Objective To observe the value of habitat model based on lung CT for predicting brain metastasis(BM)of lung adenocarcinoma with epidermal growth factor receptor(EGFR)mutation.Methods Data of plain lung CT of 198 lung adenocarcinoma patients with EGFR-mutant were retrospectively analyzed.The patients were divided into training set(n=138)and test set(n=60)at the ratio of 7∶3,and further divided into BM subgroup and non-BM subgroup in each set.Then a logistic regression(LR)clinical model was constructed using variables being statistically different between subgroups in training set.For features extracted from tumor and subregion of tumor,radiomics models and habitat models were constructed based on random forest,Gaussian process(GP)and support vector machine(SVM)algorithms,and the best radiomics and habitat models with generalization ability were screened.LR combined model was constructed based on the predicted values of the best radiomics and habitat models with generalization ability,as well as the clinical model.Then receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the efficacy of each model for predicting BM of lung adenocarcinoma with EGFR-mutant.Spearman correlation analysis was performed to observe the correlations between Ki-67 and habitat features of lung adenocarcinoma with EGFR-mutant.Results AUC of LR clinical model,GP radiomics model,SVM habitat model and LR combined model for predicting BM of lung adenocarcinoma with EGFR-mutant was 0.700,0.726,0.801 and 0.834 in training set,0.754,0.600,0.715 and 0.848 in test set,respectively.AUC of LR combined model was higher than that of LR clinical model in training set(P＜0.001),also higher than that of GP radiomics model in test set(P=0.010).Compared with GP radiomics model and SVM habitat model,the performance of LR combined model was significantly and positively improved in training set(integrated discrimination improvement index[IDI]=8.60%,8.55%,both P＜0.001).Ki-67 level of EGFR-mutant lung adenocarcinoma was lowly and positively correlated with habitatmap_original_glszm_lalgle extracted from habitat map(│rs│=0.201,P=0.004).Conclusion The habitat model based on lung CT could be used to predict BM of lung adenocarcinoma with EGFR-mutant effectively.

Objective:To carry out cytogenetic and molecular genetic analysis for two infertile patients carrying rare small supernumerary marker chromosomes (sSMC).Methods:Two infertile patients who received reproductive and genetic counseling at CITIC Xiangya Reproductive and Genetic Hospital on October 31, 2018 and May 10, 2021, respectively were selected as the study subjects. The origin of sSMCs was determined by conventional G banding, fluorescence in situ hybridization (FISH) and copy number variation sequencing (CNV-seq). Microdissection combined with high-throughput whole genome sequencing (MicroSeq) was carried out to determine the fragment size and genomic information of their sSMCs. Results:For patient 1, G-banded karyotyping and FISH revealed that he has a karyotype of mos47, XY, del(16)(p10p12), + mar[65]/46, XY, del(16)(p10p12)[6]/48, XY, del(16)(p10p12), + 2mar[3].ish mar(Tel 16p-, Tel 16q-, CEP 16-, WCP 16+ ). CNV analysis has yielded a result of arr[GRCh37]16p12.1p11.2(24999364_33597595)×1[0.25]. MicroSeq revealed that his sSMC has contained the region of chromosome 16 between 24979733 and 34023115 (GRCh37). For patient 2, karyotyping and reverse FISH revealed that she has a karyotype of mos 47, XX, + mar[37]/46, XX[23].rev ish CEN5, and CNV analysis has yielded a result of seq[GRCh37]dup(5)(p12q11.2)chr5: g(45120001_56000000)dup[0.8]. MicroSeq results revealed that her sSMC has contained the region of chromosome 5 between 45132364 and 55967870(GRCh37). After genetic counseling, both couples had opted in vitro fertilization (IVF) treatment and preimplantation genetic testing (PGT). Conclusion:For individuals harboring sSMCs, it is vital to delineate the origin and structural characteristics of the sSMCs for their genetic counseling and reproductive guidance. Preimplantation genetic testing after microdissection combined with high-throughput whole genome sequencing (MicroSeq-PGT) can provide an alternative treatment for carrier couples with a high genetic risk.

