PURPOSE: Early mortality in major trauma has decreased, but MODS remains a leading cause of poor outcomes, driven by trauma-induced cytokine storms that exacerbate injuries and organ damage. METHODS: This prospective cohort study included 79 major trauma patients (ISS >15) treated in the National Center for Trauma Medicine, Peking University People's Hospital, from September 1, 2021, to July 31, 2023. Patients (1) with ISS >15 (according to AIS 2015), (2) aged 15-80 years, (3) admitted within 6 h of injury, (4) having no prior treatment before admission, were included. Exclusion criteria were (1) GCS score <9 or AIS score ≥3 for TBI, (2) confirmed infection, infectious disease, or high infection risk, (3) pregnancy, (4) severe primary diseases affecting survival, (5) recent use of immunosuppressive or cytotoxic drugs within the past 6 months, (6) psychiatric patients, (7) participation in other clinical trials within the past 30 days, (8) patients with incomplete data or missing blood samples. Admission serum inflammatory cytokines and pathophysiological data were analyzed to develop machine learning models predicting MODS within 7 days. LR, DR, RF, SVM, NB, and XGBoost were evaluated based on the area under the AUROC. The SHAP method was used to interpret results. RESULTS: This study enrolled 79 patients with major trauma, and the median (Q₁, Q₃) age was 51 (35, 59) years (52 males, 65.8%). The inflammatory cytokine data were collected for all participants. Among these patients, 35 (44.3%) developed MODS, and 44 (55.7%) did not. Additionally, 2 patients (2.5%) from the MODS group succumbed. The logistic regression model showed strong performance in predicting MODS. Ten key cytokines, IL-18, Eotaxin, MCP-4, IP-10, CXCL12, MIP-3α, MCP-1, IL-1RA, Cystatin C, and MRP8/14 were identified as critical to the trauma-induced cytokine storm and MODS development. Early elevation of these cytokines achieved high predictive accuracy, with an AUROC of 0.887 (95% CI 0.813-0.976). CONCLUSION Trauma-induced cytokine storms are strongly associated with MODS. Early identification of inflammatory cytokine changes enables better prediction and timely interventions to improve outcomes.
Humans ; Prospective Studies ; Middle Aged ; Male ; Female ; Adult ; Aged ; Cytokine Release Syndrome/etiology* ; Adolescent ; Young Adult ; Aged, 80 and over ; Wounds and Injuries/complications* ; Cytokines/blood* ; Multiple Organ Failure/diagnosis* ; Machine Learning

PURPOSE: To analyze risk factors for severe trauma and establish a nomogram for early risk prediction, to improve the early identification of severe trauma. METHODS: This study was conducted on the patients treated in 81 trauma treatment institutions in Gansu province from 2020 to 2022. Patients were grouped by year, with 5364 patients from 2020 to 2021 as the training set and 1094 newly admitted patients in 2020 as the external validation set. Based on the injury severity score (ISS), patients in the training set were classified into 2 subgroups of the severe trauma group (n = 478, ISS scores ≥25) and the non-severe trauma group (n = 4886, ISS scores <25). Univariate and binary logistic regression analyses were employed to identify independent risk factors for severe trauma. Subsequently, a predictive model was developed using the R software environment. Furthermore, the model was subjected to internal and external validation via the Hosmer-Lemeshow test and receiver operating characteristic curve analysis. RESULTS: In total, 6458 trauma patients were included in this study. Initially, this study identified several independent risk factors for severe trauma, including multiple traumatic injuries (polytrauma), external hemorrhage, elevated shock index, elevated respiratory rate, decreased peripheral oxygen saturation, and decreased Glasgow coma scale score (all p < 0.05). For internal validation, the area under the receiver operating characteristic curve was 0.914, with the sensitivity and specificity of 88.4% and 87.6%, respectively; while for external validation, the area under the receiver operating characteristic curve was 0.936, with the sensitivity and specificity of 84.6% and 93.7%, respectively. In addition, a good model fitting was observed through the Hosmer-Lemeshow test and calibration curve analysis (p > 0.05). CONCLUSION This study establishes a nomogram for early risk prediction of severe trauma, which is suitable for primary healthcare institutions in underdeveloped western China. It facilitates early triage and quantitative assessment of trauma severity by clinicians prior to clinical interventions.
Humans ; Nomograms ; Male ; Female ; Wounds and Injuries/diagnosis* ; Risk Factors ; Middle Aged ; Adult ; Injury Severity Score ; Risk Assessment ; ROC Curve ; Aged ; Logistic Models ; China ; Glasgow Coma Scale

