Objective To investigate the species of sandflies and the prevalence of Leishmania infections in sandflies from selected areas of northern and northwestern China, so as to provide insights into identification of leishmaniasis vectors and assessment of epidemiological trends of leishmaniasis in China. Methods Sandfly samples were collected from Mentougou District of Beijing Municipality, Xiangning County in Linfen City of Shanxi Province, Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, and Payzawat County of Karamay District of Karamay City, Gaochang District of Turpan City in Xinjiang Uygur Autonomous Region from July 2023 to July 2024. Approximately 100 intact female sandfly samples were randomly selected from each site and the species of sandflies was identified according to morphological characteristics and molecular assays. Female sandflies originating from the same habitat were grouped into pools of 10 individuals. Leishmania infection was detected using polymerase chain reaction (PCR) assay targeting the internal transcribed spacer 1 (ITS-1) gene, and the prevalence of Leishmania infection was calculated in sandflies from different sampling sites using the minimum infection rate (MIR) method. In addition, positive amplicons were sequenced and subjected to phylogenetic analysis. Results A total of 6 155 sandflies were collected from different environments at sampling sites across the six aforementioned regions from July 2023 to July 2024. Phlebotomus chinensis (96.00%) was the dominant sandfly species in Mentougou District, Beijing Municipality, with a small proportion of Ph. sergenti (4.00%), and only Ph. chinensis was found in Xiangning County, Linfen City, Shanxi Province. Ph. wui was the only sandfly species detected in Ejin Banner, Alxa League, Inner Mongolia Autonomous Region, and Payzawat County, Kashgar City, Xinjiang Uygur Autonomous Region, and Ph. caucasicus (97.70%) was the dominant sandfly species in Karamay District, Karamay City, Xinjiang Uygur Autonomous Region, with a small proportion of Ph. wui (2.30%), while Ph. alexandri was the only species in Gaochang District, Turpan City, Xinjiang Uygur Autonomous Region. A total of 40, 60, 34, 18, 18, and 22 pools of sandfly samples were tested from Mentougou District in Beijing Municipality, Xiangning County in Linfen City of Shanxi Province, Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, Payzawat County in Kashgar City, Karamay District in Karamay City, and Gaochang District in Turpan City of Xinjiang Uygur Autonomous Region, respectively. L. infantum was detected in Ph. chinensis samples from Mentougou District in Beijing Municipality, and Xiangning County of Linfen City in Shanxi Province, with MIR of 0.25% to 1.00%, and L. donovani was detected in Ph. wui from Ejin Banner in Alxa League of Inner Mongolia Autonomous Region, and Payzawat County in Kashgar City of Xinjiang Uygur Autonomous Region, with MIR of 0.56% to 0.88%; however, no Leishmania infection was detected in Ph. caucasicus from Karamay District in Karamay City or Ph. alexandri from Gaochang District in Turpan City of Xinjiang Uygur Autonomous Region. Phylogenetic analysis showed that the Leishmania ITS-1 gene sequences obtained from Mentougou District in Beijing Municipality and Xiangning County in Linfen City of Shanxi Province were clustered into the same clade with the reference sequences of L. infantum ITS-1 gene, while the Leishmania ITS-1 gene sequences obtained from Ejin Banner in Alxa League of Inner Mongolia Autonomous Region and Payzawat County in Kashgar City of Xinjiang Uygur Autonomous Region were clustered into the same clade with the reference sequences of L. donovani ITS-1 gene. Conclusions There are variations in sandfly species in selected areas of northern and northwestern China, and variations in the species of Leishmania infecting sandflies. Improved surveillance of sandfly vectors and targeted control strategies with adaptations to geographical features and leishmaniasis vectors are recommended.

