Objective:To investigate the association between small vulnerable newborn (SVN) phenotypes and the risk of neurodevelopmental delay at the age of 1 year.Methods:A prospective cohort study was conducted. A total of 25 860 singleton infants from "The Born in Guangzhou Cohort Study" who completed the Gesell developmental scale assessment at 1 year of age between January 2013 and June 2025 were included. Maternal sociodemographic characteristics, and other information were collected using a self-administered questionnaire, and maternal pregnancy-related information and neonatal birth data were extracted from medical records. Global developmental delay (GDD) was defined as a developmental quotient below 86 in ≥3 domains of the Gesell developmental scale, which assesses the adaptive, gross motor, fine motor, language, and personal-social domains. The random forest algorithm was employed for missing data imputation. Based on prematurity, small for gestational age (SGA), and low birth weight (LBW), newborns were categorized into 6 phenotypes: preterm-SGA-LBW, preterm-appropriate for gestational age (AGA)-LBW, preterm-AGA-nonLBW, term-SGA-LBW, term-LBW-only or term-SGA-only, and term-AGA-nonLBW phenotype. Among these, the first 5 were classified as SVN phenotypes, and the last one served as the reference group. Inter-group comparisons were performed using analysis of variance (ANOVA), χ2 tests, or Kruskal-Wallis test, as appropriate.?? Multivariable robust Poisson regression models were applied to analyze the association of different SVN phenotypes with the risks of GDD and developmental delays in specific domains, with stratified analyses by sex. Results:Among the 25 860 infants, 13 719 (53.1%) were male and 12 141 (46.9%) were female. The gestational age at birth was 39.4 (38.6, 40.0) weeks. The overall detection rate of GDD at 1 year of age was 3.7% (962/25 860). The rates of delay across developmental domains, in descending order, language in 8 134 cases (31.5%), gross motor in 4 488 cases (17.4%), personal-social in 1 271 cases (4.9%), adaptive in 1 262 cases (4.9%), and fine motor in 621 cases (2.4%). Compared with the reference group, preterm-AGA-LBW, preterm-SGA-LBW, preterm-AGA-noneLBW, and term-SGA-LBW phenotypes were all associated with an increased risk of GDD, with the adjusted RR (95% CI) of 6.07(5.01-7.35), 4.81(3.11-7.46), 2.10(1.54-2.88) and 1.89(1.29-2.76) respectively.The preterm-AGA-noneLBW phenotype was all associated with an increased risk of delay in gross motor, language and personal-social functional domains (all P<0.05). The term-SGA-LBW phenotype was associated with an increased risk of delay in gross motor, fine motor and personal-social functional domains (all P<0.01). Whereas the term-LBW-only or term-SGA-only phenotype showed no statistically association with developmental delay in any functional domain (all P≥0.05). Conclusion:The combined classification based on gestational age and birth weight helps identify infants at high risk for neurodevelopmental delay at 1 year of age, suggesting that it may offer a reference for the rational allocation of clinical resources.

