Objective:To compare the accuracy and applicability of three adult height prediction methods based on artificial intelligence-assisted bone age assessment—the Bayley-Pinneau method(BP method), the Tanner-Whitehouse 3 method(TW3 method), and China 05 method—in girls.Methods:This bidirectional cohort study collected clinical data and 690 posteroanterior X-ray images of the left hand from 278 female children who underwent pubertal development assessments at Shenzhen Children′s Hospital between January 2014 and December 2020, with follow-up until adult height was reached. Adult height prediction was performed using BP, TW3, and China 05 methods on artificial intelligence-assisted bone age assessment.Results:The BP and TW3 methods overestimated adult height by(1.7±3.7) cm and(2.6±3.0) cm, respectively, while the China 05 method underestimated adult height by(2.3±3.5) cm. The proportion of PAH within±5 cm of FAH were 80.0% for the TW3 method, 77.0% for the BP method, and 74.2% for the China 05 method, with significant differences among them( P=0.038). Analysis of cases with prediction deviations>10 cm and subgroup comparisons revealed that the TW3 and BP methods were more likely to overestimate adult height in girls aged 6.0-<8.0 years, with delayed bone age, or in the prepubertal stage(all P<0.001). The China 05 method was more prone to underestimate adult height in those with advanced bone age( P<0.001). All three methods showed significantly greater prediction errors(absolute difference between PAH and FAH) in girls with early puberty compared to those with normal pubertal development(all P<0.05). Conclusions:The TW3 and BP methods tend to overestimate adult height in girls, while the China 05 method tends to underestimate it. Caution is warranted when predicting adult height, particularly in girls under 8 years of bone age, with delayed or advanced bone age, and those with early puberty.

This article reviews the diagnosis, therapeutic approaches, and subsequent care for a patient with a complex, long-standing history of encapsulating peritoneal sclerosis (EPS). A 40-year-old male, who had been on peritoneal dialysis (PD) for 11 years, encountered refractory peritonitis, leading to the removal of PD catheter and the subsequent diagnosis of EPS. The patient was transitioned to hemodialysis (HD) and prescribed tamoxifen to mitigate peritoneal fibrosis. After 4 months on HD, the patient underwent a kidney transplant, but acute rejection episode caused the transplanted kidney to fail 3 months postoperatively, necessitating a return to HD. Over the past 7 years, the patient has been repeatedly hospitalized due to recurrent bowel obstructions and infected abdominal fluid accumulation. A multidisciplinary approach, including anti-infective therapy, gastrointestinal intervention, nutritional support, and psychological care, has been instrumental in managing symptoms, and sustaining life. This case underscores the importance of recognizing EPS in long-term PD patients with peritonitis. While discontinuing PD, switching to HD, or receiving kidney transplantation do not halt the progression of EPS, optimized comprehensive management can extend the patient's survival.

Objective To construct a regional collaborative cloud-based treatment model treatment model for patients with severe road traffic injuries,and to preliminarily evaluate the differences in nursing timeliness indicators and outcomes.Methods The regional collaborative cloud-based treatment platform includes 4 ports,including public security traffic police,pre-hospital emergency center,regional trauma center triage,and regional trauma center resuscitation unit.This forms a standardized real-time interactive treatment process between regional medical services and police for patients with severe road traffic injuries.Using a concurrent control study design,241 patients with severe road traffic injuries admitted to the emergency department of a regional trauma center in Zhejiang Province from May 2022 to May 2024 were selected as the study subjects.Among them,120 patients treated with the regional real-time collaborative cloud-based treatment model were designated as an experimental group,while 121 patients treated with the original trauma care process were designated as a control group.The differences in timeliness indicators and outcomes between the 2 groups were compared.Results The study included 241 patients with severe trauma.After the application of the regional collaborative cloud-based treatment model,the time from the scene of the accident to the hospital,the proportion of information early waming,completion time of pre-examination and triage,waiting time of the trauma team,the time of the first CT,the length of multidisciplinary consultation,and the time for completing hospitalization procedures in the experimental group were shorter than those in the control group(P＜0.05),the proportion of information early waming in the experimental group was 100％(120/120),and the proportion of information early waming in the control group was 52.1％(63/121).The difference between the two groups was statistically significant(P＜0.001).The survival rate of the experimental group was 90.8％(109/120),and that of the control group was 86.0％(104/121).There was no significant difference between the two groups(x2=1.399,P=0.237).Conclusion The regional collaborative cloud-based treatment model improves the timeliness and standardization of the treatment of patients with severe road traffic injury,which has certain reference significance and promotion value.

