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Yanli Zeng

Publications and source records attributed to Yanli Zeng.

2 recordsLinked to original sources

Global prevalence and associated factors of turnover intention among intensive care nurses: A systematic review and meta-analysis.

OBJECTIVES: To estimate the global prevalence of two distinct turnover intentions among intensive care unit (ICU) nurses-intention to leave the ICU and intention to leave the nursing profession-identify significant sources of heterogeneity, and synthesise associated psychosocial factors. METHODS: Ten databases were systematically searched from inception to September 28, 2025. Two reviewers independently conducted study selection, data extraction, and quality appraisal using Joanna Briggs Institute checklists. Random-effects meta-analyses were performed to estimate pooled prevalence and associated factors. Subgroup and meta-regression analyses explored potential sources of heterogeneity. Associated factors were pooled as odds ratios (ORs) and interpreted within an integrated Job Demands-Resources and Theory of Planned Behavior framework. RESULTS: Forty-six studies published between 2007 and 2025, involving 39,246 ICU nurses, were included. The pooled prevalence was 30.7% for intention to leave the ICU and 27.5% for intention to leave the nursing profession. Significant sources of heterogeneity included ICU type, geographic region, publication year, study design, measurement tool, and sampling method. Depression, burnout, high workload, and unsafe patient-to-nurse ratios were associated with increased turnover intention, whereas positive work environments, perceived organisational support, and nursing competence were protective factors. No significant publication bias was detected. CONCLUSIONS: Turnover intention affects approximately one-third of ICU nurses globally and varies across clinical and geographical contexts. Excessive workload, inadequate organisational support, and unfavourable work environments appear to be important contributors to turnover intention among ICU nurses. IMPLICATIONS FOR CLINICAL PRACTICE: Strategies to reduce turnover intention among ICU nurses should focus on reducing excessive workload, improving staffing conditions, strengthening organisational support, and fostering positive work environments. Promoting supportive and sustainable ICU work environments may help improve nurse retention and maintain the quality of critical care services.

Humans

Multi-Omics Biomarker Signatures for Precision Diagnosis and Prognosis in Primary Liver Cancer: A Literature Review.

Primary liver cancer (PLC) is a biologically heterogeneous group of malignancies dominated by hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), and a smaller subset of combined hepatocellular-cholangiocarcinoma (cHCC-CCA), and its clinical burden remains high because current diagnostic and prognostic tools do not adequately capture molecular diversity. Conventional imaging, serum markers, and histopathological assessment remain insufficient for precise early diagnosis, subtype-resolved classification, and outcome stratification, while tissue and liquid biopsy approaches have expanded the range of analytes available for clinical assessment. Recent studies have identified candidate biomarker signatures across genomic, epigenomic, transcriptomic, proteomic, metabolomic, and circulating layers, suggesting that integrated multi-omics profiling may better represent tumor lineage, clonal evolution, immune context, and therapeutic vulnerability than isolated molecular readouts. However, these layers are not equally mature for clinical use: genomic testing is closest to routine therapeutic application in iCCA, plasma methylation assays are advancing for HCC surveillance augmentation, and many proteomic or metabolomic panels remain validation-stage tools. Their clinical value remains constrained by sampling bias, biospecimen-dependent signal loss, assay standardization, cost, and the need for prospective validation across clinically diverse populations. This narrative review critically synthesizes current evidence on multi-omics biomarker signatures for precision diagnosis and prognosis in primary liver cancer and argues that clinically useful signatures should be question-specific, stage-aware, and specimen-aware rather than universal multi-analyte panels.

Humans