Objective:To investigate the association between small vulnerable newborn (SVN) phenotypes and the risk of neurodevelopmental delay at the age of 1 year.Methods:A prospective cohort study was conducted. A total of 25 860 singleton infants from "The Born in Guangzhou Cohort Study" who completed the Gesell developmental scale assessment at 1 year of age between January 2013 and June 2025 were included. Maternal sociodemographic characteristics, and other information were collected using a self-administered questionnaire, and maternal pregnancy-related information and neonatal birth data were extracted from medical records. Global developmental delay (GDD) was defined as a developmental quotient below 86 in ≥3 domains of the Gesell developmental scale, which assesses the adaptive, gross motor, fine motor, language, and personal-social domains. The random forest algorithm was employed for missing data imputation. Based on prematurity, small for gestational age (SGA), and low birth weight (LBW), newborns were categorized into 6 phenotypes: preterm-SGA-LBW, preterm-appropriate for gestational age (AGA)-LBW, preterm-AGA-nonLBW, term-SGA-LBW, term-LBW-only or term-SGA-only, and term-AGA-nonLBW phenotype. Among these, the first 5 were classified as SVN phenotypes, and the last one served as the reference group. Inter-group comparisons were performed using analysis of variance (ANOVA), χ2 tests, or Kruskal-Wallis test, as appropriate.?? Multivariable robust Poisson regression models were applied to analyze the association of different SVN phenotypes with the risks of GDD and developmental delays in specific domains, with stratified analyses by sex. Results:Among the 25 860 infants, 13 719 (53.1%) were male and 12 141 (46.9%) were female. The gestational age at birth was 39.4 (38.6, 40.0) weeks. The overall detection rate of GDD at 1 year of age was 3.7% (962/25 860). The rates of delay across developmental domains, in descending order, language in 8 134 cases (31.5%), gross motor in 4 488 cases (17.4%), personal-social in 1 271 cases (4.9%), adaptive in 1 262 cases (4.9%), and fine motor in 621 cases (2.4%). Compared with the reference group, preterm-AGA-LBW, preterm-SGA-LBW, preterm-AGA-noneLBW, and term-SGA-LBW phenotypes were all associated with an increased risk of GDD, with the adjusted RR (95% CI) of 6.07(5.01-7.35), 4.81(3.11-7.46), 2.10(1.54-2.88) and 1.89(1.29-2.76) respectively.The preterm-AGA-noneLBW phenotype was all associated with an increased risk of delay in gross motor, language and personal-social functional domains (all P<0.05). The term-SGA-LBW phenotype was associated with an increased risk of delay in gross motor, fine motor and personal-social functional domains (all P<0.01). Whereas the term-LBW-only or term-SGA-only phenotype showed no statistically association with developmental delay in any functional domain (all P≥0.05). Conclusion:The combined classification based on gestational age and birth weight helps identify infants at high risk for neurodevelopmental delay at 1 year of age, suggesting that it may offer a reference for the rational allocation of clinical resources.

Objective: To evaluate the platelet transfusion requirements in children with high-risk stage Ⅳ neuroblastoma undergoing autologous hematopoietic stem cell transplantation (ASCT), and to identify risk factors for increased transfusion needs and prolonged time to platelet transfusion independence. Methods: This single-center retrospective clinical study included 96 children with high-risk stage Ⅳ neuroblastoma who underwent ASCT from January 2019 to May 2024 in our hospital. Relevant clinical data were collected and analyzed, including age, gender, body surface area, platelet count (PLT) on stem cell infusion day (day 0), conditioning regimen, CD34 stem cell dose, platelet transfusion requirements during transplantation, and time to platelet transfusion independence post-transplant. Results: All 96 (100%) children received transfusion after ASCT. From day 0 to transfusion independence, the median number of platelet transfusion was 3 (2, 4.50), and the median volume of platelet transfused was 3 (2, 4.25) units. Platelet transfusion was required in almost all children in pseudo-healing stage (day 4 to day 6) and polar stage (day 7 to day 14), with transfusion rates as high as 83.33%(n=80) and 100%(n=96), respectively. The median time to platelet transfusion independence post-transplant was 13(11,17) days. Multivariate analysis showed that PLT<100×10 /L on day 0, platelet transfusion within one week before ASCT, the use of “busulfan+ melphalan” conditioning regimen, and CD34 stem cell dose<4.0×10 /kg were associated with significantly increased platelet requirements and numbers of transfusion (P<0.05). PLT<100×10 /L on day 0, platelet transfusion within one week before ASCT, and CD34 stem cell dose<4.0×10 /kg were associated with significantly delayed platelet transfusion independence (P<0.05). Age, sex, and blood type showed no statistically significant association (P>0.05) with post-transplant platelet transfusion requirements or time to transfusion independence in neuroblastoma patients. Conclusion: This study provided quantitative data for platelet transfusion after ASCT in children with high-risk stage Ⅳ neuroblastoma, and identified PLT<100×10 /L on day 0, platelet transfusion within one week before ASCT, CD34 stem cell dose<4.0×10 /kg were risk factors for increased platelet transfusions and delayed transfusion independence. Furthermore, the use of the BuMel (busulfan-melphalan) conditioning regimen was also found to contribute to increased transfusion requirements.