Objective To investigate the genetic diversity of sandfly populations in endemic areas of visceral leishmaniasis in China, so as to provide references insights into management of visceral leishmaniasis and the vector sandflies. MethodsSixteen sampling sites were selected from main endemic foci of visceral leishmaniasis in China from June to September 2024, including Shanxi Province, Shaanxi Province, Henan Province, Gansu Province, Sichuan Province, and Xinjiang Uygur Autonomous Region. Sandflies were captured using light traps and manual aspirators from sheep pens, chicken coops, cave dwellings, bovinesheds, and pig pens at each sampling site. A single sandfly sample was washed in phosphate-buffered saline (PBS), and genomic DNA was extracted from sandfly samples. Cytochrome oxidase subunit 1 (COI) gene was amplified using PCR assay with universal primers, and analyzed and retrieved with the nucleotide sequence analysis tool (BLAST) software, and the sequence of COI gene was aligned with the ClustalX 1.83 and MEGA 7.0 software. The base composition and variation site of the COI gene sequence were analyzed using the software MEGA 7.0, and the number of haplotypes, total number of segregating sites, haplotype diversity, nucleotide diversity, and average nucleotide differences were calculated in the COI gene sequence using the software DnaSP 5.10, followed by Tajima’s D test for neutrality. Haplotypes were screened using the software DnaSP 5.10, and the haplotype network map of sandfly samples was plotted using the software Network 5.0. MEGA 7.0 software was employed for gene sequence editing and alignment, and calculation of genetic distances among sandfly species sampled from different regions, and a phylogenetic tree was built with a neighbor-joining method. Results A total of 466 sandflies were captured from 16 sampling sites in China from June to September 2024, and 430 gene sequences were yielded following PCR amplification and sequencing of the COI gene, with 652 to 688 bp in the length of amplification fragments. The captured sandfly samples were characterized as Phlebotomus chinensis, Sergentomyia squamirostris, Se. koloshanensis, Ph. sichuanensis, and Ph. longiductus following the COI gene sequence alignment in BLAST. A total of 251 haplotypes were identified in the 430 gene sequences from sandfly samples (50.5%), and the average haplotype diversity, nucleotide diversity and average number of nucleotide difference were 0.885, 0.257 and 160.761, respectively. The Tajima’s D values were -0.92 for sandfly populations from Yangquan City, Shanxi Province and -1.73 for sandfly populations from Sanmenxia City, Henan Province, and were all more than 0 for sandfly populations from other sampling sites. Haplotype analysis identified 50 haplotypes, which were classified into two haplogroups. Heplogroup 1 included 29 haplotypes, which had a high homology, and heplogroup 2 included 21 haplotypes. The average genetic distance was 0.000 to 0.604 among sandfly samples from different sampling sites, and phylogenetic analysis revealed that the five sandfly species were clustered into distinct clades, all with 100% clade confidence. Conclusions There is a high genetic polymorphism in the COI gene from five sandfly populations in main endemic foci of visceral leishmaniasis in China, and COI gene may serve as a marker gene for analysis of the genetic structure of sandfly populations.

Background and Aims:Laparoscopic transcystic bile duct exploration(LTCBDE)has become the preferred method for treating secondary bile duct stones due to its advantages of minimal trauma,fast recovery,and low complication rates.However,challenges remain in the dilation of the cystic duct,the insertion of the choledochoscope,and the exploration of the common hepatic duct and intrahepatic bile ducts.This study was performed to explore the clinical application and effectiveness of the programmed modified LTCBDE in the treatment of gallbladder stones combined with common bile duct stones.Methods:A retrospective analysis was conducted on the clinical data of 248 patients who underwent programmed modified LTCBDE at the Affiliated Suzhou Ninth Hospital of Soochow University from January 2018 to January 2024.The surgical strategies and treatment outcomes were summarized.Data from 913 patients who underwent laparoscopic common bile duct exploration(LCBDE)during the same period were also collected to compare surgical outcomes and postoperative complications between the two groups.Results:Through programmed surgical steps,the innovative"diaphragm"incision technique,and improved bile duct probe application,244 patients(98.4%)successfully underwent LTCBDE,while 4 patients were converted to LCBDE due to failure to insert a 4.9 mm choledochoscope through the cystic duct.After operation,1 patient(0.4%)had residual bile duct stones,which were successfully removed through T-tube tract stone extraction(this patient was converted to LCBDE during the procedure).Additionally,1 case of bile leakage and 1 case of abdominal infection(each 0.4%)occurred,both of which resolved with conservative treatment.No cases of intra-abdominal bleeding,bile duct stenosis,or bile duct injury were reported.The average operative time in the programmed modified LTCBDE group was comparable to that of the LCBDE group(85.2 min vs.88.0 min,P=0.398),but the postoperative hospital stay was significantly shorter(6.2 d vs.8.3 d,P<0.001),and the incidence of complications was lower(1.6%vs.4.7%,P=0.044).Conclusion:The programmed modified LTCBDE is a standardized,safe,and effective procedure with a low complication rate.It is worthy of further clinical promotion and application.