This report summarizes the emergency care and nursing interventions for a Parkinson's disease patient with severe hypothermia complicated by ventricular arrhythmia.Key nursing points included continuous core temperature monitoring with goal-directed,phased,progressive rewarming;proactive identification and rapid response to arrhythmias;precise fluid management and skin protection to dynamically optimize blood perfusion and pressure redistribution;vigilant prevention and early intervention of hypothermia-related complications.With multidisciplinary treatment and meticulous nursing care,the patient was successfully discharged after 17 days of hospitalization with a favorable recovery.At the three-month follow-up after discharge,the patient had recovered well with no recurrence of similar episodes.

Purpose To assess the utility of echocardiographic parameters in predicting adverse cardiovascular in patients with connective tissue disease.Materials and Methods A retrospective analysis was conducted on the clinical and echocardiographic records of patients with connective tissue disease from the Affiliated Hospital of Inner Mongolia Medical University(June 1st,2020 to June 1st,2023)who had complete medical data and at least twelve months of follow-up.Variables were screened based on univariate analysis,combined with clinical expertise and XGBoost feature weight analysis;this information was used to construct a Cox proportional hazards regression model designed to predict composite endpoint events of adverse cardiovascular outcomes.Internal validation was performed using the Bootstrap resampling method,and the model's performance was evaluated.Results The study included 123 participants.The incidence of positive events reached 39.02%(48/123).Mitral valve early diastolic annular velocity(reflecting left heart function)(HR=0.79,P=0.041)and tricuspid annular plane systolic excursion(reflecting right heart function)(HR=0.92,P=0.044)emerged as significant predictors for adverse cardiovascular outcomes.Compared with the clinical model,the model combined with left heart function parameters showed significant improvements in both risk classification and absolute accuracy for short-term and medium-term adverse prognosis(NRI365=0.054,IDI365=0.060,NRI730=0.064,IDI730=0.079,all P<0.05)and optimized risk classification for long-term adverse prognosis(NRI1 095=0.256,P<0.05).In contrast,the model combined with right heart function parameters improved risk classification at all time points(NRI365=0.054,NRI730=0.000,NRI1 095=0.135,all P<0.05).Conclusion Mitral valve early diastolic annular velocity and tricuspid annular plane systolic excursion,which reflect cardiac function,are factors for predicting adverse cardiovascular outcomes among individuals diagnosed with connective tissue disease.Multi-parameter combined models incorporating echocardiographic variables can provide incremental predictive value compared with clinical models.

This article reviews the diagnosis, therapeutic approaches, and subsequent care for a patient with a complex, long-standing history of encapsulating peritoneal sclerosis (EPS). A 40-year-old male, who had been on peritoneal dialysis (PD) for 11 years, encountered refractory peritonitis, leading to the removal of PD catheter and the subsequent diagnosis of EPS. The patient was transitioned to hemodialysis (HD) and prescribed tamoxifen to mitigate peritoneal fibrosis. After 4 months on HD, the patient underwent a kidney transplant, but acute rejection episode caused the transplanted kidney to fail 3 months postoperatively, necessitating a return to HD. Over the past 7 years, the patient has been repeatedly hospitalized due to recurrent bowel obstructions and infected abdominal fluid accumulation. A multidisciplinary approach, including anti-infective therapy, gastrointestinal intervention, nutritional support, and psychological care, has been instrumental in managing symptoms, and sustaining life. This case underscores the importance of recognizing EPS in long-term PD patients with peritonitis. While discontinuing PD, switching to HD, or receiving kidney transplantation do not halt the progression of EPS, optimized comprehensive management can extend the patient's survival.

Objective To construct a regional collaborative cloud-based treatment model treatment model for patients with severe road traffic injuries,and to preliminarily evaluate the differences in nursing timeliness indicators and outcomes.Methods The regional collaborative cloud-based treatment platform includes 4 ports,including public security traffic police,pre-hospital emergency center,regional trauma center triage,and regional trauma center resuscitation unit.This forms a standardized real-time interactive treatment process between regional medical services and police for patients with severe road traffic injuries.Using a concurrent control study design,241 patients with severe road traffic injuries admitted to the emergency department of a regional trauma center in Zhejiang Province from May 2022 to May 2024 were selected as the study subjects.Among them,120 patients treated with the regional real-time collaborative cloud-based treatment model were designated as an experimental group,while 121 patients treated with the original trauma care process were designated as a control group.The differences in timeliness indicators and outcomes between the 2 groups were compared.Results The study included 241 patients with severe trauma.After the application of the regional collaborative cloud-based treatment model,the time from the scene of the accident to the hospital,the proportion of information early waming,completion time of pre-examination and triage,waiting time of the trauma team,the time of the first CT,the length of multidisciplinary consultation,and the time for completing hospitalization procedures in the experimental group were shorter than those in the control group(P＜0.05),the proportion of information early waming in the experimental group was 100％(120/120),and the proportion of information early waming in the control group was 52.1％(63/121).The difference between the two groups was statistically significant(P＜0.001).The survival rate of the experimental group was 90.8％(109/120),and that of the control group was 86.0％(104/121).There was no significant difference between the two groups(x2=1.399,P=0.237).Conclusion The regional collaborative cloud-based treatment model improves the timeliness and standardization of the treatment of patients with severe road traffic injury,which has certain reference significance and promotion value.