Objective: To evaluate the platelet transfusion requirements in children with high-risk stage Ⅳ neuroblastoma undergoing autologous hematopoietic stem cell transplantation (ASCT), and to identify risk factors for increased transfusion needs and prolonged time to platelet transfusion independence. Methods: This single-center retrospective clinical study included 96 children with high-risk stage Ⅳ neuroblastoma who underwent ASCT from January 2019 to May 2024 in our hospital. Relevant clinical data were collected and analyzed, including age, gender, body surface area, platelet count (PLT) on stem cell infusion day (day 0), conditioning regimen, CD34 stem cell dose, platelet transfusion requirements during transplantation, and time to platelet transfusion independence post-transplant. Results: All 96 (100%) children received transfusion after ASCT. From day 0 to transfusion independence, the median number of platelet transfusion was 3 (2, 4.50), and the median volume of platelet transfused was 3 (2, 4.25) units. Platelet transfusion was required in almost all children in pseudo-healing stage (day 4 to day 6) and polar stage (day 7 to day 14), with transfusion rates as high as 83.33%(n=80) and 100%(n=96), respectively. The median time to platelet transfusion independence post-transplant was 13(11,17) days. Multivariate analysis showed that PLT<100×10 /L on day 0, platelet transfusion within one week before ASCT, the use of “busulfan+ melphalan” conditioning regimen, and CD34 stem cell dose<4.0×10 /kg were associated with significantly increased platelet requirements and numbers of transfusion (P<0.05). PLT<100×10 /L on day 0, platelet transfusion within one week before ASCT, and CD34 stem cell dose<4.0×10 /kg were associated with significantly delayed platelet transfusion independence (P<0.05). Age, sex, and blood type showed no statistically significant association (P>0.05) with post-transplant platelet transfusion requirements or time to transfusion independence in neuroblastoma patients. Conclusion: This study provided quantitative data for platelet transfusion after ASCT in children with high-risk stage Ⅳ neuroblastoma, and identified PLT<100×10 /L on day 0, platelet transfusion within one week before ASCT, CD34 stem cell dose<4.0×10 /kg were risk factors for increased platelet transfusions and delayed transfusion independence. Furthermore, the use of the BuMel (busulfan-melphalan) conditioning regimen was also found to contribute to increased transfusion requirements.

[This corrects the article DOI: 10.1016/j.apsb.2021.07.004.].

Objective:To elucidate the genomic characteristics of the immunoglobulin (IG) heavy-chain variable region and light-chain variable region, the expression of subclones, and the prognostic significance in patients with CLL.Methods:Blood and/or bone marrow specimens were gathered from a cohort of 36 patients with CLL diagnosed at Jiangsu Province Hospital from December 2018 to May 2023, including 12 cases of B cell receptor (BCR) stereotyped patients. IG heavy-chain (IGH) and light-chain (IG Kappa [IGK] and IG lambda [IGL]) gene rearrangements were performed using next-generation sequencing (NGS) technology to analyze the characteristics and prognostic value in CLL.Results:NGS detection of IG variable region (IGHV) demonstrated a significant correlation and superior consistency with Sanger sequencing ( r=0.957, P < 0.001). Among the 36 patients, the IGH variant (IGHV) was observed in 9 (25.0%) but not in 27 (75.0%) participants. The incidence of the MYD88 mutation was higher among patients with mutated IGHV [1/27 (3.7%) vs 4/9 (44.4%), P=0.00]. A high incidence of trisomy 12 was observed in the IGHV #8/#8B subset [4/11 (36.4%) vs 1/25 (4.0%), P=0.023], which were more likely to develop Richter transformation [8/11 (72.7%) vs 4/25 (16.0%), P=0.002]. In the patient cohort, 36 individuals (36/36, 100.0%) used the IGK variable, whereas 15 individuals (15/36, 41.7%) employed the IGL variable (IGLV). IGLV3 - 21 reported the highest utilization rate in IGLV (5/15, 33.3%). Remarkably, patients with CLL with IGLV3-21 fragments were exclusively observed in the Binet C stage and Rai Phase Ⅲ-Ⅳ, with an incidence of del (13) (q14) at 