Comparing perioperative outcomes between regional anesthesia and general anesthesia in patients undergoing hip fracture surgery: a systematic review and meta-analysis

PURPOSE

Nearly all patients with hip fractures undergo surgical treatment. The use of different anesthesia techniques during surgery may influence the clinical outcomes. The optimal anesthetic technique for patients undergoing hip fracture surgery is still controversial. We performed this updated systematic review and meta-analysis to compare clinical outcomes of patients undergoing hip fracture surgery with different anesthesia techniques.

SOURCE

Articles published from 2000 to May 2023 were included from MEDLINE, Embase, Web of Science, and the Cochrane Library. We included randomized controlled trials and observational studies comparing general anesthesia (GA) with regional anesthesia (RA) for the outcomes of 30-day mortality, 90-day mortality, in-hospital mortality, perioperative complications, length of hospital stay, and length of surgery in patients undergoing hip fracture surgery. Subgroup analyses were performed for the outcomes based on study design (randomized controlled trials or observational studies). We used a random-effects model for all analyses.

PRINCIPAL FINDINGS

In this meta-analysis, we included 12 randomized controlled trials. There was no difference in postoperative 30-day mortality between the two groups (odds ratio [OR], 0.88; 95% confidence interval [CI], 0.44 to 1.74; I2 = 0%). The incidence of intraoperative hypotension was lower in patients who received RA vs GA (OR, 0.52; 95% CI, 0.38 to 0.72; I2 = 0%). No significant differences were observed in 90-day mortality, in-hospital mortality, postoperative delirium, pneumonia, myocardial infarction, venous thromboembolism, length of surgery, and length of hospital stay.

CONCLUSION

In this updated systematic review and meta-analysis, RA did not reduce postoperative 30-day mortality in hip fracture surgery patients compared to GA. Fewer patients receiving RA had intraoperative hypotension than those receiving GA did. Apart from intraoperative hypotension, the data showed no differences in complications between the two anesthetic techniques.

STUDY REGISTRATION

PROSPERO (CRD42023411854); registered 7 April 2023.

Identification of potential diagnostic biomarkers for tenosynovial giant cell tumour by integrating microarray and single-cell RNA sequencing data

PURPOSE

Tenosynovial giant cell tumour (TGCT) is a benign hyperplastic and inflammatory disease of the joint synovium or tendon sheaths, which may be misdiagnosed due to its atypical symptoms and imaging features. We aimed to identify biomarkers with high sensitivity and specificity to aid in diagnosing TGCT.

METHODS

Two scRNA-seq datasets (GSE210750 and GSE152805) and two microarray datasets (GSE3698 and GSE175626) were downloaded from the Gene Expression Omnibus (GEO) database. By integrating the scRNA-seq datasets, we discovered that the osteoclasts are abundant in TGCT in contrast to the control. The single-sample gene set enrichment analysis (ssGSEA) further validated this discovery. Differentially expressed genes (DEGs) of the GSE3698 dataset were screened and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were conducted. Osteoclast-specific up-regulated genes (OCSURGs) were identified by intersecting the osteoclast marker genes in the scRNA-seq and the up-regulated DEGs in the microarray and by the least absolute shrinkage and selection operator (LASSO) regression algorithm. The expression levels of OCSURGs were validated by an external dataset GSE175626. Then, single gene GSEA, protein-protein interaction (PPI) network, and gene-drug network of OCSURGs were performed.

RESULT

22 seurat clusters were acquired and annotated into 10 cell types based on the scRNA-seq data. TGCT had a larger population of osteoclasts compared to the control. A total of 159 osteoclast marker genes and 104 DEGs (including 61 up-regulated genes and 43 down-regulated genes) were screened from the scRNA-seq analysis and the microarray analysis. Three OCSURGs (MMP9, SPP1, and TYROBP) were finally identified. The AUC of the ROC curve in the training and testing datasets suggested a favourable diagnostic capability. The PPI network results illustrated the protein-protein interaction of each OCSURG. Drugs that potentially target the OCSURGs were predicted by the DGIdb database.

CONCLUSION

MMP9, SPP1, and TYROBP were identified as osteoclast-specific up-regulated genes of the tenosynovial giant cell tumour via bioinformatic analysis, which had a reasonable diagnostic efficiency and served as potential drug targets.