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Record W4405897757 · doi:10.1212/wnl.0000000000210130

Chemotherapy-Related Cognitive Impairment and Changes in Neural Network Dynamics

2024· review· en· W4405897757 on OpenAlexaboutno aff
Sandra Leskinen, Samir Alsalek, Rosivel Galvez, Favour C. Ononogbu-Uche, Harshal A. Shah, Morana Vojnic, Randy S. D’Amico

Bibliographic record

VenueNeurology · 2024
Typereview
Languageen
FieldMedicine
TopicCancer-related cognitive impairment studies
Canadian institutionsnot available
Fundersnot available
KeywordsCognitive impairmentCognitionMedicineArtificial neural networkNeurosciencePsychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: This systematic review aims to synthesize the current literature on the association between chemotherapy (CTX) and chemotherapy-related cognitive impairment (CRCI) with functional and structural brain alterations in patients with noncentral nervous system cancers. METHODS: A comprehensive search of the PubMed/MEDLINE, Web of Science, and Embase databases was conducted, and results were reported following preferred reporting items for systematic review and meta-analyses guidelines. Data on study design, comparison cohort characteristics, patient demographics, cancer type, CTX agents, neuroimaging methods, structural and functional connectivity (FC) changes, and cognitive/psychological assessments in adult patients were extracted and reported. Study quality was assessed using an adapted version of the Newcastle-Ottawa Scale (NOS) for observational studies. Qualitative synthesis of cognitive and psychological testing outcomes, functional and structural connectivity changes, and their associations with CRCI were performed. RESULTS: From 11,335 records identified, 63 studies analyzing 3,642 patients were included. Study designs included 24 prospective studies, 1 retrospective study, 36 cross-sectional studies, and 2 longitudinal studies. Most studies (75%) focused on patients with breast cancer. Common neuroimaging techniques included functional magnetic resonance imaging and diffusion tensor imaging. Postchemotherapy, many studies reported structural and FC alterations in brain networks such as the default mode, central executive, and dorsal attention networks. Cognitive function was assessed in 56 of the 63 included studies. Of the studies examining specific cognitive domains, 64% reported worsened learning and memory, 56% found impaired processing speed, and 70% identified deficits in attention/working memory in patients after CTX. Of the studies examining associations between connectivity changes and worsened cognitive function, 72% reported significant correlations in postchemotherapy patients. However, most of these studies were of low evidence, while 45% of high evidence-level studies, including prospective cohort studies, did not find significant associations between connectivity alterations and cognitive impairments. DISCUSSION: While there is evidence suggesting CTX affects brain connectivity and neural network dynamics that can lead to cognitive difficulties, the findings are inconsistent. More robust and standardized research is needed to conclusively determine the extent of these effects and to develop targeted interventions for mitigating potential cognitive impairments in patients undergoing systemic treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0060.006
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.326
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2024
Admission routes1
Has abstractyes

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