60.0% (3/5). The median time to first treatment (TTFT) of patients with or without IGLV3 - 21 fragments was 5.2 (1.1 - 41.5) and 9.9 (0.1 - 94.4) months, respectively. Using the total reads threshold of 2.5%, 4 (4/36, 11.1%) samples were detected to have two IGHV productive clones. The median TTFT and overall survival (OS) time were 2.8 (0.9-72.7) and 12.8 months in patients with one mutated clone and 57.5 (32.0-120.7) and 51.8 months in those with two mutated clones, respectively. The median TTFT and OS time were 10.9 (0.3-94.4) and 6.3 (0.1 - 12.5) months in patients with one unmutated clone and 49.9 (22.2 - 211.1) and 30.0 (9.6 - 50.3) months in those with multiple unmutated clones, respectively ( P>0.05) . Conclusions:Detection of IG gene rearrangements using NGS technology not only facilitates the analysis of the IGHV mutation status, dominant clones, and prognostic value but also contributes to the exploration of IGK/IGL gene rearrangement fragments and the utilization of subclones. Further, it provides information about the poor prognosis of IGLV3 - 21 CLL. The shortened survival of the two unmutated clone groups in the IGHV unmutated group may indicate a poor prognosis.

Objective:To explore the therapeutic efficacy and prognostic factors of combined rituximab and intensive chemotherapy for sporadic adult Burkitt lymphoma (BL) .Methods:This retrospective study examined the clinical and survival data of 30 patients newly diagnosed with BL between July 2011 and February 2023 at the Blood Diseases Hospital. Kaplan-Meier method was used for survival analysis, and the log-rank test was used for univariate analysis of prognostic factors.Results:The median age of the 30 patients was 43 years (24 - 66 years), and the male to female ratio was 3: 2. Extranodal invasion was present in 80% of the patients, with involvement of the bone marrow in 53.3% and central nervous system in 10.0%. The Ann Arbor stage was Ⅲ and Ⅳ in 86.7%. According to the number of Burkitt Lymphoma International Prognostic Index (BL-IPI) risk factors, patients were classified as low risk (0) in 20.0%, intermediate risk (1) in 43.3%, and high risk (≥2) in 36.7%. All patients were treated with an induction regimen of rituximab combined with intensive chemotherapy, with objective and complete response rates of 80.0% and 76.7%, respectively. The median follow-up was 49 months (6-153 months), and the 5-year progression-free survival (PFS) and overall survival (OS) rates were both (76.7±7.7) %. All patients with limited stage ( n=4) achieved continuous complete remission (CCR). Patients who had high risk, advanced stage sensitive to induction therapy ( n=10) sequentially received first-line autologous hematopoietic stem cell transplantation (auto-HSCT) as consolidation therapy; 9 patients achieved CCR, whereas 1 patient with central nervous system invasion developed early disease progression and died. The BL-IPI low, intermediate, and high risk groups had respective 5-year PFS rates of (83.3±15.2) %, 100.0%, and (45.5±15.0) % ( P=0.0069) and OS rates of (83.3±15.2) %, 100.0%, and (45.5±15.0) % ( P=0.0075). The main adverse effects of induction therapy were myelosuppression and secondary infections, which were effectively managed by appropriate symptomatic treatment. Univariate analysis demonstrated that worse PFS was associated with BL-IPI score ≥2 ( HR=4.90, 95% CI 1.02-23.45, P=0.0329) ; extranodal invasion at ≥2 sites ( HR=12.62, 95% CI 2.59-61.62, P=0.0021) ; and failure to achieve first complete response (CR1) after induction therapy ( HR=31.86, 95% CI 4.19-242.20, P<0.0001) . Conclusions:Intensive immunochemotherapy regimens were effective and well-tolerated by adult patients with highly aggressive BL. Treatment efficacy was ideal in patients with limited-stage disease, whereas prognosis was unsatisfactory in patients with high-risk BL-IPI. Sequential first-line auto-HSCT consolidation therapy may further improve outcomes in patients with high-risk advanced-stage disease who are sensitive to induction therapy. BL-IPI score ≥2, extranodal invasion at ≥2 sites, and failure to achieve CR1 after induction therapy were adverse prognostic factors in adult patients with BL.

