Objective·To explore the diagnostic and treatment methods for patients with cystic fibrosis(CF)complicated by allergic bronchopulmonary aspergillosis(ABPA),and to enhance clinicians'understanding of these two diseases.Methods·A retrospectively analysis was conducted on the clinical data of 5 patients with CF complicated by ABPA admitted to the Department of Respiratory Medicine,Shanghai Children's Hospital,Shanghai Jiao Tong University School of Medicine,from July 2023 to August 2024.A literature search was performed in PubMed,Web of Science,Cochrane Library,and CNKI for studies published in the past 10 years regarding the co-existence of these diseases.Clinical manifestations,treatment courses,and current epidemiological research were summarized and analyzed.Results·Common symptoms of patients with CF complicated by ABPA included aggravated cough and expectoration,wheezing,fever,and dyspnea.Whole-exome aequencing indicated mutations in the cystic fibrosis transmembrane conductance regulator(CFTR)gene,and an increase in the concentration of chloride ions in sweat.The levels of total serum immunoglobulin E(IgE)and Aspergillus fumigatus-specific IgE increased,and chest computed tomography(CT)showed bronchiectasis and mucus plugging.CF complicated by ABPA is often missed or misdiagnosed for asthma.In China,ABPA is often diagnosed before CF,whereas in Caucasian populations CF is typically diagnosed first.Initial treatment usually involves long-term oral administration of antifungal drugs such as voriconazole combined with glucocorticoids such as prednisone.For patients with frequent relapses or severe side effects,alternative antifungal agents or omalizumab therapy may be considered.Co-infection with Pseudomonas aeruginosa is common,often requiring intravenous antibiotics such as cefoperazone-sulbactam.Current epidemiological research focuses mainly on clinical characteristics,treatment regimens,and novel diagnostic methods.Conclusion·ABPA and CF have overlapping symptoms.Accurate diagnosis of CF complicated by ABPA requires genetic testing,sweat chloride measurement,chest CT,and serological tests.The coexistence of these diseases often leads to missed,delayed,or incorrect diagnosis,increasing patient burden.Present epidemiological studies mainly address clinical characteristics with a lack of targeted clinical drug trials for this patient population.

Objective:To establish an arsenic free fully automatic online digestion iodine analyzer detection method for urinary iodine (hereinafter referred to as the method).Methods:Based on the principle of iodine catalyzed antimony cerium redox reaction, a fully automatic online digestion iodine analyzer was used to determine the iodine content in urine. The effectiveness of the method in terms of detection limit, precision, accuracy (determination of urinary iodine primary standard reference materials GBW09108z and GBW09110f and spiked recovery experiment), and interference experiments was validated. The method was compared with the arsenic cerium catalytic spectrophotometry method recommended by the National Reference Laboratory for Iodine Deficiency Disorders.Results:The linear range of the method was 0 - 300 μg/L, with a correlation coefficient │ r│> 0.999 5. The qualitative and quantitative detection limits were 7.41 and 18.01 μg/L, respectively. The relative standard deviation ( RSD) of urine samples with different iodine concentrations ranged from 1.0% to 1.7%. The results of the determination of iodine concentrations in urine using standard substances GBW09108z and GBW09110f were within the given standard range, with RSD < 2.5%. The range of spiked recovery rates for urine samples with different iodine concentrations was 101.3% to 104.8%, with an overall average spiked recovery rate of 103.0%. The average concentration of the baseline iodine standard solution was determined to be 116.21 μg/L, and the relative error of the concentration determination with the addition of interfering substances was less than 5.0%. The comparison results showed that there was no statistically significant difference in the measurement results between the two methods ( t = - 0.06, P = 0.952). Conclusions:The method adopts automated detection, which is simple to operate, labor-saving, and does not require the use of arsenic trioxide. It has high precision and accuracy, and is suitable for detection of large quantities of samples.