Azoospermia is the complete absence of spermatozoa in the ejaculate in two or more semen analyses after centrifugation. Nonobstructive azoospermia (NOA) represents the most severe form of male factor infertility accounting for 10%-15% of cases and stems from an impairment to spermatogenesis. Understanding of the hypothalamic-pituitary-testicular axis has allowed NOA to be subcategorized by anatomic and/or pathophysiologic level. The etiologies of NOA, and therefore, the differential diagnoses when considering NOA as a cause of male factor infertility, can be subcategorized and condensed into several distinct classifications. Etiologies of NOA include primary hypogonadism, secondary hypogonadism, defects in androgen synthesis and/or response, defective spermatogenesis and sperm maturation, or a mixed picture thereof. This review includes up-to-date clinical, diagnostic, cellular, and histologic features pertaining to the multitude of NOA etiologies. This in turn will provide a framework by which physicians practicing infertility can augment their clinical decision-making, patient counseling, thereby improving upon the management of men with NOA.
Humans ; Azoospermia/diagnosis* ; Male ; Spermatogenesis/physiology* ; Hypogonadism/complications* ; Infertility, Male/etiology* ; Testis/pathology*

Male infertility has seen an increase in prevalence with cases of azoospermia estimated to affect 10%-15% of infertile men. Confirmation of azoospermia subsequently necessitates an early causal differentiation between obstructive azoospermia (OA) and nonobstructive azoospermia (NOA). Although less common when compared to NOA, OA can represent upward 20%-40% of cases of azoospermia. While there are a multitude of etiologies responsible for causing NOA and OA, correctly distinguishing between the two types of azoospermia has profound implications in managing the infertile male. This review represents an amalgamation of the current guidelines and literature which will supply the reproductive physician with a diagnostic armamentarium to properly distinguish between NOA and OA, therefore providing the best possible care to the infertile couple.
Humans ; Azoospermia/etiology* ; Male ; Diagnosis, Differential ; Infertility, Male/etiology*

Male factor infertility has been rising, which accounts for up to 30% of infertility cases and contributes to 50% of overall cases. The aim of this review is to explore the recent advances that have emerged in the field through a narrative review. A comprehensive literature search was conducted using multiple databases, including the Cochrane Library, PubMed, Scopus, and Web of Science. Gray literature was also reviewed through ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform. The findings were presented narratively to encompass the extensive range of published data on male infertility. Significant strides have been made in the field of male infertility, particularly with biomarkers, shear wave elastography, 3-dimensional (3D) bioprinting, artificial intelligence (AI), and robotic and microsurgical treatment, offering promising avenues for diagnosis and treatment. Continued research and technological innovation are essential to further improve outcomes for patients facing male factor infertility.
Humans ; Male ; Infertility, Male/diagnosis* ; Artificial Intelligence ; Elasticity Imaging Techniques ; Bioprinting ; Microsurgery ; Biomarkers ; Robotic Surgical Procedures