Objective:To evaluate the impact of roxadustat on thyroid function and to identify the associated factors in patients undergoing maintenance peritoneal dialysis (PD).Methods:This study was a single-center retrospective study. PD patients who received roxadustat or recombinant human erythropoietin (rHuEPO) treatment at Nanjing Drum Tower Hospital between January 2020 and June 2024 were included. The general and clinical information as well as laboratory indexes were collected. Serum free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone (TSH) were compared before and after treatment initiation. Hemoglobin (Hb) responses were also observed between the two groups. Logistic regression analysis was performed to explore the factors associated with thyroid function changes.Results:A total of 120 patients were enrolled, with an age of (55.17±16.42) years, including 66 males (55.0%). There were 81 patients received roxadustat (roxadustat group) and 39 patiens received rHuEPO (rHuEPO group). Compared to the rHuEPO group, the roxadustat group had a higher proportion of patients with diabetes ( χ 2= 4.172, P=0.041), a shorter PD vintage ( Z=-3.406, P=0.002), a lower serum level of total cholesterol ( Z=-2.082, P=0.037) and a lower level of fasting blood glucose ( Z=-2.589, P=0.010). Following treatment with roxadustat, the levels of FT4 ( Z=-5.349, P<0.01) and TSH ( Z=-3.720, P<0.01) decreased significantly. In contrast, no significant changes in FT4 or TSH levels were observed in the rHuEPO group (both P>0.05). For both roxadustat and rHuEPO groups, there were no significant changes in FT3 levels after treatment (both P>0.05). Multivariate analysis identified that higher baseline TSH (TSH≥2.27 μIU/ml, OR=1.581, 95% CI 1.196-2.089, P=0.001) and roxadustat exposure ( OR=3.432, 95% CI 1.410-8.355, P=0.007) as independent associated factors of subsequent TSH decline, and identified that higher baseline FT4 (FT4≥14.9 pmol/L, OR=1.390, 95% CI 1.162-1.662, P=0.001) and roxadustat exposure ( OR=5.798, 95% CI 2.225-15.113, P=0.001) as independent associated factors of subsequent FT4 decline. The degrees of hemoglobin changes after roxadustat or rHuEPO treatment did not differ significantly between roxadustat group and rHuEPO group ( t=-1.062, P=0.290). Of the 31 patients who underwent a second thyroid function test during roxadustat treatment, 24 continued with the original regimen, while 7 discontinued roxadustat. Among 24 patients who maintained roxadustat treatment, TSH ( Z=-0.400, P=0.689) and FT4 ( t=0.143, P=0.888) remained stable between the second and third tests. All 7 patients who discontinued roxadustat treatment showed TSH rebound and the changes of TSH levels were more significant than that in continuers ( Z=-2.505, P=0.012). FT4 recovery occurred in only 3 of them, with no significant difference in FT4 change between discontinuers and continuers ( Z=-0.685, P=0.493). Conclusions:Roxadustat commonly suppresses TSH and FT4, but not FT3, in PD patients. Baseline levels of TSH and FT4 are key associated factors of the inhibitory effect of roxadustat on thyroid function. This suppression does not intensify with prolonged exposure and is reversible after discontinuation, with TSH levels normalizing more quickly than FT4. Roxadustat-induced thyroid suppression does not compromise its efficacy in treating renal anemia.

