treating symptoms. Identifying symptoms and patients' needs is a first step toward improving patient care. In glioma patients with stable disease, we assessed the frequency and burden of patient-reported symptoms, examined how these symptoms co-occur, and also determined whether patients would consider treatment to ameliorate specific symptoms. Methods: In this retrospective study, patients rated the frequency and burden of seventeen symptoms on a seven-point Likert scale and stated whether they would consider treatment for these symptoms. Correlations between frequency, burden, and considering treatment were evaluated with Kendall's Tau correlation coefficients. Based on partial correlations between symptom frequencies we visualized the symptoms as a network. Results: Fifty-two glioma patients with stable disease were included (31 WHO grade II/III, 21 WHO grade IV). The top five symptoms were fatigue, memory problems, reduced physical fitness, concentration problems, and drowsiness. Fatigue had the highest median frequency (4.5, interquartile range 2.5). Over half of the patients experienced three or more symptoms simultaneously and associations between all symptoms were depicted as a network. Overall, 35% of patients would consider treatment for at least one symptom. The wish to undergo symptom treatment correlated only moderately with symptom frequency and burden (range of correlations 0.24-0.57 and 0.28-0.61, respectively). Conclusion: Glioma patients with stable disease experience multiple symptoms with a consequently high symptom burden. Despite the high prevalence of symptoms, the inclination for symptom management interventions was relatively low. The most frequent and burdensome symptoms and the way they are interrelated could serve as a roadmap for future research on symptom management in these patients.

Cannabinoids to Improve Health-Related Quality of Life in Patients with Neurological or Oncological Disease: A Meta-Analysis.

Background: Cannabinoids have been suggested to alleviate frequently experienced symptoms of reduced mental well-being such as anxiety and depression. Mental well-being is an important subdomain of health-related quality of life (HRQoL). Reducing symptoms and maintaining HRQoL are particularly important in malignant primary brain tumor patients, as treatment options are often noncurative and prognosis remains poor. These patients frequently report unprescribed cannabinoid use, presumably for symptom relieve. As studies on brain tumor patients specifically are lacking, we performed a meta-analysis of the current evidence on cannabinoid efficacy on HRQoL and mental well-being in oncological and neurological patients. Methods: We performed a systematic PubMed, PsychINFO, Embase, and Web of Science search according to PRISMA guidelines on August 2 and 3, 2021. We included randomized controlled trials (RCTs) that assessed the effects of tetrahydrocannabinol (THC) or cannabidiol (CBD) on general HRQoL and mental well-being. Pooled effect sizes were calculated using Hedges g. Risk of bias of included studies was assessed using Cochrane's Risk of Bias tool. Results: We included 17 studies: 4 in oncology and 13 in central nervous system (CNS) disease. Meta-analysis showed no effect of cannabinoids on general HRQoL (g=-0.02 confidence interval [95% CI -0.11 to 0.06]; p=0.57) or mental well-being (g=-0.02 [95% CI -0.16 to 0.13]; p=0.81). Conclusions: RCTs in patients with cancer or CNS disease showed no effect of cannabinoids on HRQoL or mental well-being. However, studies were clinically heterogeneous and since many glioma patients currently frequently use cannabinoids, future studies are necessary to evaluate its value in this specific population.

Toward unraveling the correlates of fatigue in glioma.

Background: Even though fatigue is one of the most prevalent and burdensome symptoms in patients with glioma, its etiology and determinants are still poorly understood. We aimed to identify which demographic, tumor- and treatment-related characteristics and patient-reported outcome measures (PROMs) are associated with or are predictors of fatigue in glioma. Methods: In this retrospective observational study, we included glioma patients with preoperative and postoperative assessments including PROMs on fatigue, depression, cognitive functioning, and health-related quality of life (HRQoL). Linear mixed models were used to identify which clinical factors and PROMs were associated with fatigue and linear multiple regression was used to detect predictors of postoperative fatigue. Results: In this study, 222 patients were included (78% grade II-III glioma, 22% grade IV). These patients had performed 333 assessments (193 preoperative and 116 one year postoperatively). Of all assessments, 39% was indicative of severe fatigue. Several HRQoL domains, depression, and right-sided tumors were significantly associated with fatigue (marginal R 2 = 0.63). Contrary to common expectations, tumor type, treatment-related factors, and timing of the assessment, were not associated with fatigue. In a subgroup of 70 patients with follow-up assessments, preoperative fatigue, and physical functioning were predictors of postoperative fatigue (adjusted R 2 = 0.31). Conclusion: Fatigue is a complex symptom, which should not solely be attributed to the tumor or its treatment, but is instead related to different aspects of mood and HRQoL. These insights are important in understanding fatigue and could guide symptom management, especially in patients with lower-grade tumors.

Determining a target SpO2 to maintain PaO2 within a physiological range.

