With the aging population and the widespread implementation of lung cancer screening programs, an increasing number of elderly patients are undergoing curative lung resection. Due to diminished physiological reserve and complex comorbidities, this demographic exhibits a significantly higher incidence of severe perioperative complications (defined as Clavien-Dindo grade≥Ⅲ), which adversely affects both perioperative safety and long-term prognosis. In recent years, the research paradigm has shifted from univariate analysis toward multidimensional risk integration and the development of predictive models. This article systematically reviews the key risk factors for severe perioperative complications in elderly lung cancer patients, encompassing biological aging processes, frailty and sarcopenia, cardiopulmonary and renal functional reserves, inflammatory-immune and coagulation status, and perioperative interventions. Furthermore, it traces the evolution of risk assessment tools from traditional regression models to machine learning models that integrate multimodal data. The review also discusses common challenges in this field, including the standardization of outcome definitions, external validation, calibration assessment, and clinical translation. Future efforts should prioritize the deep integration of predictive tools with clinical decision support systems to establish a closed-loop care pathway from risk identification to stratified intervention, thereby effectively reducing complication rates and enhancing surgical outcomes for elderly lung cancer patients.

Objective:To develop a nucleic acid detection system for Helicobacter pylori ( H. pylori) based on recombinase-aided isothermal amplification (RAA) and clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated(Cas13a). Methods:Thirty strains of H. pylori, as well as two strains each of Escherichia coli, Staphylococcus aureus, Enterococcus faecalis, Enterobacter cloacae, and Klebsiella pneumoniae were collected from the Emergency General Hospital between 2021 and 2022. The specific primers and CRISPR RNA (crRNA) required for this newly established method were designed based on the conserved region of the ureC gene of H. pylori. Then, the primer pair that produced the least non-specific products was screened out using agarose gel electrophoresis, and the crRNA sequence with the highest cleavage efficiency was screened according to the fluorescence intensity produced by Cas13a cutting fluorescence probe. The RAA-Cas13a nucleic acid detection system was developed, and the limit of detection and the specificity of which were evaluated by detecting gradient dilutions of H. pylori ATCC 43504 genomic DNA and 5 different clinically common pathogens′ genomic DNA. The consistency with quantitative real-time PCR(qPCR) method was obtained by simultaneously detecting clinical strains using this method and established qPCR method. Two-tailed paired t-test was used to compare the fluorescence results between the two groups, and a P value less than 0.05 indicates a statistically significant difference. Results:The established RAA-Cas13a nucleic acid detection system could detect target DNA as low as 10 copies/μl. within 1 hour ( t=11.05, P<0.01), without cross-reaction with the other 5 clinically common strains. That method also showed good consistency compared to the qPCR method, the kappa coefficient=1. Conclusions:A method combining RAA with CRISPR-Cas13a for detecting H. pylori has been established, which can be used for rapid and sensitive identification of H. pylori infection.