Objective To analyze the rates of drug resistance of carbapenem-resistant Klebsiella pneumoniae (CRKP) and extended-spectrum β-lactamase-producing Escherichia coli (ESBL-E.coli) in bronchoalveolar lavage fluid (BALF) of critically ill patients with severe pneumonia and artificial airway and risk factors of CRKP. Methods Patients with severe pneumonia and artificial airway treated in the Center of Emergency and Intensive Care Unit, Jinshan Hospital, Fudan University from May 2022 to May 2025 were selected. Klebsiella pneumoniae (K. pneumoniae) and Escherichia coli (E.coli) isolated and cultured from BALF of these patients were analyzed. The drug resistance rates of the two bacteria were compared. The multivariate logistic regression was used to analyze related risk factors for CRKP infection. Results A total of 384 patients were included, and 384 strains were cultured, including 330 strains (85.9%) of K. pneumoniae and 54 strains (14.1%) of E.coli. The infection rate of K. pneumoniae was higher. Compared with E.coli, the drug-resistant gene expression rate of K. pneumoniae was lower (37.3% vs 57.4%, P＜0.01). The resistance rates of CRKP to cefotaxime, cefepime, aztreonam, and imipenem were higher than those of ESBL-E.coli (P＜0.003). Both CRKP and ESBL-E.coli had high sensitivity to polymyxin and tigecycline. Multivariate logistic regression showed duration of mechanical ventilation ≥ 7 days, and combination of ≥ 2 antibiotics for over 7 days were independent risk factors for CRKP infection (P＜0.01). Conclusions For patients with severe pneumonia and artificial airway in ICU, K. pneumoniae is the main bacterial infection. CRKP and ESBL-E.coli in BALF exhibit different degrees of drug resistance to various antibacterial agents, both have the characteristic of multidrug resistance, and are sensitive to polymyxin and tigecycline. Prevention and control of risk factors related to CRKP should be formulated particularly.

Background: To investigate directional deviations between pilot holes and final pedicle screw trajectories in freehand placement and analyze risk factors for misplacement. While pedicle screws are widely used in thoracolumbosacral surgery, directional deviations between pilot holes and final screw trajectories remain understudied as potential risk factors for misplacement. Methods: Thirty-three patients undergoing posterior fixation were prospectively enrolled. Inertial measurement units (IMUs) tracked the spatial positions of pedicle finders and screwdrivers via custom software. Surgeons (n = 6) were stratified into senior, middle, and junior groups. Analyzed variables included the use of tapping, surgeon experience, spinal deformity status, screw tip morphology, and surgical parameters. Results: Among 198 implanted screws (6.00 ± 2.88/patient), all exhibited trajectory deviations (8.12° ± 3.47°). Tapping significantly reduced deviations (7.23° ± 3.23° vs. 8.87° ± 3.31°, p < 0.01). Senior surgeons achieved smaller deviations (7.34° ± 3.33°) than the middle group (8.60° ± 3.51°, p = 0.039) and junior group (8.68° ± 3.49°, p = 0.022). Multivariate analysis confirmed tapping (p = 0.001) and senior experience (p = 0.023) as protective factors. No significant associations emerged for spinal deformity (8.43° ± 3.73° vs. 7.97° ± 3.35°, p = 0.377), screw tip type (cylindrical, 8.43° ± 3.26° vs. tapered, 8.07 ± 3.51°; p = 0.637), obesity, or surgical position parameters. Conclusions Freehand pedicle screw placement consistently produces trajectory deviations from pilot holes, and surgeon experience and tapping are modifiable protective factors. The IMU-based tracking system enables quantitative surgical motion analysis, suggesting its utility for training optimization and technique standardization.

ObjectiveTo explore the effects of mechanical pressure regulation on the migration and bone-promoting ability of suture dural cells （S-DCs） and non-suture dural cells （NS-DCs）. MethodsDural cells （S-DCs）， non-cranial suture dural cells （NS-DCs） and cranial suture mesenchymal stem cells （CS-MSCs） of 5-day-old SD rats were isolated and cultured. Four experimental conditions， namely S-DCs-Normal， S-DCs-Stress， NS-DCs-Normal and NS-DCs-Stress， were set according to the source of the cells and whether mechanical pressure （1.07 kPa， 24 hours） was applied. The migration ability of dural cells was detected by cell scratch test. Four experimental condition culture media were collected and co-cultured with CS-MSCs for osteogenic induction. Calcium salt deposition was detected by alizarin red staining， and the expression of osteogenesis-related proteins was detected by Western blot. ResultsCompared with the Normal group， the migration abilities of both S-DCs and NS-DCs decreased after Stress treatment （P<0.05）. Compared with S-DCs， NS-DCs has a weaker migration ability under the same processing conditions （P<0.05）. The conditioned medium experiment showed that Stress treatment reduced the osteogenic ability of CS-MSCs （P<0.05）， and the osteogenic effect of the conditioned medium derived from NS-DCs was weaker than that of S-DCs （P<0.05）. The Western blot results were consistent with the trend of alizarin red staining. Both Stress treatment and NS-DCs sources could down-regulate the expression of osteogenesis-related proteins （P<0.05）. ConclusionMechanical stress can significantly inhibit the migration of dural cells and the osteogenic differentiation process of CS-MSCs mediated by it. The mechanical tolerance and osteogenic regulation ability of S-DCs are significantly better than those of NS-DCs.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

