Clinical Value of the Prognostic Nutrition Index in the Assessment of Prognosis in Critically Ill Patients with Stroke: A Retrospective Analysis

Purpose

The purpose of study was to evaluate the association between prognostic nutritional index (PNI) and all-cause mortality of critically ill patients with stroke.

Methods

Clinical data derived from Multiparameter Intelligent Monitoring in Intensive Care were analyzed. The primary endpoint was 30-day all-cause mortality; secondary endpoints were 90-day mortality and one-year cause mortality. The potential prognostic roles of PNI were analyzed by Cox proportional hazard models. The independent prognostic roles of PNI in the cases were analyzed by smooth curve fitting.

Results

Concerning 30-day mortality, the HR (95% CI) for a high PNI (≥39.7) was 0.700 (0.544, 0.900; P = 0.00539), compared to a low PNI (<39.7). After adjusting for multiple confounders, the HR (95% CI) for a high PNI (≥39.7) was 0.732 (0.547, 0.978; P = 0.03514), compared to a low PNI (<39.7). Regarding 90-day and one-year mortality, a similar trend was observed. In addition, a nonlinear association between PNI and 30-day mortality was found. Using recursive algorithm and two-piecewise linear regression model, inflection point (IP) was calculated, which was 49.4. On the right side of the IP, there was a positive relationship between PNI and 30-day mortality, and the effect size, 95% CI, and P value were 1.04 (1.01, 1.07), P = 0.0429, respectively. On the left of the IP, the effect size, 95% CI, and P value were 0.97 (0.96, 0.99) and 0.0011, respectively.

Conclusions

The PNI was an independent predicting factor of 30-day, 90-day, and 1-year mortality of the critically ill patients with stroke. In addition, there was a U-shaped relationship between PNI and all-cause mortality of stroke patients. PNI was a risk factor for the outcome of stroke when PNI was >49.4, while PNI was a protective factor for outcome of stroke when PNI was <49.4.

Single-Cell Sequencing Analysis Based on Public Databases for Constructing a Metastasis-Related Prognostic Model for Gastric Cancer

Background

Although incidences of gastric cancer have decreased in recent years, the disease remains a significant danger to human health. Lack of early symptoms often leads to delayed diagnosis of gastric cancer, so that many patients miss the opportunity for surgery. Treatment for advanced gastric cancer is often limited. Immunotherapy, targeted therapy, and the mRNA vaccine have all emerged as potentially viable treatments for advanced gastric cancer. However, our understanding of the immune microenvironment of gastric cancer is far from sufficient; now is the time to explore this microenvironment.

Methods

In our study, using TCGA dataset and the GEO dataset GSE62254, we performed in-depth transcriptome and single-cell sequencing analyses based on public databases. We analyzed differential gene expressions of immune cells in metastatic and nonmetastatic gastric cancer and constructed a prognostic model of gastric cancer patients based on these differential gene expressions. We also screened candidate vaccine genes for gastric cancer.

Results

This prognostic model can accurately predict the prognosis of gastric cancer patients by dividing them into high-risk and low-risk groups. In addition to this, we identified a candidate vaccine gene for gastric cancer: PTPN6.

Conclusions

Our study could provide new ideas for the treatment of gastric cancer.

Utility of Circulating Cell-Free DNA in Assessing Microsatellite Instability and Loss of Heterozygosity in Breast Cancer Using Human Identification Approach

The diagnostic and prognostic utility of circulating cell-free DNA (cfDNA) in breast cancer (BC) patients was recently reported. Here, we investigated the use of cfDNA to examine microsatellite instability (MSI) and loss of heterozygosity (LOH) for early BC diagnosis. cfDNA and genomic DNA from 41 female BC patients and 40 healthy controls were quantified using NanoDrop spectrophotometry and real-time PCR. The stability of genomic and cfDNA was assessed using a high-resolution AmpFlSTR MiniFiler human identification kit. Significant increases in cfDNA plasma concentrations were observed in BC patients compared to controls. The genotype distribution of the eight autosomal short tandem repeat (STR) loci D7S820, D13S317, D21S11, D2S1338, D18S51, D16S539, FGA, and CSF1PO were in Hardy–Weinberg equilibrium. Significant differences in the allele frequencies of D7S820 allele-8, D21S11 allele-29, allele-30.2, allele-32.2, and CSF1PO allele-11 were seen between BC patients and controls. LOH and MSI were detected in 36.6% of the cfDNA of patients compared to genomic DNA. This study highlights the utility of plasma-derived cfDNA for earlier, less invasive, and cost-effective cancer diagnosis and molecular stratification. It also highlights the potential value of cfDNA in molecular profiling and biomarkers discovery in precision and forensic medicine.