Objective To construct and verify a risk prediction model of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer,and to screen the optimal model by using machine learning algorithm,so as to provide references for clinical formulation of a nursing risk management plan.Methods The convenience sampling method was used to retrospectively select 476 patients who underwent thoracoscopic radical resection of lung cancer in a tertiary hospital in Hangzhou,Zhejiang Province from January to December 2023 as a construction group.Logistic regression,decision tree,random forest and naive Bayesian model were constructed by SPSS 29.0 and R 4.3.0 software.The prediction performance of each model was compared by accuracy,precision,recall,F1 score and area under the receiver operating characteristic curve,and the optimal model was screened.From January to June 2024,204 patients in the unit were prospectively selected as the research subjects of an external validation group.The discrimination and calibration of the optimal model were evaluated by AUC value and calibration curve.Results A total of 680 patients completed the survey.All 4 models showed that multimodal analgesia,thoracic drainage tube type,pain score,tracheal intubation type,state anxiety and catheter indwelling time were the influencing factors of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer(P＜0.05).The 4 risk prediction models showed that the random forest prediction model had the best comprehensive performance.The external verification results showed that the AUC value was 0.913,and the calibration curve fitted well with the 45° ideal line.Conclusion Among the 4 risk prediction models,the random forest prediction model has the best performance,which is more suitable for the assessment of the risk of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer,and has good generalization and clinical application value.

This article reports a rare case of pantothenate kinase-associated neurodegeneration: the patient′s initial symptoms were Parkinson-like symptoms such as tremor and bradykinesia, as well as dysarthria. Brain magnetic resonance imaging showed abnormal signals in the bilateral basal ganglia region similar to the tiger′s eye sign. Two heterozygous mutations including c.803A>G(p.Asp268Gly) and c.1021C>T(p.Arg341 *) were found in the pantothenate kinase 2 gene by whole exome sequencing, and the final diagnosis was neurodegeneration with brain iron accumulation type 1, also known as pantothenate kinase-associated neurodegeneration. By reviewing the clinical characteristics, diagnostic approaches and therapeutic strategies, this article aims to enhance the recognition of this disease, avoid misdiagnosis and missed diagnosis, and provide guidance for clinical diagnosis and treatment.

Objective To explore the diagnostic performance of prostate imaging reporting and data system(PI-RADS)V2.1 score combined with prostate specific antigen(PSA)-related parameters in transition zone prostate cancer(PCa)in patients with PSA levels of 4-20 ng/mL.Methods The clinical data of 129 patients who underwent prostate biopsy were retrospectively analyzed,including age,total prostate specific antigen(tPSA),free prostate specific antigen(fPSA),f/t PSA,prostate volume(PV),and prostate specific antigen density(PSAD).Among 129 patients,52 were diagnosed with transition zone PCa and 77 with benign prostate hyperplasia.The MRI images of all patients were scored according to the PI-RADS V2.1 criteria.The clinical and imaging parameters between transition zone PCa and benign prostate hyperplasia were compared using univariate logistic regression analysis.Independent predic-tors were identified via multivariate logistic regression,and a combined predictive model was constructed.Diagnostic performance of the model was evaluated using the receiver operating characteristic(ROC)curves.Results Univariate logistic regression analysis showed that the transition zone PCa exhibited significantly higher PI-RADS V2.1 score,tPSA,and PSAD than the benign prostate hyperplasia(P＜0.05).Multivariate logistic regression analysis identified PI-RADS V2.1 score and PSAD were independent predictors for predicting transition zone PCa(P＜0.05).Optimal diagnostic thresholds were PI-RADS V2.1 score＞3 points and PSAD＞0.23 ng/mL2.The combined prediction model achieved an area under the curve(AUC)of 0.863,outperforming PI-RADS V2.1 score(AUC=0.821)and PSAD(AUC=0.779)alone(P＜0.05).Conclusion The combination of PI-RADS V2.1 score and PSAD has a high predictive value for transition zone PCa in patients with PSA levels of 4-20 ng/mL.Thresholds of PI-RADS V2.1 score＞3 points and PSAD＞0.23 ng/mLL2 significantly improve diagnostic accuracy.

