Association between Cognitive Function and Physical Function, Frailty, and Quality of Life in Older Breast Cancer Survivors.

Background: Older cancer survivors in general are at greater risk for cancer-related cognitive impairment (CRCI), yet few studies have explored its association with health outcomes. This study examined the association between subjective and objective measures of cognitive function and physical function, frailty, and quality of life (QoL) among older breast cancer survivors.

Materials And Methods: Older breast cancer survivors who reported cognitive concerns completed surveys on patient-reported cognitive function, physical function, frailty, and QoL as well as objective tests of visuospatial working memory and sustained attention.

Zero-shot learning to extract assessment criteria and medical services from the preventive healthcare guidelines using large language models.

Objectives: The integration of these preventive guidelines with Electronic Health Records (EHRs) systems, coupled with the generation of personalized preventive care recommendations, holds significant potential for improving healthcare outcomes. Our study investigates the feasibility of using Large Language Models (LLMs) to automate the assessment criteria and risk factors from the guidelines for future analysis against medical records in EHR.

Materials And Methods: We annotated the criteria, risk factors, and preventive medical services described in the adult guidelines published by United States Preventive Services Taskforce and evaluated 3 state-of-the-art LLMs on extracting information in these categories from the guidelines automatically.

Challenges and Opportunities to Advance Adolescent Health Measurement in Armenia: Alignment Between Global Priority Indicators and National Policies, and Feasibility of Collecting Sexual, Reproductive, and Mental Health Indicators.

Purpose: To assess alignment of the Global Action for Measurement of Adolescent health (GAMA) draft adolescent health indicators with national policies and explore challenges and opportunities for collecting data on adolescent sexual, reproductive, and mental health in Armenia.

Methods: We reviewed Armenia's national laws, decrees, policies, strategies, and programs for content related to the draft indicators. We conducted three focus group discussions with government and nongovernmental stakeholders and youth representatives on the feasibility of collecting the draft indicators, and analyzed the discussion segments related to sexual, reproductive, and mental health indicators.

Exploring a Preliminary Set of Indicators to Measure Adolescent Health: Results From a 12-Country Feasibility Study.

Purpose: To explore data availability, perceived relevance, acceptability and feasibility of implementing 52 draft indicators for adolescent health measurement in different countries globally.

Methods: A mixed-methods, sequential explanatory study was conducted in 12 countries. An online spreadsheet was used to assess data availability and a stakeholder survey to assess perceived relevance, acceptability, and feasibility of implementing each draft indicator proposed by the Global Action for Measurement of Adolescent health (GAMA).

Symptom clusters in breast cancer survivors with and without type 2 diabetes over the cancer trajectory.

Objective: This study aimed to investigate symptoms and symptom clusters in breast cancer survivors (BCS) with and without type 2 diabetes across three crucial periods during the cancer trajectory (0-6 months, 12-18 months, and 24-30 months) post-initial chemotherapy.

Methods: Eight common symptoms in both BCS and individuals with diabetes were identified through natural language processing of electronic health records from January 2007 to December 2018. Exploratory factor analysis was employed to discern symptom clusters, evaluating their stability, consistency, and clinical relevance.

Cell-type expression and activation by light of neuropsins in the developing and mature retina.

Photosensitive opsins detect light and perform image- or nonimage-forming tasks. Opsins such as the "classical" visual opsins and melanopsin are well studied. However, the retinal expression and functions of a novel family of neuropsins are poorly understood.

SymptomGraph: Identifying Symptom Clusters from Narrative Clinical Notes using Graph Clustering.

Patients with cancer or other chronic diseases often experience different symptoms before or after treatments. The symptoms could be physical, gastrointestinal, psychological, or cognitive (memory loss), or other types. Previous research focuses on understanding the individual symptoms or symptom correlations by collecting data through symptom surveys and using traditional statistical methods to analyze the symptoms, such as principal component analysis or factor analysis.

Symptom Clusters in Patients With Colorectal Cancer and Diabetes Over Time.

Objectives: To examine symptoms and symptom clusters in patients with colorectal cancer (CRC) with or without diabetes at three key periods (0-6 months, 12-18 months, and 24-30 months) post-initial chemotherapy.

Sample & Setting: Patients with CRC from a cancer center in the midwestern United States between January 2007 and December 2017.

Methods & Variables: Eight of the most common symptoms (fatigue, gastrointestinal issues, depression, anxiety, peripheral neuropathy, physical function, cognition, and sleep disturbance) reported by patients with CRC and patients with diabetes were extracted from electronic health records.

Effect of COVID-19 on Type 2 Diabetes Self-Care Behaviors: A Rapid Review.

Objective: The aim of this review was to describe how the coronavirus disease 2019 (COVID-19) lockdown affected the self-care behaviors of people living with type 2 diabetes.

Methods: A systematic rapid review was conducted using four electronic databases. Studies reporting on the lockdown's impact on at least one of the self-care behaviors that were published from January 2020 through October 2021 were included.

The Experience of Peripheral Neuropathy Symptoms in Breast Cancer Survivors With Diabetes.

Background: Diabetes (type 2) is a risk factor for developing peripheral neuropathy (PN) symptoms in breast cancer survivors (BCS). Because PN symptoms are associated with deficits in physical functioning and quality of life, more information is needed about the effects of PN symptoms on the lives of BCS with diabetes.