OBJECTIVE: To explore the risk factors affecting the prognosis of patients with sepsis complicated with acute pulmonary embolism, and to construct and validate a nomogram predictive model for in-hospital mortality risk. METHODS: Based on the American Medical Information Mart for Intensive Care (MIMIC-III, MIMIC-IV) databases, the data were collected on patients with sepsis complicated with acute pulmonary embolism from 2001 to 2019, including baseline characteristics, and vital signs, disease scores, laboratory tests within 24 hours of admission to the intensive care unit (ICU), and interventions. In-hospital mortality was the outcome event. The total samples were divided into training and testing sets in a 7:3 ratio by random sampling. Univariate Cox regression analysis was used to verify the impact of all variables on the risk of in-hospital mortality, thereby screen potential influencing factors. Subsequently, a stepwise bi-directional regression method was applied to select factors one by one, leading to the construction of a nomogram prediction model. Collinearity testing was used to demonstrate the absence of strong multicollinearity among the influencing factors in the nomogram prediction model. The discrimination of the nomogram model, sequential organ failure assessment (SOFA), and simplified pulmonary embolism severity index (sPESI) was evaluated using C-index in the test set. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of various models for in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. RESULTS: A total of 562 patients with sepsis complicated with acute pulmonary embolism were included, including 393 in the training set and 169 in the testing set. Univariate Cox regression analysis showed that 30 factors associated with in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. Through stepwise bi-directional regression, 12 variables were ultimately selected, including gender, presence of malignant tumors, body temperature, red cell distribution width (RDW), blood urea nitrogen (BUN), serum potassium, prothrombin time (PT), 24-hour urine output, mechanical ventilation, vasoactive drugs, warfarin use, and sepsis-induced coagulopathy (SIC). Collinearity testing indicated no strong multicollinearity among the influencing factors [all variance inflation factor (VIF) > 10]. A nomogram model was constructed using the 12 variables mentioned above. The nomogram model predicted the C-index and its 95% confidence interval (95%CI) of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism better than SOFA score and sPESI [0.771 (0.725-0.816) vs. 0.579 (0.519-0.639), 0.608 (0.554-0.663)]. The ROC curve showed that the area under the curve (AUC) and its 95%CI of the nomogram model were higher than those of the SOFA score and sPESI [0.811 (0.766-0.857) vs. 0.630 (0.568-0.691), 0.623 (0.566-0.680)]. These findings were consistently replicated in the internal validation of the testing set. In both the training and testing sets, Delong's test showed that the AUC of the nomogram model was significantly higher than the SOFA score and sPESI (both P < 0.05). CONCLUSION The nomogram model demonstrated good predictive effectiveness for the risk of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism, enabling clinicians to predict mortality risk in advance and take timely interventions to reduce mortality.
Humans ; Pulmonary Embolism/mortality* ; Hospital Mortality ; Nomograms ; Sepsis/complications* ; Prognosis ; Risk Factors ; Intensive Care Units ; Male ; Female ; Middle Aged ; Aged

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

Objective:To explore the association between albumin-corrected serum calcium (ACSC) levels and 30-day all-cause mortality in patients hospitalized for community-acquired bacterial pneumonia (CABP).Methods:A secondary analysis was conducted on 1 899 patients with CABP from a Norwegian cohort study. The relationship between baseline ACSC levels and 30-day mortality was assessed using multivariable logistic regression models, adjusted for potential confounders.Results:A significant positive correlation was found between ACSC levels and 30-day mortality risk after adjusting for confounding variables ( OR=1.95, 95% CI=1.48-2.58). When ACSC levels were categorized into tertiles (T1-T3), a trend analysis revealed that the T2 and T3 groups had significantly higher mortality risks compared to the lowest tertile (T1), with odds ratios ( OR) and 95% confidence intervals ( CI) of 1.52(95% CI: 0.97-2.38) and 2.21 (95% CI: 1.44-3.39), respectively ( P for trend <0.001). Subgroup analyses demonstrated no significant interactions across predefined subgroups (all P for interaction > 0.05). Conclusions:In patients with CABP and admission ACSC levels of ≥8.6 mg/dL, higher ACSC levels were positively associated with an increased risk of 30-day mortality. These findings highlight the potential prognostic value of ACSC levels in CABP patients.