Objective·To explore the diagnostic and treatment methods for patients with cystic fibrosis(CF)complicated by allergic bronchopulmonary aspergillosis(ABPA),and to enhance clinicians'understanding of these two diseases.Methods·A retrospectively analysis was conducted on the clinical data of 5 patients with CF complicated by ABPA admitted to the Department of Respiratory Medicine,Shanghai Children's Hospital,Shanghai Jiao Tong University School of Medicine,from July 2023 to August 2024.A literature search was performed in PubMed,Web of Science,Cochrane Library,and CNKI for studies published in the past 10 years regarding the co-existence of these diseases.Clinical manifestations,treatment courses,and current epidemiological research were summarized and analyzed.Results·Common symptoms of patients with CF complicated by ABPA included aggravated cough and expectoration,wheezing,fever,and dyspnea.Whole-exome aequencing indicated mutations in the cystic fibrosis transmembrane conductance regulator(CFTR)gene,and an increase in the concentration of chloride ions in sweat.The levels of total serum immunoglobulin E(IgE)and Aspergillus fumigatus-specific IgE increased,and chest computed tomography(CT)showed bronchiectasis and mucus plugging.CF complicated by ABPA is often missed or misdiagnosed for asthma.In China,ABPA is often diagnosed before CF,whereas in Caucasian populations CF is typically diagnosed first.Initial treatment usually involves long-term oral administration of antifungal drugs such as voriconazole combined with glucocorticoids such as prednisone.For patients with frequent relapses or severe side effects,alternative antifungal agents or omalizumab therapy may be considered.Co-infection with Pseudomonas aeruginosa is common,often requiring intravenous antibiotics such as cefoperazone-sulbactam.Current epidemiological research focuses mainly on clinical characteristics,treatment regimens,and novel diagnostic methods.Conclusion·ABPA and CF have overlapping symptoms.Accurate diagnosis of CF complicated by ABPA requires genetic testing,sweat chloride measurement,chest CT,and serological tests.The coexistence of these diseases often leads to missed,delayed,or incorrect diagnosis,increasing patient burden.Present epidemiological studies mainly address clinical characteristics with a lack of targeted clinical drug trials for this patient population.

Objective:To establish an arsenic free fully automatic online digestion iodine analyzer detection method for urinary iodine (hereinafter referred to as the method).Methods:Based on the principle of iodine catalyzed antimony cerium redox reaction, a fully automatic online digestion iodine analyzer was used to determine the iodine content in urine. The effectiveness of the method in terms of detection limit, precision, accuracy (determination of urinary iodine primary standard reference materials GBW09108z and GBW09110f and spiked recovery experiment), and interference experiments was validated. The method was compared with the arsenic cerium catalytic spectrophotometry method recommended by the National Reference Laboratory for Iodine Deficiency Disorders.Results:The linear range of the method was 0 - 300 μg/L, with a correlation coefficient │ r│> 0.999 5. The qualitative and quantitative detection limits were 7.41 and 18.01 μg/L, respectively. The relative standard deviation ( RSD) of urine samples with different iodine concentrations ranged from 1.0% to 1.7%. The results of the determination of iodine concentrations in urine using standard substances GBW09108z and GBW09110f were within the given standard range, with RSD < 2.5%. The range of spiked recovery rates for urine samples with different iodine concentrations was 101.3% to 104.8%, with an overall average spiked recovery rate of 103.0%. The average concentration of the baseline iodine standard solution was determined to be 116.21 μg/L, and the relative error of the concentration determination with the addition of interfering substances was less than 5.0%. The comparison results showed that there was no statistically significant difference in the measurement results between the two methods ( t = - 0.06, P = 0.952). Conclusions:The method adopts automated detection, which is simple to operate, labor-saving, and does not require the use of arsenic trioxide. It has high precision and accuracy, and is suitable for detection of large quantities of samples.

