Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective To explore the effects of 1 800 MHz electromagnetic radiation(EMR)on cognitive function of 3xTg-AD and 57C mice,providing a theoretical basis for the potential impacts of electromagnetic radiation on the human body.Methods A total of 12 3xTg-AD transgenic mice and 12 wild-type C57 mice were selected as research subjects.The one-month-old mice were divided into four groups:RF WT,Control WT,RF AD,and Control AD,with 6 mice in each group.The 1 800 MHz EMR exposure experiments were conducted from 20:00 to 8:00 the next day for a duration of 5 months.After the exposure,a water maze test was conducted to evaluate the effects of EMR on spatial learning and memory abilities of 3xTg AD mice,along with measurements of body weight,brain weight,and calculation of the brain-to-body ratio.Finally,Western Blot technique was used to measure the levels of APP,NR1,and NR2A in hippocampal tissue to analyze effects of 1 800 MHz EMR on the cognitive function of 3xTg AD mice.Results Under 1 800 MHz EMR exposure,there were no statistically significant differences in Morris water maze spatial learning ability among the four groups(P>0.05).However,longer escape time,greater swimming distances,and more crossings of target quadrant were exhibited in the RF AD group compared to the other groups(P<0.05).Western Blot results showed that the APP protein levels in 3xTg AD mice was higher than those in C57 mice(P<0.05).The expression levels of NR1 protein in the WT group was higher than those in the AD group(P<0.05);in the AD group,the RF AD group had higher levels than the Control WT group(P<0.05),and the NR2A protein levels in the Control WT group were higher than in the other groups(P<0.05).Conclusion Prolonged exposure to 1 800 MHz EMR can affect the learning and cognitive function of both 3xTg AD and C57 mice.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To explore a simple method for measuring the dynamic intrinsic positive end-expiratory pressure (PEEPi) during invasive mechanical ventilation.Methods:A 60-year-old male patient was admitted to the critical care medicine department of Dongying People's Hospital in September 2020. He underwent invasive mechanical ventilation treatment for respiratory failure due to head and chest trauma, and incomplete expiratory flow occurred during the treatment. The expiratory flow-time curve of this patient was served as the research object. The expiratory flow-time curve of the patient was observed, the start time of exhalation was taken as T 0, the time before the initiation of inspiratory action (inspiratory force) was taken as T 1, and the time when expiratory flow was reduced to zero by inspiratory drive (inspiratory force continued) was taken as T 2. Taking T 1 as the starting point, the follow-up tracing line was drawn according to the evolution trending of the natural expiratory curve before the T 1 point, until the expiratory flow reached to 0, which was called T 3 point. According to the time phase, the intrapulmonary pressure at the time just from expiratory to inspiratory (T 1 point) was called PEEPi 1. When the expiratory flow was reduced to 0 (T 2 point), the intrapulmonary pressure with the inhaling power being removed hypothetically was called PEEPi 2. And it was equal to positive end-expiratory pressure (PEEP) set in the ventilator at T 3 point. The area under the expiratory flow-time curve (expiratory volume) between T 0 and T 1 was called S 1. And it was S 2 between T 0 and T 2, S 3 between T 0 and T 3. After sedation, in the volume controlled ventilation mode, approximately one-third of the tidal volume was selected, and the static compliance of patient's respiratory system called "C" was measured using the inspiratory pause method. PEEPi 1 and PEEP 2 were calculated according to the formula "C =ΔV/ΔP". Here, ΔV was the change in alveolar volume during a certain period of time, and ΔP represented the change in intrapulmonary pressure during the same time period. This estimation method had obtained a National Invention Patent of China (ZL 2020 1 0391736.1). Results:① PEEPi 1: according to the formula "C =ΔV/ΔP", the expiratory volume span from T 1 to T 3 was "S 3-S 1", and the intrapulmonary pressure decreased span was "PEEPi 1-PEEP". So, C = (S 3-S 1)/(PEEPi 1-PEEP), PEEPi 1 = PEEP+(S 3-S 1)/C. ②PEEPi 2: the expiratory volume span from T 2 to T 3 was "S 3-S 2", and the intrapulmonary pressure decreased span was "PEEPi 2-PEEP". So, C = (S 3-S 2)/(PEEPi 2-PEEP), PEEPi 2 = PEEP+(S 3-S 2)/C. Conclusion:For patients with incomplete expiratory during invasive mechanical ventilation, the expiratory flow-time curve extension method can theoretically be used to estimate the dynamic PEEPi in real time.