Background and Aims:Laparoscopic transcystic bile duct exploration(LTCBDE)has become the preferred method for treating secondary bile duct stones due to its advantages of minimal trauma,fast recovery,and low complication rates.However,challenges remain in the dilation of the cystic duct,the insertion of the choledochoscope,and the exploration of the common hepatic duct and intrahepatic bile ducts.This study was performed to explore the clinical application and effectiveness of the programmed modified LTCBDE in the treatment of gallbladder stones combined with common bile duct stones.Methods:A retrospective analysis was conducted on the clinical data of 248 patients who underwent programmed modified LTCBDE at the Affiliated Suzhou Ninth Hospital of Soochow University from January 2018 to January 2024.The surgical strategies and treatment outcomes were summarized.Data from 913 patients who underwent laparoscopic common bile duct exploration(LCBDE)during the same period were also collected to compare surgical outcomes and postoperative complications between the two groups.Results:Through programmed surgical steps,the innovative"diaphragm"incision technique,and improved bile duct probe application,244 patients(98.4%)successfully underwent LTCBDE,while 4 patients were converted to LCBDE due to failure to insert a 4.9 mm choledochoscope through the cystic duct.After operation,1 patient(0.4%)had residual bile duct stones,which were successfully removed through T-tube tract stone extraction(this patient was converted to LCBDE during the procedure).Additionally,1 case of bile leakage and 1 case of abdominal infection(each 0.4%)occurred,both of which resolved with conservative treatment.No cases of intra-abdominal bleeding,bile duct stenosis,or bile duct injury were reported.The average operative time in the programmed modified LTCBDE group was comparable to that of the LCBDE group(85.2 min vs.88.0 min,P=0.398),but the postoperative hospital stay was significantly shorter(6.2 d vs.8.3 d,P<0.001),and the incidence of complications was lower(1.6%vs.4.7%,P=0.044).Conclusion:The programmed modified LTCBDE is a standardized,safe,and effective procedure with a low complication rate.It is worthy of further clinical promotion and application.

Objective To analyze and evaluate the implementation effect of tuberculosis prevention and control program in Wuhan, and to provide reference for scientific formulation of tuberculosis prevention and control measures. Methods Using the National Tuberculosis Information Management System, descriptive statistical analysis was carried out on the medical record information of pulmonary tuberculosis patients registered in Wuhan , 2016 - 2021. Results A total of 34 937 cases of pulmonary tuberculosis were registered in Wuhan , with an average annual incidence rate of 49.85/100 000. The incidence rate showed a downward trend year by year, with a statistically significant difference in 2016—2021 (χ²_trend = 708.387, P<0.001). The patients mainly came from referrals, accounting for 71.86%, and the proportion of referrals varied significantly among different years (χ²=355.541, P<0.001). The diagnosis type was mainly pathogenic negative, accounting for 49.12%. The proportion of pathogenic negative had statistically significant difference among different years (χ²=1 354.830, P<0.001). The proportion of patients cured and completed the course of treatment reached 93.98%, with statistically significant differences in the proportions among different years (cured, χ²=1 080.252, P<0.001; completed the treatment course, χ²= 933.655, P<0.001). The sputum examination rate of newly diagnosed patients in each year reached over 90%, and the overall completion rate reached over 95%. The proportion of positive pathogens showed an increasing trend year by year. Conclusion The overall epidemic situation of tuberculosis in Wuhan is declining year by year, and tuberculosis prevention and control work has achieved remarkable results. Active screening in key areas and populations should be strengthened, and prevention and control strategies should be formulated by emphasizing the key and difficult points.