The choice of biopsy method is critical in diagnosing prostate cancer (PCa). This retrospective cohort study compared systematic biopsy (SB) or cognitive fusion-targeted biopsy combined with SB (CB) in detecting PCa and clinically significant prostate cancer (csPCa). Data from 2572 men who underwent either SB or CB in Fudan University Shanghai Cancer Center (Shanghai, China) between January 2019 and December 2023 were analyzed. Propensity score matching (PSM) was used to balance baseline characteristics, and detection rates were compared before and after PSM. Subgroup analyses based on prostate-specific antigen (PSA) levels and Prostate Imaging-Reporting and Data System (PI-RADS) scores were performed. Primary and secondary outcomes were the detection rates of PCa and csPCa, respectively. Of 2572 men, 1778 were included in the PSM analysis. Before PSM, CB had higher detection rates for both PCa (62.9% vs 52.4%, odds ratio [OR]: 1.54, P < 0.001) and csPCa (54.9% vs 43.3%, OR: 1.60, P < 0.001) compared to SB. After PSM, CB remained superior in detecting PCa (63.1% vs 47.9%, OR: 1.86, P < 0.001) and csPCa (55.0% vs 38.2%, OR: 1.98, P < 0.001). In patients with PSA 4-12 ng ml -1 (>4 ng ml -1 and ≤12 ng ml -1 , which is also applicable to the following text), CB detected more PCa (59.8% vs 40.7%, OR: 2.17, P < 0.001) and csPCa (48.1% vs 27.7%, OR: 2.42, P < 0.001). CB also showed superior csPCa detection in those with PI-RADS 3 lesions (32.1% vs 18.0%, OR: 2.15, P = 0.038). Overall, CB significantly improves PCa and csPCa detection, especially in patients with PSA 4-12 ng ml -1 or PI-RADS 3 lesions.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Propensity Score ; Retrospective Studies ; Middle Aged ; Aged ; Image-Guided Biopsy/methods* ; Prostate-Specific Antigen/blood* ; Prostate/diagnostic imaging*

Anemia of prematurity (AOP) is a multifactorial condition associated with congenital iron deficiency, low erythropoietin levels, a short lifespan of red blood cells, and iatrogenic blood loss. AOP is a common complication in premature infants that can adversely affect growth, development, and long-term neurocognitive outcomes. To standardize the diagnosis and treatment of AOP, the Neonatal Clinical Practice Guidelines Expert Committee and the Neonatal Evidence-Based Medicine Group of the Commission of Neonatal Medicine of the Cross-Strait Medical and Health Exchange Association, along with the Editorial Office of the Chinese Journal of Contemporary Pediatrics, have developed the "Clinical practice guidelines for the diagnosis and treatment of anemia of prematurity (2025)", based on the World Health Organization's handbook for guideline development and the formulation/revision principles of Chinese clinical practice guidelines. This guideline addresses eight clinical issues related to AOP, including risk factors, early identification, etiological diagnosis, diagnostic criteria, early prevention, transfusion therapy, strategies to improve prognosis, and post-discharge follow-up. It presents 29 recommendations formed from current evidence and expert consensus, aiming to provide guidance and decision-making support for healthcare professionals in the diagnosis and treatment of AOP.
Humans ; Infant, Newborn ; Infant, Premature ; Anemia, Neonatal/diagnosis* ; Anemia/diagnosis* ; Practice Guidelines as Topic

OBJECTIVES: To investigate the clinical sub-phenotype (SP) of pediatric acute kidney injury (AKI) and their association with clinical outcomes. METHODS: General status and initial values of laboratory markers within 24 hours after admission to the pediatric intensive care unit (PICU) were recorded for children with AKI in the derivation cohort (n=650) and the validation cohort (n=177). In the derivation cohort, a least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify death-related indicators, and a two-step cluster analysis was employed to obtain the clinical SP of AKI. A logistic regression analysis was used to develop a parsimonious classifier model with simplified metrics, and the area under the curve (AUC) was used to assess the value of this model. This model was then applied to the validation cohort and the combined derivation and validation cohort. The association between SPs and clinical outcomes was analyzed with all children with AKI as subjects. RESULTS: In the derivation cohort, two clinical SPs of AKI (SP1 and SP2) were identified by the two-step cluster analysis using the 20 variables screened by LASSO regression, namely SP_d1 group (n=536) and SP_d2 group (n=114). The simplified classifier model containing eight variables (P<0.05) had an AUC of 0.965 in identifying the two clinical SPs of AKI (P<0.001). The validation cohort was clustered into SP_v1 group (n=156) and SP_v2 group (n=21), and the combined derivation and validation cohort was clustered into SP1 group (n=694) and SP2 group (n=133). After adjustment for confounding factors, compared with the SP1 group, the SP2 group had significantly higher incidence rates of multiple organ dysfunction syndrome and death during the PICU stay (P<0.001), and SP2 was significantly associated with the risk of death within 28 days after admission to the PICU (P<0.001). CONCLUSIONS This study establishes a parsimonious classifier model and identifies two clinical SPs of AKI with different clinical features and outcomes.The SP2 group has more severe disease and worse clinical prognosis.
Humans ; Acute Kidney Injury/diagnosis* ; Prognosis ; Male ; Female ; Child ; Child, Preschool ; Phenotype ; Infant ; Logistic Models ; Adolescent