Objective:To explore potential predictors of refractory Mycoplasma pneumoniae pneumonia (RMPP) in early stage. Methods:The prospective multicenter study was conducted in Zhejiang, China from May 1 st, 2019 to January 31 st, 2020. A total of 1 428 patients with fever >48 hours to <120 hours were studied. Their clinical data and oral pharyngeal swab samples were collected; Mycoplasma pneumoniae DNA in pharyngeal swab specimens was detected. Patients with positive Mycoplasma pneumoniae DNA results underwent a series of tests, including chest X-ray, complete blood count, C-reactive protein, lactate dehydrogenase (LDH), and procalcitonin. According to the occurrence of RMPP, the patients were divided into two groups, RMPP group and general Mycoplasma pneumoniae pneumonia (GMPP) group. Measurement data between the 2 groups were compared using Mann-Whitney U test. Logistic regression analyses were used to examine the associations between clinical data and RMPP. Receiver operating characteristic (ROC) curves were used to analyse the power of the markers for predicting RMPP. Results:A total of 1 428 patients finished the study, with 801 boys and 627 girls, aged 4.3 (2.7, 6.3) years. Mycoplasma pneumoniae DNA was positive in 534 cases (37.4%), of whom 446 cases (83.5%) were diagnosed with Mycoplasma pneumoniae pneumonia, including 251 boys and 195 girls, aged 5.2 (3.3, 6.9) years. Macrolides-resistant variation was positive in 410 cases (91.9%). Fifty-five cases were with RMPP, 391 cases with GMPP. The peak body temperature before the first visit and LDH levels in RMPP patients were higher than that in GMPP patients (39.6 (39.1, 40.0) vs. 39.2 (38.9, 39.7) ℃, 333 (279, 392) vs. 311 (259, 359) U/L, both P<0.05). Logistic regression showed the prediction probability π=exp (-29.7+0.667×Peak body temperature (℃)+0.004×LDH (U/L))/(1+exp (-29.7+0.667×Peak body temperature (℃)+0.004 × LDH (U/L))), the cut-off value to predict RMPP was 0.12, with a consensus of probability forecast of 0.89, sensitivity of 0.89, and specificity of 0.67; and the area under ROC curve was 0.682 (95% CI 0.593-0.771, P<0.01). Conclusion:In MPP patients with fever over 48 to <120 hours, a prediction probability π of RMPP can be calculated based on the peak body temperature and LDH level before the first visit, which can facilitate early identification of RMPP.

OBJECTIVE: To investigate the prevalence, risk factors, duration and outcome of delirium in intensive care unit (ICU) patients. METHODS: A prospective observational study was conducted for critically ill patients admitted to the department of critical care medicine, the Affiliated Hospital of Guizhou Medical University from September to November 2021. Delirium assessments were performed twice daily using the Richmond agitation-sedation scale (RASS) and confusion assessment method of ICU (CAM-ICU) for patients who met the inclusions and exclusion criteria. Patient's age, gender, body mass index (BMI), underlying disease, acute physiologic assessment and chronic health evaluation (APACHE) at ICU admission, sequential organ failure assessment (SOFA) at ICU admission, oxygenation index (PaO₂/FiO₂), diagnosis, type of delirium, duration of delirium, outcome, etc. were recorded. Patients were divided into delirium and non-delirium groups according to whether delirium occurred during the study period. The clinical characteristics of the patients in the two groups were compared, and risk factors for the development of delirium were screened using univariate analysis and multivariate Logistic regression analysis. RESULTS: A total of 347 ICU patients were included, and delirium occurred in 57.6% (200/347) patients. The most common type was hypoactive delirium (73.0% of the total). Univariate analysis showed statistically significant differences in age, APACHE score and SOFA score at ICU admission, history of smoking, hypertension, history of cerebral infarction, immunosuppression, neurological disease, sepsis, shock, glucose (Glu), PaO₂/FiO₂ at ICU admission, length of ICU stay, and duration of mechanical ventilation between the two groups. Multivariate Logistic regression analysis showed that age [odds ratio (OR) = 1.045, 95% confidence interval (95%CI) was 1.027-1.063, P < 0.001], APACHE score at ICU admission (OR = 1.049, 95%CI was 1.008-1.091, P = 0.018), neurological disease (OR = 5.275, 95%CI was 1.825-15.248, P = 0.002), sepsis (OR = 1.941, 95%CI was 1.117-3.374, P = 0.019), and duration of mechanical ventilation (OR = 1.005, 95%CI was 1.001-1.009, P = 0.012) were all independent risk factors for the development of delirium in ICU patients. The median duration of delirium in ICU patients was 2 (1, 3) days. Delirium was still present in 52% patients when they discharged from the ICU. CONCLUSIONS The prevalence of delirium in ICU patients is over 50%, with hypoactive delirium being the most common. Age, APACHE score at ICU admission, neurological disease, sepsis and duration of mechanical ventilation were all independent risk factors for the development of delirium in ICU patients. More than half of patients with delirium were still delirious when they discharged from the ICU.
Humans ; Prevalence ; Critical Care ; Risk Factors ; Sepsis ; Intensive Care Units

The article analyzes chief physician SUN Wuquan's empirical characteristics in treating neck-type cervical spondylosis:disease differentiation combined with pattern differentiation,emphasizing the assessment of tendons and bones,with DING's Tuina(Chinese therapeutic massage)manipulations and static Gongfa(Qigong exercise)as the predominant treatment,inherits the academic features of DING's Tuina school,"paying equal attention to tendons and bones,putting function first";thus provides a reference for treating neck-type cervical spondylosis with Tuina therapy.