Objective To observe the value of multi-task improved nnU-Net model based on enhanced CT for segmenting primary oral cancer and predicting patients'relapse free survival(RFS).Methods Enhanced CT data of 186 cases of primary oral cancer were retrospectively analyzed,and a multi-task improved nnU-Net model was constructed for tumor segmentation and survival prediction tasks.Pre-training of tumor segmentation was completed with nnU-Net as the baseline network,and the accuracy of recognizing and segmenting tumor was improved by enhancing the decoder through the modified skip connection.Then univariable and multivariable regression analyses were used to select clinical features closely associated with RFS.Radiomics and deep learning features were also extracted to construct a survival prediction model,with fine-tuning of the above model.The training set,validation set and test set were divided at a ratio of 7∶2∶1.Dice similarity coefficient(DSC)was used to evaluate the segmentation performance of the modified model,and the consistency index C-index was used to verify the performance of the improved model for predicting RFS.Results DSC of the multi-task improved nnU-Net model(0.78)for segmenting primary oral cancer was superior to that of 3D Inception ResNet(0.65),3D InceptSENet(0.75)and 3D U-Net models(0.69),respectively,its C-index for predicting RFS(0.798)was higher than that of Cox regression model(0.744),ICARE model(0.761),random forest model(0.744),DeepSurv model(0.735),nnU-Net model(0.760)and radiology+nnU-Net model(0.744),respectively.DSC for segmenting primary oral cancer and C-index for predicting RFS of multi-task improved nnU-Net model were both superior to those of simple baseline network(0.653 and 0.649),baseline network+multi-scale convolution fusion(0.755 and 0.752),as well as baseline network combined with clinical features(0.764 and 0.759),radiomics features(0.770 and 0.764)and clinical+radiomics features(0.773 and 0.761),respectively.Conclusion Multi-task improved nnU-Net model could be used to effectively improve the accuracy of tumor segmentation and predicting patients'RFS.

Objective To observe the value of multi-task improved nnU-Net model based on enhanced CT for segmenting primary oral cancer and predicting patients'relapse free survival(RFS).Methods Enhanced CT data of 186 cases of primary oral cancer were retrospectively analyzed,and a multi-task improved nnU-Net model was constructed for tumor segmentation and survival prediction tasks.Pre-training of tumor segmentation was completed with nnU-Net as the baseline network,and the accuracy of recognizing and segmenting tumor was improved by enhancing the decoder through the modified skip connection.Then univariable and multivariable regression analyses were used to select clinical features closely associated with RFS.Radiomics and deep learning features were also extracted to construct a survival prediction model,with fine-tuning of the above model.The training set,validation set and test set were divided at a ratio of 7∶2∶1.Dice similarity coefficient(DSC)was used to evaluate the segmentation performance of the modified model,and the consistency index C-index was used to verify the performance of the improved model for predicting RFS.Results DSC of the multi-task improved nnU-Net model(0.78)for segmenting primary oral cancer was superior to that of 3D Inception ResNet(0.65),3D InceptSENet(0.75)and 3D U-Net models(0.69),respectively,its C-index for predicting RFS(0.798)was higher than that of Cox regression model(0.744),ICARE model(0.761),random forest model(0.744),DeepSurv model(0.735),nnU-Net model(0.760)and radiology+nnU-Net model(0.744),respectively.DSC for segmenting primary oral cancer and C-index for predicting RFS of multi-task improved nnU-Net model were both superior to those of simple baseline network(0.653 and 0.649),baseline network+multi-scale convolution fusion(0.755 and 0.752),as well as baseline network combined with clinical features(0.764 and 0.759),radiomics features(0.770 and 0.764)and clinical+radiomics features(0.773 and 0.761),respectively.Conclusion Multi-task improved nnU-Net model could be used to effectively improve the accuracy of tumor segmentation and predicting patients'RFS.