Objective To explore the diagnostic performance of prostate imaging reporting and data system(PI-RADS)V2.1 score combined with prostate specific antigen(PSA)-related parameters in transition zone prostate cancer(PCa)in patients with PSA levels of 4-20 ng/mL.Methods The clinical data of 129 patients who underwent prostate biopsy were retrospectively analyzed,including age,total prostate specific antigen(tPSA),free prostate specific antigen(fPSA),f/t PSA,prostate volume(PV),and prostate specific antigen density(PSAD).Among 129 patients,52 were diagnosed with transition zone PCa and 77 with benign prostate hyperplasia.The MRI images of all patients were scored according to the PI-RADS V2.1 criteria.The clinical and imaging parameters between transition zone PCa and benign prostate hyperplasia were compared using univariate logistic regression analysis.Independent predic-tors were identified via multivariate logistic regression,and a combined predictive model was constructed.Diagnostic performance of the model was evaluated using the receiver operating characteristic(ROC)curves.Results Univariate logistic regression analysis showed that the transition zone PCa exhibited significantly higher PI-RADS V2.1 score,tPSA,and PSAD than the benign prostate hyperplasia(P＜0.05).Multivariate logistic regression analysis identified PI-RADS V2.1 score and PSAD were independent predictors for predicting transition zone PCa(P＜0.05).Optimal diagnostic thresholds were PI-RADS V2.1 score＞3 points and PSAD＞0.23 ng/mL2.The combined prediction model achieved an area under the curve(AUC)of 0.863,outperforming PI-RADS V2.1 score(AUC=0.821)and PSAD(AUC=0.779)alone(P＜0.05).Conclusion The combination of PI-RADS V2.1 score and PSAD has a high predictive value for transition zone PCa in patients with PSA levels of 4-20 ng/mL.Thresholds of PI-RADS V2.1 score＞3 points and PSAD＞0.23 ng/mLL2 significantly improve diagnostic accuracy.

Objective To construct and verify a risk prediction model of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer,and to screen the optimal model by using machine learning algorithm,so as to provide references for clinical formulation of a nursing risk management plan.Methods The convenience sampling method was used to retrospectively select 476 patients who underwent thoracoscopic radical resection of lung cancer in a tertiary hospital in Hangzhou,Zhejiang Province from January to December 2023 as a construction group.Logistic regression,decision tree,random forest and naive Bayesian model were constructed by SPSS 29.0 and R 4.3.0 software.The prediction performance of each model was compared by accuracy,precision,recall,F1 score and area under the receiver operating characteristic curve,and the optimal model was screened.From January to June 2024,204 patients in the unit were prospectively selected as the research subjects of an external validation group.The discrimination and calibration of the optimal model were evaluated by AUC value and calibration curve.Results A total of 680 patients completed the survey.All 4 models showed that multimodal analgesia,thoracic drainage tube type,pain score,tracheal intubation type,state anxiety and catheter indwelling time were the influencing factors of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer(P＜0.05).The 4 risk prediction models showed that the random forest prediction model had the best comprehensive performance.The external verification results showed that the AUC value was 0.913,and the calibration curve fitted well with the 45° ideal line.Conclusion Among the 4 risk prediction models,the random forest prediction model has the best performance,which is more suitable for the assessment of the risk of emergence agitation in patients undergoing thoracoscopic radical resection of lung cancer,and has good generalization and clinical application value.

This article reports a rare case of pantothenate kinase-associated neurodegeneration: the patient′s initial symptoms were Parkinson-like symptoms such as tremor and bradykinesia, as well as dysarthria. Brain magnetic resonance imaging showed abnormal signals in the bilateral basal ganglia region similar to the tiger′s eye sign. Two heterozygous mutations including c.803A>G(p.Asp268Gly) and c.1021C>T(p.Arg341 *) were found in the pantothenate kinase 2 gene by whole exome sequencing, and the final diagnosis was neurodegeneration with brain iron accumulation type 1, also known as pantothenate kinase-associated neurodegeneration. By reviewing the clinical characteristics, diagnostic approaches and therapeutic strategies, this article aims to enhance the recognition of this disease, avoid misdiagnosis and missed diagnosis, and provide guidance for clinical diagnosis and treatment.