Objective To develop a nomogram diagnostic model to differentiate peripheral small cell lung cancer(PSCLC)from peripheral lung adenocarcinoma(PADC)using clinical and multi spiral computed tomography features.Methods A retrospective analysis was conducted on the CT characteristics and clinical presentations of 50 PSCLC and 100 PADC.Univariate and multivariate logistic regression analyses were employed to identify significant features.A nomogram was constructed to quantify the influencing factors.The efficacy and clinical applicability of the model were assessed using the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results Smoking,neuron-specific enolase(NSE),smooth margin,spindle/branching shape,and lymphadenopathy were independent risk factors for PSCLC(P＜0.05),whereas rough margin and lobulation sign were independent risk factors for PADC(P＜0.05).The nomogram model demonstrated high diagnostic efficacy,and the calibration curve exhibited a good degree of calibration(Brier=0.079).The DCA indicated that the nomogram model possesses substantial clinical utility.Conclusion The nomogram model developed based on six indicators,including smoking,NSE≥17 ng/mL,margin characteristics,spindle/branching shape,lobulation sign,and lymphadenopathy can well distinguish PSCLC from PADC.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective:To investigate the expression of erythropoietin-producing hepatocyte kinase receptor A10 (EphA10) in gastric cancer and adjacent tissues, and analyze its correlation with clinical features and prognosis.Methods:The clinical data of 112 patients with gastric cancer from January 2018 to December 2023 in Eastern Theater Command Air Force Hospital were retrospectively analyzed. The expression of EphA10 in gastric cancer and adjacent tissues was detected by EnVision immunohistochemical staining. The relationship between EphA10 expression and clinicopathological features was analyzed. The Kaplan-Meier survival curve was drawn, and the comparison used the log-rank test. Multivariate Cox regression was used to analyze the independent risk factors of the overall survival time in patients with gastric cancer.Results:The positive expression rate of EphA10 in gastric cancer tissues was significantly higher than that in adjacent tissues: 44.6% (50/112) vs. 0, and there was statistical difference ( χ2 = 64.37, P<0.01). In patients with gastric cancer, the positive expression of EphA10 in gastric cancer tissues was correlated with tumor long diameter, differentiation, TNM stage and lymph node metastasis ( P<0.01 or <0.05), but without age, gender and distant metastasis ( P>0.05). Kaplan-Meier survival curve analysis result showed that the median overall survival time in patients with positive EphA10 expression was significantly lower than that in patients with negative EphA10 expression: 18 months vs. 48 months, and there was statistical difference (log-rank χ2 = 53.66, P<0.01). Multivariate Cox regression analysis result showed that tumor long diameter ≥3 cm, TNM stage Ⅲ to Ⅳ, lymph node metastasis and EphA10 positive expression were the independent risk factors of the overall survival time in patients with gastric cancer ( HR = 1.250, 1.515, 1.321 and 0.831; 95% CI 1.143 to 1.368, 1.267 to 1.813, 1.168 to 1.497 and 0.756 to 0.913; P<0.01 or <0.05). Conclusions:The expression level of EphA10 in gastric cancer tissues is up-regulated, and its expression level is correlated with the clinicopathological features. EphA10 can be used as one of the reference indicators for clinical prognosis evaluation in patients with gastric cancer.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

INTRODUCTION: Obstructive sleep apnoea (OSA) is common in Singapore, with moderate to severe OSA affecting around 30% of residents. These consensus statements aim to provide scientifically grounded recommendations for the management of OSA, standar-dise the management of OSA in Singapore and promote multidisciplinary collaboration. METHOD: An expert panel, which was convened in 2024, identified several areas of OSA management that require guidance. The expert panel reviewed the current literature and developed consensus statements, which were later independently voted on using a 3-point Likert scale (agree, neutral or disagree). Consensus (total ratings of agree and neutral) was set a priori at ≥80% agreement. Any statement not reaching consensus was excluded. RESULTS: The final consensus included 49 statements that provide guidance on the screening, diagnosis and management of adults with OSA. Additionally, 23 statements on the screening, diagnosis and management of paediatric OSA achieved consensus. These 72 consensus statements considered not only the latest clinical evidence but also the benefits and harms, resource implications, feasibility, acceptability and equity impact of the recommendations. CONCLUSION The statements presented in this paper aim to guide clinicians based on the most updated evidence and collective expert opinion from sleep specialists in Singapore. These recommendations should augment clinical judgement rather than replace it. Management decisions should be individualised, taking into account the patient's clinical characteristics, as well as patient and caregiver concerns and preferences.
Humans ; Sleep Apnea, Obstructive/diagnosis* ; Singapore ; Consensus ; Adult