Objective:To develop and evaluate a nomogram prediction model for the 3-month mortality risk of patients with sepsis-associated acute kidney injury (S-AKI).Methods:Based on the American Medical Information Mart for Intensive Care-Ⅳ (MIMIC-Ⅳ), clinical data of S-AKI patients from 2008 to 2021 were collected.Initially, 58 relevant predictive factors were included, with all-cause mortality within 3 months as the outcome event. The data were divided into training and testing sets at a 7∶3 ratio. In the training set, univariate Logistic regression analysis was used for preliminary variable screening. Multicollinearity analysis, Lasso regression, and random forest algorithm were employed for variable selection, combined with the clinical application value of variables, to establish a multivariable Logistic regression model, visualized using a nomogram. In the testing set, the predictive value of the model was evaluated through internal validation. The receiver operator characteristic curve (ROC curve) was drawn, and the area under the curve (AUC) was calculated to evaluate the discrimination of nomogram model and Oxford acute severity of illness score (OASIS), sequential organ failure assessment (SOFA), and systemic inflammatory response syndrome score (SIRS). The calibration curve was used to evaluate the calibration, and decision curve analysis (DCA) was performed to assess the net benefit at different probability thresholds.Results:Based on the survival status at 3 months after diagnosis, patients were divided into 7?768 (68.54%) survivors and 3?566 (31.46%) death. In the training set, after multiple screenings, 7 variables were finally included in the nomogram model: Logistic organ dysfunction system (LODS), Charlson comorbidity index, urine output, international normalized ratio (INR), respiratory support mode, blood urea nitrogen, and age. Internal validation in the testing set showed that the AUC of nomogram model was 0.81 [95% confidence interval (95% CI) was 0.80-0.82], higher than the OASIS score's 0.70 (95% CI was 0.69-0.71) and significantly higher than the SOFA score's 0.57 (95% CI was 0.56-0.58) and SIRS score's 0.56 (95% CI was 0.55-0.57), indicating good discrimination. The calibration curve demonstrated that the nomogram model's calibration was better than the OASIS, SOFA, and SIRS scores. The DCA curve suggested that the nomogram model's clinical net benefit was better than the OASIS, SOFA, and SIRS scores at different probability thresholds. Conclusions:A nomogram prediction model for the 3-month mortality risk of S-AKI patients, based on clinical big data from MIMIC-Ⅳ and including seven variables, demonstrates good discriminative ability and calibration, providing an effective new tool for assessing the prognosis of S-AKI patients.

Objective To investigate the value of derived neutrophil to lymphocyte ratio(dNLR)as a pre-dictive biomarker for immunotherapy response in advanced non-small cell lung cancer(NSCLC).Methods A total of 92 patients with advanced NSCLC who received anti-programmed cell death receptor(PD-1)combined therapy in the hospital from August 2018 to December 2019 were selected as the research objects.Peripheral blood samples were collected within 24 h before immunotherapy,complete blood cell count was measured,and dNLR was calculated.Patients with advanced NSCLC were treated with PD-1 inhibitors or combination regi-mens,and the response to immunotherapy was evaluated by objective response rate(ORR)and disease control rate(DCR).The receiver operating characteristic(ROC)curve was used to analyze the predictive value of dN-LR for the diagnosis and response to immunotherapy in advanced NSCLC.Multivariate Logistic regression model was used to analyze the relationship between dNLR and immunotherapy response in advanced NSCLC.Kaplan-Meier survival curve and Log-Rank test were used to analyze the overall survival(OS),progression-free survival(PFS)and disease-specific survival(DSS)of the low dNLR group and the high dNLR group.Re-sults The ORR and DCR of advanced NSCLC patients after immunotherapy were 32.61％and 65.22％,re-spectively,and the PFS and OS were 17.0(8.5,25.5)and 24.0(12.7,36.1)months,respectively.The dNLR of DCR group was lower than that of non-DCR group(P＜0.001).The dNLR of ORR group was lower than that of non-ORR group(P＜0.001).The area under the curve of dNLR for predicting DCR or ORR was 0.897(95％CI 0.829-0.965)and 0.874(95％CI 0.795-0.953),respectively.Multivariate Logistic regres-sion analysis showed that dNLR≥2.28 increased the risk of non-response to immunotherapy,and this inde-pendent relationship still existed after further adjustment for objective confounding factors(P＜0.05).Sur-vival curve results showed that patients with high dNLR had significantly shorter PFS,OS,and DSS(P＜0.05).Multivariate Cox regression analysis showed that high dNLR was an independent factor affecting the poor prognosis of patients with advanced NSCLC(P＜0.05).Conclusion High dNLR advanced NSCLC pa-tients are more difficult to benefit from immune therapy,and prognosis is worse.dNLR is promising as a pre-dictive biomarker for immunotherapy response in advanced NSCLC.