Objective: The aim of this study was to describe the experiences of PN among BCS with diabetes from their own perspectives.

Acceptability of computerized cognitive training and global cognitive stimulating-based games delivered remotely: Results from a randomized controlled trial to address cancer and cancer-related cognitive impairment in breast cancer survivors.

Background: Although the cancer-related cognitive impairment (CRCI) is a common symptom incurred by the breast cancer survivors (BCS), more emphasis is needed in identifying acceptable interventions for survivors.

Purpose: The purpose of this qualitative descriptive study was to examine the acceptability of cognitive programs by identifying the facilitators and barriers for implementing computerized cognitive training (BrainHQ) and computerized global cognitive stimulating-based games (e.g.

Impact of diabetes (type 2) and glycemic control on health-related outcomes of patients receiving chemotherapy for non-metastatic breast cancer: a retrospective analysis.

Purpose: To examine the impact of diabetes (type 2) and glycemic control on healthcare-related outcomes (healthcare utilization, adverse effects, and treatment modifications) in non-metastatic breast cancer (NMBC) patients during chemotherapy treatment.

Methods: This was a retrospective study of 243 NMBC patients (stages 1-3) with/without diabetes receiving neoadjuvant or adjuvant cytotoxic chemotherapy. The primary study endpoint was to compare healthcare utilization between NMBC patients with and without diabetes.

Hyperglycemia, symptoms, and symptom clusters in colorectal cancer survivors with type 2 diabetes.

Purpose: The purpose of the study was to compare the individual and total number of symptoms and explore symptom clusters by hyperglycemia status in colorectal cancer survivors (CRCS) with diabetes (type 2).

Methods: A retrospective cohort study was conducted, whereby symptom data were extracted from clinical notes in electronic health records. CRCS (stage II or III) diagnosed between 2007 and 2017 who had diabetes and at least one HbA1c within 8 months of initial chemotherapy were included.

Differences in Health-Related Outcomes and Health Care Resource Utilization in Breast Cancer Survivors With and Without Type 2 Diabetes.

Purpose: Up to 74% of breast cancer survivors (BCS) have at least one preexisting comorbid condition, with diabetes (type 2) common. The purpose of this study was to examine differences in health-related outcomes (anemia, neutropenia, and infection) and utilization of health care resources (inpatient, outpatient, and emergency visits) in BCS with and without diabetes.

Methods: In this retrospective cohort study, data were leveraged from the electronic health records of a large health network linked to the Indiana State Cancer Registry.

A Deep Language Model for Symptom Extraction From Clinical Text and its Application to Extract COVID-19 Symptoms From Social Media.

Patients experience various symptoms when they haveeither acute or chronic diseases or undergo some treatments for diseases. Symptoms are often indicators of the severity of the disease and the need for hospitalization. Symptoms are often described in free text written as clinical notes in the Electronic Health Records (EHR) and are not integrated with other clinical factors for disease prediction and healthcare outcome management.

A Computational Framework to Analyze the Associations Between Symptoms and Cancer Patient Attributes Post Chemotherapy Using EHR Data.

Patients with cancer, such as breast and colorectal cancer, often experience different symptoms post-chemotherapy. The symptoms could be fatigue, gastrointestinal (nausea, vomiting, lack of appetite), psychoneurological symptoms (depressive symptoms, anxiety), or other types. Previous research focused on understanding the symptoms using survey data.

Cognitive impairment in syphilis: Does treatment based on cerebrospinal fluid analysis improve outcome?

Background: Individuals with previous syphilis may experience cognitive impairment. The goal of this study was to determine if those at high risk for laboratory-defined neurosyphilis are cognitively impaired, and whether treatment based on cerebrospinal fluid (CSF) findings results in better outcomes.

Methods: Participants had a new syphilis diagnosis, serum RPR titer ≥ 1:32 or peripheral blood CD4+ T cells ≤ 350/ul (in persons living with HIV) and did not endorse neurological symptoms.

Association of cognitive impairment and breast cancer survivorship on quality of life in younger breast cancer survivors.

Purpose: Younger breast cancer survivors (BCS) often report cognitive impairment and poor quality of life (QoL), which could be interrelated. The purpose of this study was to examine the association of cognitive impairment and breast cancer status (BCS versus healthy control (HC)), with QoL, which included psychological (depressive symptoms, well-being, perceived stress, and personal growth) and physical well-being (physical functioning and fatigue).

Methods: Four hundred ninety-eight BCS (≤45 years at diagnosis) who were 3 to 8 years post-chemotherapy treatment and 394 HC completed subjective questionnaires and a one-time neuropsychological assessment, including tests of attention, memory, processing speed, and verbal fluency.

Analyzing the symptoms in colorectal and breast cancer patients with or without type 2 diabetes using EHR data.

This research extracted patient-reported symptoms from free-text EHR notes of colorectal and breast cancer patients and studied the correlation of the symptoms with comorbid type 2 diabetes, race, and smoking status. An NLP framework was developed first to use UMLS MetaMap to extract all symptom terms from the 366,398 EHR clinical notes of 1694 colorectal cancer (CRC) patients and 3458 breast cancer (BC) patients. Semantic analysis and clustering algorithms were then developed to categorize all the relevant symptoms into eight symptom clusters defined by seed terms.