Objective:To evaluate the clinical value of peripheral blood monocyte subset analysis in the diagnosis and treatment of chronic myelomonocytic leukemia (CMML) .Method:We retrospectively enrolled 51 patients newly diagnosed with CMML at Guangdong Provincial People's Hospital between June 1, 2020, and December 31, 2024, according to the WHO 2022 diagnostic criteria. Twenty-three patients with other myeloid neoplasms (excluding CMML) and peripheral monocytosis (absolute count ≥0.5×10 9/L and percentage ≥10%) were included as the control group. All patients underwent bone marrow aspiration for examinations including bone marrow smears, biopsies, cytogenetics, and gene mutation analysis to establish a definitive diagnosis. Concurrently, flow cytometry was used to determine the proportions of peripheral blood monocyte subsets: classical (MO1, CD14 +CD16 -) , intermediate (MO2, CD14 +CD16 +) , and non-classical (MO3, CD14 lowCD16 +) . Differences between the groups were compared, and diagnostic efficacy was evaluated using receiver operating characteristic (ROC) curves. Result:Among the 51 CMML patients, the proportion of the peripheral blood MO1 subset was significantly higher than that in patients with other myeloid neoplasms ( P=0.027) , whereas there were no significant differences in the MO2 and MO3 subsets (all P>0.05) . Further analysis revealed that 43 (84.31%) of the CMML patients met the WHO diagnostic threshold for the MO1 subset (≥94%) , while the remaining 8 patients did not; 46 patients (90.20%) had MO3 subset proportions below the threshold proposed by Hudson (≤1.13%) , while the remaining 5 patients were above this threshold. In-depth analysis showed that among the 8 patients who did not meet the WHO criteria, 7 were experiencing inflammation. Similarly, all 5 patients who did not meet the Hudson criteria were in an inflammatory state. Subsequent ROC curve analysis of this cohort identified a cut-off value for the MO1 subset of 97.55% [Area Under the Curve (AUC) =0.661, P=0.027], which aligns with the WHO criteria. Conclusion:Peripheral blood monocyte subset analysis, particularly MO1 subset analysis, can effectively assist in CMML diagnosis, but exclusion of inflammatory conditions is required.

Objective:To evaluate the clinical value of peripheral blood monocyte subset analysis in the diagnosis and treatment of chronic myelomonocytic leukemia (CMML) .Method:We retrospectively enrolled 51 patients newly diagnosed with CMML at Guangdong Provincial People's Hospital between June 1, 2020, and December 31, 2024, according to the WHO 2022 diagnostic criteria. Twenty-three patients with other myeloid neoplasms (excluding CMML) and peripheral monocytosis (absolute count ≥0.5×10 9/L and percentage ≥10%) were included as the control group. All patients underwent bone marrow aspiration for examinations including bone marrow smears, biopsies, cytogenetics, and gene mutation analysis to establish a definitive diagnosis. Concurrently, flow cytometry was used to determine the proportions of peripheral blood monocyte subsets: classical (MO1, CD14 +CD16 -) , intermediate (MO2, CD14 +CD16 +) , and non-classical (MO3, CD14 lowCD16 +) . Differences between the groups were compared, and diagnostic efficacy was evaluated using receiver operating characteristic (ROC) curves. Result:Among the 51 CMML patients, the proportion of the peripheral blood MO1 subset was significantly higher than that in patients with other myeloid neoplasms ( P=0.027) , whereas there were no significant differences in the MO2 and MO3 subsets (all P>0.05) . Further analysis revealed that 43 (84.31%) of the CMML patients met the WHO diagnostic threshold for the MO1 subset (≥94%) , while the remaining 8 patients did not; 46 patients (90.20%) had MO3 subset proportions below the threshold proposed by Hudson (≤1.13%) , while the remaining 5 patients were above this threshold. In-depth analysis showed that among the 8 patients who did not meet the WHO criteria, 7 were experiencing inflammation. Similarly, all 5 patients who did not meet the Hudson criteria were in an inflammatory state. Subsequent ROC curve analysis of this cohort identified a cut-off value for the MO1 subset of 97.55% [Area Under the Curve (AUC) =0.661, P=0.027], which aligns with the WHO criteria. Conclusion:Peripheral blood monocyte subset analysis, particularly MO1 subset analysis, can effectively assist in CMML diagnosis, but exclusion of inflammatory conditions is required.