Objective To investigate the effect of electromagnetic wave power density on the expression of glial fibrillary acidic protein(GFAP)in the hippocampus of SD rats under 1800 MHz electromagnetic wave irradiation,and whether it exhibits a"window effect".Methods Ninety-eight 4-week-old SPF-grade SD rats were randomly divided into 14 groups,with 7 rats in each group.Seven groups were exposed groups(frequency:1800 MHz,power densities:0.1 mW/cm2,0.3 mW/cm2,0.5 mW/cm2,0.7 mW/cm2,0.9 mW/cm2,1.0 mW/cm2,1.2 mW/cm2)and corresponding 7 groups were control groups(power density:0 mW/cm2).Exposure was conducted for 12 hours daily for 3 weeks.After exposure,Western Blot was used to detect the expression level of GFAP in the hippocampal tissue,and immunohistochemistry staining was performed to determine the average optical density(MOD)value of GFAP-positive expression products in the DG,CA3,and CA1 regions of the hippocampal tissue,to determine the power density window of GFAP expression in the hippocampus of SD rats under 1800 MHz exposure.Results At power densities of 0.1 mW/cm2 and 0.3 mW/cm2,Western Blot results showed increased expression of GFAP in the rat hippocampus(P<0.05),and immunohistochemistry staining demonstrated increased MOD values of GFAP in the three regions(P<0.05).Conclusion Long-term exposure to 1800 MHz elect-romagnetic radiation has a"window effect"on the expression of GFAP in the DG,CA3,and CA1 regions of the hippocampus in SD rats,with power density windows of 0.1 mW/cm2 and 0.3 mW/cm2.

A 82-year-old man was admitted to hospital with fever,unresponsiveness,elevated hypersensitive C-reactive protein and neutrophile granulocyte.Ceftriaxone was administrated by intravenous dripping in the emergency room,but the effect was not satisfactory.Following his admission to the ward,cefoperazone sulbactam were given.Elizabethkingia meningoseptica was identified by blood culture and further confirmed by 16S rRNA sequencing.The lumbar puncture showed that cerebrospinal fluid pressure was 80 mmH2O(1 mmH2O=0.0098 kPa)and biochemical results were normal.After 11 days of cefoperazone sulbactam treatment,the patient was discharged with negative blood culture.The hypersensitive C-reactive protein and neutrophile granulocyte had also declined.The patient received levofloxacin tablets for anti-infection treatment for 14 d after discharge.No signs of infection were observed in three months'following up.