Objective:To preliminarily observe the feasibility of different immobilization techniques for total skin irradiation (TSI) using helical tomotherapy.Methods:Three eczema scrophuloderma patients treated with TSI in Sun Yat-sen University Cancer Center were immobilized with low-temperature thermoplastic in a prone position, diving suit combined with negative pressure vacuum bag in a supine position, low-temperature thermoplastic combined with vacuum bag in a supine position, respectively. Different immobilization effects were observed. The conformity index (CI) of the target area, heterogeneity index (HI) of the target area, and the mean dose (D mean) of the target area were calculated. Results:Three immobilization methods could achieve satisfactory immobilization effects, and all the dosimetric parameters of radiation treatment plans met the clinical requirements. The average set-up errors in the left and right, head and foot, and abdomen and back directions of three patients were (0.26±3.40) mm, (-2.63±4.63) mm and (6.13±4.86) mm, respectively. The CI, HI andD mean were0.56±0.09, 1.186±0.059 and (2586.56±63.28) cGy. Conclusions:Low-temperature thermoplastic or diving suits can be combined with vacuum bags for immobilization in TSI. The epidermal dose can be increased with bolus through the dose-building effect, which can provide a safe and reliable method for TSI in helical tomotherapy.

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.

Objective:To investigate the etiology of necrotizing pneumonia (NP) in children and the clinical characteristics of NP caused by different pathogens in China.Methods:A retrospective, case-control study was performed in children with NP who were admitted to 13 hospitals in China from January 2008 to December 2019. The demographic and clinical information, laboratory data, etiological and radiological findings were analyzed. The data were divided into three groups based on the following years: 2008-2011, 2012-2015 and 2016-2019, and the distribution characteristics of the pathogens in different period were compared. Meanwhile, the pathogens of pediatric NP in the southern and northern China were compared. And the clinical characteristics of the Mycoplasma pneumoniae (MP) NP and the bacterial NP were also compared. T-test or Mann-Whitney nonparametric test was used for comparison of numerical variables, and χ 2 test was used for categorical variables. Results:A total of 494 children with NP were enrolled, the median ages were 4.7 (0.1-15.3) years, including 272 boys and 222 girls. Among these patients, pathogens were identified in 347 cases and the pathogen was unclear in the remaining 147 cases. The main pathogens were MP (238 cases), Streptococcus pneumoniae (SP) (61 cases), Staphylococcus aureus (SA) (51 cases), Pseudomonas aeruginosa (13 cases), Haemophilus influenzae (10 cases), adenovirus (10 cases), and influenza virus A (7 cases), respectively. MP was the most common pathogen in all three periods and the proportion increased yearly. The proportion of MP in 2016-2019 was significantly higher than that in 2012-2015 (52.1% (197/378) vs. 36.8% (32/87), χ 2= 6.654, P=0.010), while there was no significant difference in the proportion of MP in 2012-2015 and that in 2008-2011 (36.8% (32/87) vs. 31.0% (9/29), χ2=0.314, P=0.575).Regarding the regional distribution, 342 cases were in the southern China and 152 in the northern China. Also, MP was the most common pathogen in both regions, but the proportion of MP was higher and the proportion of SP was lower in the north than those in the south (60.5% (92/152) vs. 42.7% (146/342), χ 2=13.409, P<0.010; 7.9% (12/152) vs. 14.3% (49/342), χ 2= 4.023, P=0.045). Comparing the clinical characteristics of different pathogens, we found that fever and cough were the common symptoms in both single MP and single bacterial groups, but chest pain was more common (17.0% (34/200) vs. 6.1% (6/98), χ 2=6.697, P=0.010) while shortness of breath and wheezing were less common in MP group (16.0% (32/200) vs. 60.2% (59/98), χ 2=60.688, P<0.01; 4.5% (9/200) vs. 21.4% (21/98), χ 2=20.819, P<0.01, respectively). The white blood cell count, C-reactive protein and procalcitonin in the bacterial group were significantly higher than those in the MP group (14.7 (1.0-67.1)×10 9/L vs. 10.5 (2.5-32.2)×10 9/L, 122.5 (0.5-277.3) mg/L vs. 51.4 (0.5-200.0) g/L, 2.13 (0.05-100.00) μg/L vs. 0.24 (0.01-18.85) μg/L, Z=-3.719, -5.901 and -7.765, all P<0.01). Conclusions:The prevalence of pediatric NP in China shows an increasing trend during the past years. MP, SP and SA are the main pathogens of NP, and the most common clinical symptoms are fever and cough. The WBC count, C-reactive protein and procalcitonin in bacterial NP are significantly higher than those caused by MP.