This report summarizes the emergency care and nursing interventions for a Parkinson's disease patient with severe hypothermia complicated by ventricular arrhythmia.Key nursing points included continuous core temperature monitoring with goal-directed,phased,progressive rewarming;proactive identification and rapid response to arrhythmias;precise fluid management and skin protection to dynamically optimize blood perfusion and pressure redistribution;vigilant prevention and early intervention of hypothermia-related complications.With multidisciplinary treatment and meticulous nursing care,the patient was successfully discharged after 17 days of hospitalization with a favorable recovery.At the three-month follow-up after discharge,the patient had recovered well with no recurrence of similar episodes.

Purpose To assess the utility of echocardiographic parameters in predicting adverse cardiovascular in patients with connective tissue disease.Materials and Methods A retrospective analysis was conducted on the clinical and echocardiographic records of patients with connective tissue disease from the Affiliated Hospital of Inner Mongolia Medical University(June 1st,2020 to June 1st,2023)who had complete medical data and at least twelve months of follow-up.Variables were screened based on univariate analysis,combined with clinical expertise and XGBoost feature weight analysis;this information was used to construct a Cox proportional hazards regression model designed to predict composite endpoint events of adverse cardiovascular outcomes.Internal validation was performed using the Bootstrap resampling method,and the model's performance was evaluated.Results The study included 123 participants.The incidence of positive events reached 39.02%(48/123).Mitral valve early diastolic annular velocity(reflecting left heart function)(HR=0.79,P=0.041)and tricuspid annular plane systolic excursion(reflecting right heart function)(HR=0.92,P=0.044)emerged as significant predictors for adverse cardiovascular outcomes.Compared with the clinical model,the model combined with left heart function parameters showed significant improvements in both risk classification and absolute accuracy for short-term and medium-term adverse prognosis(NRI365=0.054,IDI365=0.060,NRI730=0.064,IDI730=0.079,all P<0.05)and optimized risk classification for long-term adverse prognosis(NRI1 095=0.256,P<0.05).In contrast,the model combined with right heart function parameters improved risk classification at all time points(NRI365=0.054,NRI730=0.000,NRI1 095=0.135,all P<0.05).Conclusion Mitral valve early diastolic annular velocity and tricuspid annular plane systolic excursion,which reflect cardiac function,are factors for predicting adverse cardiovascular outcomes among individuals diagnosed with connective tissue disease.Multi-parameter combined models incorporating echocardiographic variables can provide incremental predictive value compared with clinical models.

Objective:To compare the accuracy and applicability of three adult height prediction methods based on artificial intelligence-assisted bone age assessment—the Bayley-Pinneau method(BP method), the Tanner-Whitehouse 3 method(TW3 method), and China 05 method—in girls.Methods:This bidirectional cohort study collected clinical data and 690 posteroanterior X-ray images of the left hand from 278 female children who underwent pubertal development assessments at Shenzhen Children′s Hospital between January 2014 and December 2020, with follow-up until adult height was reached. Adult height prediction was performed using BP, TW3, and China 05 methods on artificial intelligence-assisted bone age assessment.Results:The BP and TW3 methods overestimated adult height by(1.7±3.7) cm and(2.6±3.0) cm, respectively, while the China 05 method underestimated adult height by(2.3±3.5) cm. The proportion of PAH within±5 cm of FAH were 80.0% for the TW3 method, 77.0% for the BP method, and 74.2% for the China 05 method, with significant differences among them( P=0.038). Analysis of cases with prediction deviations>10 cm and subgroup comparisons revealed that the TW3 and BP methods were more likely to overestimate adult height in girls aged 6.0-<8.0 years, with delayed bone age, or in the prepubertal stage(all P<0.001). The China 05 method was more prone to underestimate adult height in those with advanced bone age( P<0.001). All three methods showed significantly greater prediction errors(absolute difference between PAH and FAH) in girls with early puberty compared to those with normal pubertal development(all P<0.05). Conclusions:The TW3 and BP methods tend to overestimate adult height in girls, while the China 05 method tends to underestimate it. Caution is warranted when predicting adult height, particularly in girls under 8 years of bone age, with delayed or advanced bone age, and those with early puberty.