Objective:To construct a nomogram model for predicting the risk of leukopenia among tuberculosis patients receiving anti-tuberculosis therapy.Methods:A total of 2 681 tuberculosis patients admitted to the affiliated Dongyang Hospital of Wenzhou Medical University from Jan 2013 to Jun 2024，were enrolled in this study. All cases received first line anti-tuberculosis treatment and were randomly divided into training（ n=1 876）and validation groups（ n=805）at a ratio of 7∶3. The endpoint was the occurrence of leukopenia during anti-tuberculosis therapy. In the training group，the predictors were screened by Lasso regression and multivariable Logistic regression analysis，and used to establish a nomogram prediction model. The discrimination power，fitness and clinical applicability were evaluated using the receiver operating characteristic（ROC）curve，calibration curve and decision curve analysis，respectively. Several machine learning models based on different methods（random forest，support vector machine，extreme gradient boosting and naive Bayes）were also constructed in the validation group. Results:There were 15.0%（273/1 876）and 15.9%（128/805）of cases developing leukopenia during anti-tuberculosis therapy in the training group and validation groups，respectively. Following Lasso regression analysis，the multivariable Logistic regression analysis showed that age ≥65 years（ OR=2.997，95% CI 2.185-4.128），alcohol consumption（ OR=4.803，95% CI 3.502-6.593）and diabetes（ OR= 5.459，95% CI 3.914-7.621）were risk factors related to the occurrence of leukopenia；while the higher levels of baseline hemoglobin（ OR=0.979，95% CI 0.971-0.987）and platelet count（ OR=0.996，95% CI 0.995-0.998）were protective factors. Based on these five factors，a nomogram prediction model was developed. The areas under ROC curve（AUCs）were 0.836（95% CI 0.810-0.863）and 0.818（95% CI 0.776-0.860）in the training group and the validation group，respectively. Moreover，this model had good fitness and clinical applicability. The discrimination power of nomogram model was comparable to those of machine learning models. Conclusion:The established nomogram model in this study has good discrimination power，calibration ability and clinical applicability for predicting the risk of leucopenia in tuberculosis patients undergoing anti-tuberculosis therapy.

Objective:To construct a nomogram model for predicting the risk of leukopenia among tuberculosis patients receiving anti-tuberculosis therapy.Methods:A total of 2 681 tuberculosis patients admitted to the affiliated Dongyang Hospital of Wenzhou Medical University from Jan 2013 to Jun 2024，were enrolled in this study. All cases received first line anti-tuberculosis treatment and were randomly divided into training（ n=1 876）and validation groups（ n=805）at a ratio of 7∶3. The endpoint was the occurrence of leukopenia during anti-tuberculosis therapy. In the training group，the predictors were screened by Lasso regression and multivariable Logistic regression analysis，and used to establish a nomogram prediction model. The discrimination power，fitness and clinical applicability were evaluated using the receiver operating characteristic（ROC）curve，calibration curve and decision curve analysis，respectively. Several machine learning models based on different methods（random forest，support vector machine，extreme gradient boosting and naive Bayes）were also constructed in the validation group. Results:There were 15.0%（273/1 876）and 15.9%（128/805）of cases developing leukopenia during anti-tuberculosis therapy in the training group and validation groups，respectively. Following Lasso regression analysis，the multivariable Logistic regression analysis showed that age ≥65 years（ OR=2.997，95% CI 2.185-4.128），alcohol consumption（ OR=4.803，95% CI 3.502-6.593）and diabetes（ OR= 5.459，95% CI 3.914-7.621）were risk factors related to the occurrence of leukopenia；while the higher levels of baseline hemoglobin（ OR=0.979，95% CI 0.971-0.987）and platelet count（ OR=0.996，95% CI 0.995-0.998）were protective factors. Based on these five factors，a nomogram prediction model was developed. The areas under ROC curve（AUCs）were 0.836（95% CI 0.810-0.863）and 0.818（95% CI 0.776-0.860）in the training group and the validation group，respectively. Moreover，this model had good fitness and clinical applicability. The discrimination power of nomogram model was comparable to those of machine learning models. Conclusion:The established nomogram model in this study has good discrimination power，calibration ability and clinical applicability for predicting the risk of leucopenia in tuberculosis patients undergoing anti-tuberculosis therapy.