OBJECTIVES: To investigate the expression of soluble factor-related apoptosis ligand (sFasL) in peripheral blood and microRNA-147b (miR-147b) in monocytes in children with sepsis and their value in assessing prognosis. METHODS: A prospective study was conducted on 124 children with sepsis (sepsis group), 60 children with common infections (infection group), and 60 healthy children undergoing physical examinations (healthy control group). The independent risk factors for poor prognosis in children with sepsis were analyzed, and the value of serum sFasL and monocyte miR-147b in predicting poor prognosis in children with sepsis was assessed. RESULTS: The serum level of sFasL and the relative expression of miR-147b in monocytes were highest in the sepsis group, followed by the infection group and the healthy control group (P<0.05). The multivariate logistic regression analysis showed that the serum level of sFasL and the relative expression of miR-147b in monocytes were closely associated with the poor prognosis of children with sepsis (P<0.05). The receiver operating characteristic curve analysis showed that the combination of serum sFasL level and relative expression of miR-147b in monocytes had a larger area under the curve compared to each indicator alone in predicting the prognosis of children with sepsis (P<0.05). CONCLUSIONS There are significant increases in the level of sFasL in peripheral blood and the relative expression of miR-147b in monocytes in children with sepsis. The combined use of these two indicators has relatively high clinical value in assessing the prognosis of children with sepsis.
Humans ; Sepsis/diagnosis* ; MicroRNAs/blood* ; Male ; Female ; Monocytes/metabolism* ; Prognosis ; Child, Preschool ; Prospective Studies ; Child ; Infant ; TNF-Related Apoptosis-Inducing Ligand/blood* ; Logistic Models

OBJECTIVES: To investigate the clinical characteristics and prognosis of acute erythroleukemia (AEL) in children. METHODS: A retrospective analysis was conducted on the clinical data, treatment, and prognosis of 8 children with AEL treated at the First Affiliated Hospital of Zhengzhou University from January 2013 to December 2023. RESULTS: Among the 7 patients with complete bone marrow morphological analysis, 4 exhibited trilineage dysplasia, with a 100% incidence of erythroid dysplasia (7/7), a 71% incidence of myeloid dysplasia (5/7), and a 57% incidence of megakaryocytic dysplasia (4/7). Immunophenotyping revealed that myeloid antigens were primarily expressed as CD13, CD33, CD117, CD38, and CD123, with 4 cases expressing erythroid antigens CD71 and 2 cases expressing CD235a. Chromosomal analysis indicated that 2 cases presented with abnormal karyotypes, including +8 in one case and +4 accompanied by +6 in another; no complex karyotypes were observed. Genetic abnormalities were detected in 4 cases, with fusion genes including one case each of dup MLL positive and EVI1 positive, as well as mutations involving KRAS, NRAS, WT1, and UBTF. Seven patients received chemotherapy, with 6 achieving remission after one course of treatment; 2 underwent hematopoietic stem cell transplantation, and all had disease-free survival. Follow-up (median follow-up time of 6 months) showed that only 3 patients survived (2 cases after hematopoietic stem cell transplantation and 1 case during treatment). CONCLUSIONS Children with AEL have unique clinical and biological characteristics, exhibit poor treatment response, and have a poor prognosis; however, hematopoietic stem cell transplantation may improve overall survival rates.
Humans ; Male ; Female ; Prognosis ; Child, Preschool ; Retrospective Studies ; Child ; Leukemia, Erythroblastic, Acute/diagnosis* ; Infant ; Adolescent