Trajectories of fatigue in cancer patients during psychological care

OBJECTIVE: Psycho-oncological institutions offer specialized care for cancer patients. Little is known how this care might impact fatigue. This study aimed to identify fatigue trajectories during psychological care, examined factors distinguishing these trajectories and predicted fatigue severity after nine months of psychological care. DESIGN: Naturalistic, longitudinal study of 238 cancer patients receiving psycho-oncological care in the Netherlands. Data were collected before initiation of psychological care (T1) and three (T2) and nine months (T3) afterwards. Latent class growth analysis, repeated measure analyses (RMA) and linear regression analysis were performed. MAIN OUTCOME MEASURES: Fatigue severity: Checklist Individual Strength. RESULTS: Three fatigue trajectories were identified: high- (30%), moderate- (62%) and low-level fatigue (8%). While statistically significant decreases in fatigue were found, this decrease was not clinically relevant. RMA showed main effects for time for fatigue trajectories on depression, anxiety, personal control and illness cognitions. Fatigue severity and physical symptoms at T1, but not demographic or clinical factors, were predictive of fatigue severity at T3. CONCLUSIONS: Fatigue is very common during psycho-oncological care, and notably not clinically improving. As symptoms of fatigue, depression, anxiety and physical symptoms often cluster, supplementary fatigue treatment should be considered when it is decided to treat other symptoms first

Therapeutic strategies to slow chronic kidney disease progression

Childhood chronic kidney disease commonly progresses toward end-stage renal failure, largely independent of the underlying disorder, once a critical impairment of renal function has occurred. Hypertension and proteinuria are the most important independent risk factors for renal disease progression. Therefore, current therapeutic strategies to prevent progression aim at controlling blood pressure and reducing urinary protein excretion. Renin-angiotensin-system (RAS) antagonists preserve kidney function not only by lowering blood pressure but also by their antiproteinuric, antifibrotic, and anti-inflammatory properties. Intensified blood pressure control, probably aiming for a target blood pressure below the 75th percentile, may exert additional renoprotective effects. Other factors contributing in a multifactorial manner to renal disease progression include dyslipidemia, anemia, and disorders of mineral metabolism. Measures to preserve renal function should therefore also comprise the maintenance of hemoglobin, serum lipid, and calcium-phosphorus ion product levels in the normal range

Degradation of haloaromatic compounds

An ever increasing number of halogenated organic compounds has been produced by industry in the last few decades. These compounds are employed as biocides, for synthetic polymers, as solvents, and as synthetic intermediates. Production figures are often incomplete, and total production has frequently to be extrapolated from estimates for individual countries. Compounds of this type as a rule are highly persistent against biodegradation and belong, as "recalcitrant" chemicals, to the class of so-called xenobiotics. This term is used to characterise chemical substances which have no or limited structural analogy to natural compounds for which degradation pathways have evolved over billions of years. Xenobiotics frequently have some common features. e.g. high octanol/water partitioning coefficients and low water solubility which makes for a high accumulation ratio in the biosphere (bioaccumulation potential). Recalcitrant compounds therefore are found accumulated in mammals, especially in fat tissue, animal milk supplies and also in human milk. Highly sophisticated analytical techniques have been developed for the detection of organochlorines at the trace and ultratrace level

Integrating AI in Lipedema Management: Assessing the Efficacy of GPT-4 as a Consultation Assistant

The role of artificial intelligence (AI) in healthcare is evolving, offering promising avenues for enhancing clinical decision making and patient management. Limited knowledge about lipedema often leads to patients being frequently misdiagnosed with conditions like lymphedema or obesity rather than correctly identifying lipedema. Furthermore, patients with lipedema often present with intricate and extensive medical histories, resulting in significant time consumption during consultations. AI could, therefore, improve the management of these patients. This research investigates the utilization of OpenAI’s Generative Pre-Trained Transformer 4 (GPT-4), a sophisticated large language model (LLM), as an assistant in consultations for lipedema patients. Six simulated scenarios were designed to mirror typical patient consultations commonly encountered in a lipedema clinic. GPT-4 was tasked with conducting patient interviews to gather medical histories, presenting its findings, making preliminary diagnoses, and recommending further diagnostic and therapeutic actions. Advanced prompt engineering techniques were employed to refine the efficacy, relevance, and accuracy of GPT-4’s responses. A panel of experts in lipedema treatment, using a Likert Scale, evaluated GPT-4’s responses across six key criteria. Scoring ranged from 1 (lowest) to 5 (highest), with GPT-4 achieving an average score of 4.24, indicating good reliability and applicability in a clinical setting. This study is one of the initial forays into applying large language models like GPT-4 in specific clinical scenarios, such as lipedema consultations. It demonstrates the potential of AI in supporting clinical practices and emphasizes the continuing importance of human expertise in the medical field, despite ongoing technological advancements

Trajectories of fatigue in cancer patients during psychological care

Objective: Psycho-oncological institutions offer specialized care for cancer patients. Little is known how this care might impact fatigue. This study aimed to identify fatigue trajectories during psychological care, examined factors distinguishing these trajectories and predicted fatigue severity after nine months of psychological care. Design: Naturalistic, longitudinal study of 238 cancer patients receiving psycho-oncological care in the Netherlands. Data were collected before initiation of psychological care (T1) and three (T2) and nine months (T3) afterwards. Latent class growth analysis, repeated measure analyses (RMA) and linear regression analysis were performed. Main Outcome Measures: Fatigue severity: Checklist Individual Strength. Results: Three fatigue trajectories were identified: high- (30%), moderate- (62%) and low-level fatigue (8%). While statistically significant decreases in fatigue were found, this decrease was not clinically relevant. RMA showed main effects for time for fatigue trajectories on depression, anxiety, personal control and illness cognitions. Fatigue severity and physical symptoms at T1, but not demographic or clinical factors, were predictive of fatigue severity at T3. Conclusions: Fatigue is very common during psycho-oncological care, and notably not clinically improving. As symptoms of fatigue, depression, anxiety and physical symptoms often cluster, supplementary fatigue treatment should be considered when it is decided to treat other symptoms first