OBJECTIVE: In the context of an ongoing debate on the potential risks of hypoxemia and hyperoxemia, it seems prudent to maintain the partial arterial oxygen pressure (PaO2) in a physiological range during administration of supplemental oxygen. The PaO2 and peripheral oxygen saturation (SpO2) are closely related and both are used to monitor oxygenation status. However, SpO2 values cannot be used as an exact substitute for PaO2. The aim of this study in acutely ill and stable patients was to determine at which SpO2 level PaO2 is more or less certain to be in the physiological range. METHODS: This is an observational study prospectively collecting data pairs of PaO2 and SpO2 values in patients admitted to the emergency room or intensive care unit (Prospective Inpatient Acutely ill cohort; PIA cohort). A second cohort of retrospective data of patients who underwent pulmonary function testing was also included (Retrospective Outpatient Pulmonary cohort; ROP cohort). Arterial hypoxemia was defined as PaO2 < 60 mmHg and hyperoxemia as PaO2 > 125 mmHg. The SpO2 cut-off values with the lowest risk of hypoxemia and hyperoxemia were determined as the 95th percentile of the observed SpO2 values corresponding with the observed hypoxemic and hyperoxemic PaO2 values. RESULTS: 220 data pairs were collected in the PIA cohort. 95% of hypoxemic PaO2 measurements occurred in patients with an SpO2 below 94%, and 95% of hyperoxemic PaO2 measurements occurred in patients with an SpO2 above 96%. Additionally in the 1379 data pairs of the ROP cohort, 95% of hypoxemic PaO2 measurements occurred in patients with an SpO2 below 93%. CONCLUSION: The SpO2 level marking an increased risk of arterial hypoxemia is not substantially different in acutely ill versus stable patients. In acutely ill patients receiving supplemental oxygen an SpO2 target of 95% maximizes the likelihood of maintaining PaO2 in the physiological range.

Renal Resistive Index: Response to Shock and its Determinants in Critically Ill Patients.

INTRODUCTION: Shock is characterized by micro- and macrovascular flow impairment contributing to acute kidney injury (AKI). Routine monitoring of the circulation regards the macrocirculation but not the renal circulation which can be assessed with Doppler ultrasound as renal resistive index (RRI). RRI reflects resistance to flow. High RRI predicts persistent AKI. Study aims were to determine whether RRI is elevated in shock and to identify determinants of RRI. MATERIALS AND METHODS: This prospective observational cohort study included two cohorts of patients, with and without shock less than 24-h after intensive care admission. Apart from routine monitoring, three study measurements were performed simultaneously: RRI, sublingual microcirculation, and bioelectral impedance analysis. RESULTS: A total of 92 patients were included (40 shock, 52 nonshock), median age was 69 [60-76] vs. 67 [59-76], P = 0.541; APACHE III was 87 [65-119] vs. 57 [45-69], P < 0.001. Shock patients had higher RRI than patients without shock (0.751 [0.692-0.788] vs. 0.654 [0.610-0.686], P < 0.001). Overall, high age, APACHE III score, lactate, vasopressor support, pulse pressure index (PPI), central venous pressure (CVP), fluid balance, and low preadmission estimated glomerular filtration rate, mean arterial pressure (MAP), creatinine clearance, and reactance/m were associated with high RRI at univariable regression (P < 0.01). Microcirculatory markers were not. At multivariable regression, vasopressor support, CVP, PPI and MAP, reactance/m, and preadmission eGFR were independent determinants of RRI (n = 92, adj. R = 0.587). CONCLUSIONS: Patients with shock have a higher RRI than patients without shock. Independent determinants of high RRI were pressure indices of the systemic circulation, low membrane capacitance, and preadmission renal dysfunction. Markers of the sublingual microcirculation were not.

Renal resistive index as an early predictor and discriminator of acute kidney injury in critically ill patients; A prospective observational cohort study.

BACKGROUND: Acute kidney injury (AKI) complicates shock. Diagnosis is based on rising creatinine, a late phenomenon. Intrarenal vasoconstriction occurs earlier. Measuring flow resistance in the renal circulation, Renal Resistive Index (RRI), could become part of vital organ function assessment using Doppler ultrasound. Our aim was to determine whether RRI on ICU admission is an early predictor and discriminator of AKI developed within the first week. METHODS: In this prospective cohort of mixed ICU patients with and without shock, RRI was measured <24-h of admission. Besides routine variables, sublingual microcirculation and bioelectrical impedance were measured. AKI was defined by the Kidney Disease Improving Global Outcomes criteria. Uni- and multivariate regression and Receiver Operating Characteristics curve analyses were performed. RESULTS: Ninety-nine patients were included, median age 67 years (IQR 59-75), APACHE III score 67 (IQR 53-89). Forty-nine patients (49%) developed AKI within the first week. AKI patients had a higher RRI on admission than those without: 0.71 (0.69-0.73) vs. 0.65 (0.63-0.68), p = 0.001. The difference was significant for AKI stage 2: RRI = 0.72 (0.65-0.80) and 3: RRI = 0.74 (0.67-0.81), but not for AKI stage 1: RRI = 0.67 (0.61-0.74). On univariate analysis, RRI significantly predicted AKI 2-3: OR 1.012 (1.006-1.019); Area Under the Curve (AUC) of RRI for AKI 2-3 was 0.72 (0.61-0.83), optimal cut-off 0.74, sensitivity 53% and specificity 87%. On multivariate analysis, RRI remained significant, independent of APACHE III and fluid balance; adjusted OR: 1.008 (1.000-1.016). CONCLUSIONS: High RRI on ICU admission was a significant predictor for development of AKI stage 2-3 during the first week. High RRI can be used as an early warning signal RRI, because of its high specificity. A combined score including RRI, APACHE III and fluid balance improved AKI prediction, suggesting that vasoconstriction or poor vascular compliance, severity of disease and positive fluid balance independently contribute to AKI development. TRIAL REGISTRATION: ClinicalTrials.gov NCT02558166.