OBJECTIVE: To find out the circuit pressure and flow at the trigger point by observing the characteristics of the inspiratory trigger waveform of the ventilator, confirm the intra-alveolar pressure as the index to reflect the effort of the trigger according to the working principle of the ventilator combined with the laws of respiratory mechanics, establish the related mathematical formula, and analyze its influencing factors and logical relationship. METHODS: A test-lung was connected to the circuit in a PB840 ventilator and a SV600 ventilator set in pressure-support mode. The positive end-expiratory pressure (PEEP) was set at 5 cmH₂O (1 cmH₂O ≈ 0.098 kPa), and the wall of test-lung was pulled outwards till an inspiratory was effectively triggered separately in slow, medium, fast power, and separately in flow-trigger mode (sensitivity V_Trig 3 L/min, 5 L/min) and pressure-trigger mode (sensitivity P_Trig 2 cmH₂O, 4 cmH₂O). By adjusting the scale of the curve in the ventilator display, the loop pressure and flow corresponding to the trigger point under different triggering conditions were observed. Taking intraalveolar pressure (Pa) as the research object, the Pa (called P_a-T) needed to reach the effective trigger time (T_T) was analyzed in the method of respiratory mechanics, and the amplitude of pressure change (ΔP) and the time span (ΔT) of Pa during triggering were also analyzed. RESULTS: (1) Corresponding relationship between pressure and flow rate at TT time: in flow-trigger mode, in slow, medium and fast trigger, the inhalation flow rate was V_Trig, and the circuit pressure was separately PEEP, PEEP-Pn, and PEEP-Pn' (Pn, Pn', being the decline range, and Pn' > Pn). In pressure-trigger mode, the inhalation flow rate was 1 L/min (PB840 ventilator) or 2 L/min (SV600 ventilator), and the circuit pressure was PEEP-P_Trig. (2) Calculation of P_a-T: in flow-trigger mode, in slow trigger: P_a-T = PEEP-V_TrigR (R represented airway resistance). In medium trigger: P_a-T = PEEP-Pn-V_TrigR. In fast trigger: P_a-T = PEEP-Pn'-V_TrigR. In pressure-trigger mode: P_a-T = PEEP-P_Trig-1R. (3) Calculation of ΔP: in flow trigger mode, in flow trigger: without intrinsic PEEP (PEEPi), ΔP = V_TrigR; with PEEPi, ΔP = PEEPi-PEEP+V_TrigR. In medium trigger: without PEEPi, ΔP = Pn+V_TrigR; with PEEPi, ΔP = PEEPi-PEEP+Pn+V_TrigR. In fast trigger: without PEEPi, ΔP = Pn'+V_TrigR; with PEEPi, ΔP = PEEPi-PEEP+Pn'+V_TrigR. In pressure-trigger mode, without PEEPi, ΔP = P_Trig+1R; with PEEPi, ΔP = PEEPi-PEEP+P_Trig+1R. (4) Pressure time change rate of Pa (F_P): F_P = ΔP/ΔT. In the same ΔP, the shorter the ΔT, the greater the triggering ability. Similarly, in the same ΔT, the bigger the ΔP, the greater the triggering ability. The FP could better reflect the patient's triggering ability. CONCLUSIONS The patient's inspiratory effort is reflected by three indicators: the minimum intrapulmonary pressure required for triggering, the pressure span of intrapulmonary pressure, and the pressure time change rate of intrapulmonary pressure, and formula is established, which can intuitively present the logical relationship between inspiratory trigger related factors and facilitate clinical analysis.
Humans ; Respiration, Artificial/methods* ; Positive-Pressure Respiration ; Lung ; Ventilators, Mechanical ; Respiratory Mechanics

A 82-year-old man was admitted to hospital with fever, unresponsiveness and elevated hypersensitive C-reactive protein, neutrophile granulocyte. Ceftriaxone was administrated by intravenous dripping in the emergency room, but the effect is not satisfied. Following his admission to the ward, anti-infection treatment started and antibiotics including cefoperazone sulbactam were given. Elizabethkingia meningoseptica was identified by blood culture and 16S rRNA sequencing. The lumbar puncture showed that cerebrospinal fluid pressure was 80 mmH₂O (1 mmH₂O=0.0098 kPa), and biochemical results were normal. After 11 days of anti-infection treatment, the patient was discharged with negative blood culture,and his hypersensitive C-reactive protein and neutrophile granulocyte declined. The patient received levofloxacin tablets for anti-infection treatment for 14 d after discharge, and no signs of infection were observed in three months' following up.