Objective:To establish autoverification rules for coagulation tests in multicenter cooperative units, in order to reduce workload for manual review of suspected results and shorten turnaround time (TAT) of test reports, while ensure the accuracy of results.Methods:A total of 14 394 blood samples were collected from fourteen hospitals during December 2019 to March 2020. These samples included: Rules Establishment Group 11 230 cases, including 1 182 cases for Delta check rules; Rules Validation Group 3 164 cases, including 487cases for Delta check; Clinical Application Trial Group 77 269 cases. Samples were analyzed for coagulation tests using Sysmex CS series automatic coagulation analyzers, and the clinical information, instrument parameters, test results, clinical diagnosis, medication history of anticoagulant and other relative results such as HCT, TG, TBIL, DBIL were summarized; on the basis of historical data, the 2.5 and 97.5 percentile of all data arranged from low to high were initially accumulated; on the basis of clinical suggestions, critical values and specific drug use as well as relative guidelines, autoverification rules and limits were established.The rules were then input into middleware, in which Stage I/Stage II validation was done. Positive coincidence, negative coincidence, false negative, false positive, autoverification pass rate, passing accuracy (coincidence of autoverification and manual verification) were calculated. Autoverification rules underwent trial application in coagulation results reports.Results:(1) The autoverification algorisms involve 33 rules regarding PT/INR, APTT, FBG, D-dimer, FDP,Delta check, reaction curve and sample abnormalities; (2)Autoverification Establishment Group showed autoverification pass rate was 68.42% (7 684/11 230), the false negative rate was 0%(0/11230), coincidence of autoverification and manual verification was 98.51%(11 063/11 230), in which positive coincidence and negative coincidence were respectively 30.09% (3 379/11 230) and 68.42%(7 684/11 230); Autoverification Validation Group showed autoverification pass rate was 60.37%(1 910/3 164), the false negative rate was 0%(0/11 230), coincidence of autoverification and manual verification was 97.79%(3 094/3 164), in which positive coincidence and negative coincidence were respectively 37.42%(1 184/3 164) and 60.37%(1 910/3 164); (3) Trialed implementation of these autoverification rules on 77 269 coagulation samples showed that the average TAT shortened by 8.5 min-83.1 min.Conclusions:This study established 33 autoverification rules in coagulation tests. Validation showedthese rules could ensure test quality while shortening TAT and lighten manual workload.

OBJECTIVE： To evaluate the effectiveness of trolamine for preventing and treating radiation dermatitis （RD） and evidence quality， and to provide reference for clinical use. METHODS： Retrieved from PubMed， Cochrane library， Embase， CNKI， Wanfang and VIP database， randomized controlled trials （RCTs） about trolamine （trial group） versus usual care （control group） for preventing and treating RD were collected. After data extraction， Cochrane bias risk assessment tool 5.0.2 was used to assess the bias risk， and Rev Man 5.3 statistical software was used to perform the Meta-analysis. GRADE evidence quality grading system was used to evaluate the evidence quality of outcome indexes. RESULTS： Seven RCTs were included， involving 782 patients. Results of Meta-analysis showed that there was no statistical significance in total incidence of RD [OR＝0.50， 95％CI （0.23， 1.11）， P＝0.09]， and the incidence of grade Ⅰ RD [OR＝1.32， 95％CI（0.96，1.81）， P＝0.09]， grade Ⅱ RD [OR＝1.07， 95％CI（0.80，1.42）， P＝0.66]， grade Ⅲ RD [OR＝0.69， 95％CI（0.45，1.04）， P＝0.07] or grade Ⅳ RD [OR＝0.43， 95％CI（0.17，1.05）， P＝0.07] between 2 groups. Results of Grade evidence quality evaluation showed that total incidence of RD， and the incidence of grade Ⅱ RD and grade Ⅳ RD were recommended by moderate-level evidence in 2 groups， while the incidence of grade Ⅰ and grade Ⅲ RD were recommended by low-level evidence. CONCLUSIONS： Trolamine is not effective in preventing and treating RD， and can not reduce the incidence of RD.