The predictive value of the pretreatment prognostic nutritional index (PNI) for head and neck cancer (HNC) remains controversial. We conducted a meta-analysis to assess the predictive value of PNI in HNC patients. A systematic search through internet databases including PubMed, Embase, and Cochrane Library for qualified studies estimating the association of PNI with HNC patient survival was performed. Overall survival (OS), progression-free survival (PFS), disease-specific survival (DSS), disease-free survival (DFS) and distant metastasis-free survival (DMFS) data were collected and evaluated. A random-effects model was used to calculate the pooled hazard ratios (pHRs) and corresponding 95% confidence intervals (CIs). A total of 7815 HNC patients from 14 eligible studies were involved. Pooled analysis showed that low pretreatment PNI was correlated with poor OS (pHR: 1.93, 95% CI 1.62–2.30, p < 0.001), PFS (pHR: 1.51, 95% CI 1.19–1.92, p = 0.008), DSS (pHR: 1.98, 95% CI 1.12–3.50, p < 0.001), DFS (pHR: 2.20, 95% CI 1.66–2.91, p < 0.001) and DMFS (pHR: 2.04, 95% CI 1.74–2.38, p < 0.001). Furthermore, low pretreatment PNI was correlated with poor OS despite variations in the cancer site, sample size, PNI cut-off value, analysis method (multivariate analysis or univariate analysis) and treatment modality in subgroup analysis. Elevated pretreatment PNI is correlated with a superior prognosis in HNC patients and could be used as a biomarker in clinical practice for prognosis prediction and treatment stratification.

The C-reactive protein-to-albumin ratio is a proven prognostic predictor of nasopharyngeal carcinoma. However, the role of the C-reactive protein-to-albumin ratio in other head and neck cancers remains unclear. This meta-analysis explored the prognostic value of the C-reactive protein-to-albumin ratio in head and neck cancers. A systematic search was conducted. Outcomes of interest included overall survival, disease-free survival, and distant metastasis–free survival. The hazard ratio with 95% confidence interval was pooled using a random-effects model. A total of 11 publications from the literature were included, allowing for the analysis of 7080 participants. Data pooling demonstrated that pretreatment C-reactive protein-to-albumin ratio had a hazard ratio of 1.88 (95% CI: 1.49−2.37, p < 0.001) for predicting overall survival, 1.91 (95% CI: 1.18−3.08, p = 0.002) for disease-free survival, and 1.46 (95% CI: 1.08−1.96, p = 0.001) for distant metastasis–free survival. Subgroup analysis showed that the C-reactive protein-to-albumin ratio is a significant prognostic marker for various head and neck cancers. An elevated pretreatment C-reactive protein-to-albumin ratio predicts a worse prognosis for patients with head and neck cancers. Therefore, the C-reactive protein-to-albumin ratio could serve as a potential prognostic biomarker facilitating treatment stratification.

Cardiomegaly is associated with poor clinical outcomes and is assessed by routine monitoring of the cardiothoracic ratio (CTR) from chest X-rays (CXRs). Judgment of the margins of the heart and lungs is subjective and may vary between different operators. Methods: Patients aged > 19 years in our hemodialysis unit from March 2021 to October 2021 were enrolled. The borders of the lungs and heart on CXRs were labeled by two nephrologists as the ground truth (nephrologist-defined mask). We implemented AlbuNet-34, a U-Net variant, to predict the heart and lung margins from CXR images and to automatically calculate the CTRs. Results: The coefficient of determination (R²) obtained using the neural network model was 0.96, compared with an R² of 0.90 obtained by nurse practitioners. The mean difference between the CTRs calculated by the nurse practitioners and senior nephrologists was 1.52 ± 1.46%, and that between the neural network model and the nephrologists was 0.83 ± 0.87% (p < 0.001). The mean CTR calculation duration was 85 s using the manual method and less than 2 s using the automated method (p < 0.001). Conclusions: Our study confirmed the validity of automated CTR calculations. By achieving high accuracy and saving time, our model can be implemented in clinical practice.

Muscle dysfunction, skeletal muscle fibrosis, and disability are associated with weakness in patients with end-stage renal disease. The main purpose of this study was to validate the effectiveness of a proposed system for gait monitoring on short-distance 1.5 m walkways in a dialysis center. Gaits with reduced speed and stride length, long sit-to-stand time (SST), two forward angles, and two unbalanced gait regions are defined in the proposed Kinect v3 gait measurement and analysis system (K3S) and have been considered clinical features in end-stage renal disease (ESRD) associated with poor dialysis outcomes. The stride and pace calibrations of the Kinect v3 system are based on the Zeno Walkway. Its single rating intraclass correlation (ICC) for the stride is 0.990, and its single rating ICC for the pace is 0.920. The SST calibration of Kinect v3 is based on a pressure insole; its single rating ICC for the SST is 0.871. A total of 75 patients on chronic dialysis underwent gait measurement and analysis during walking and weighing actions. After dialysis, patients demonstrated a smaller stride (p < 0.001) and longer SST (p < 0.001). The results demonstrate that patients’ physical fitness was greatly reduced after dialysis. This study ensures patients’ adequate physical gait strength to cope with the dialysis-associated physical exhaustion risk by tracing gait outliers. As decreased stride and pace are associated with an increased risk of falls, further studies are warranted to evaluate the clinical benefits of monitoring gait with the proposed reliable and valid system in order to reduce fall risk in hemodialysis patients.