AIM:To evaluate the characteristics of ocular biometric parameters and the distribution of corneal astigmatism(CA)in patients with high myopia before cataract surgery.METHODS:A prospective cross-sectional study was conducted, and 695 cataract patients(695 eyes)with high myopia [defined as an axial length(AL)≥26.00 mm] scheduled to undergo cataract surgery at our hospital from January 2022 to December 2024 were consecutively enrolled, another 695 cataract patients(695 eyes)with normal ALs(22.00 mm ≤AL≤25.00 mm)who underwent cataract surgery at our hospital during the same period were included in the control group. For patients with both eyes eligible, the right eye was used for analysis. Before cataract surgery, IOL Master 700 was used to measure the ocular biometric parameters of both eyes for each patient in the two groups. The medical records and ocular biometric data in the two groups were recorded and collected.RESULTS:There were no statistically significant differences between the two groups in genger, age, corneal diameter, and central corneal thickness(all P>0.05). In the high myopia group, the mean AL was 29.20±2.61 mm, and 252 eyes(34.1%)had AL ≥30.00 mm(extremely high myopia). The mean anterior chamber depth(ACD), lens thickness, vitreous chamber depth(VCD), CA, AL/corneal radius of curvature and VCD/AL in the high myopia group were 3.45±0.40, 4.41±0.47, 21.34±2.60 mm, 1.18±0.78 D, 3.79±0.38, and 0.73±0.03, respectively, which were all greater than those in the control group(all P<0.01). In the high myopia group, 350 eyes(50.4%)had CA ≥1.00 D, 192 eyes(27.6%)had CA ≥1.50 D, and 94 eyes(13.5%)had CA ≥2.00 D, which were all higher than those in the control group(32.8%, 15.1%, and 6.6%, respectively; all P<0.001). In the high myopia group, 87 eyes(12.5%)had flat corneas, 424 eyes(61.0%)had moderate CA, and 40 eyes(5.8%)had high CA. These proportions were all higher than those in the control group(6.0%, 46.9%, and 2.9%, respectively; all P<0.001). In the high myopia group, ACD and ACD/AL were negatively correlated with AL(r=-0.162 and -0.661, respectively; all P<0.001), while both ACD and ACD/AL in the control group were positively correlated with AL(r=0.338 and 0.105, respectively; both P<0.01). In the high myopia group, CA increased with age when the patient's age was ≥50 years(r=0.197, P<0.001), which was consistent with the control group.CONCLUSION: The standardized ocular biometric data of cataract patients with high myopia before cataract surgery are helpful for ophthalmologists to accurately calculate the intraocular lens(IOLs)power and select the appropriate IOL type. The majority of high myopia patients need simultaneous correction of CA during cataract surgery.

OBJECTIVE To investigate the impact of Tongxinluo capsules on the pharmacokinetics of rivaroxaban in rats. METHODS Rats were randomly divided into rivaroxaban alone group （2.70 mg/kg）， low-dose Tongxinluo capsules combined with rivaroxaban group （Tongxinluo capsules 0.28 g/kg+rivaroxaban 2.70 mg/kg）， and high-dose Tongxinluo capsules combined with rivaroxaban group （Tongxinluo capsules 0.84 g/kg+rivaroxaban 2.70 mg/kg）， with five rats in each group. Following seven consecutive days of gavage with normal saline or the corresponding doses of Tongxinluo capsules， the rats were subjected to a final gavage administration of rivaroxaban. Blood samples were collected at 0 h prior to the final administration and at 0.16， 0.33， 0.50， 0.75， 1， 1.5， 2， 4， 8， 12 and 24 h post-final administration. The plasma concentration of rivaroxaban in rats was determined by high-performance liquid chromatography-tandem mass spectrometry. The pharmacokinetic parameters [peak concentration （cmax）， half-life （t1/2）， area under the drug concentration time curve （AUC）， mean residence time （MRT）， clearance （CL）， apparent volume of distribution （Vd） and peak time （tmax）] of each group were calculated using a non-compartmental model of MonolixSuite 2023R1 pharmacokinetic software. RESULTS Compared with rivaroxaban alone group， AUC₀₋ₜ and AUC0-∞ of rivaroxaban in rats were increased significantly in high-dose Tongxinluo capsules+rivaroxaban group （P＜0.05）， while CL was decreased significantly （P＜0.05）； t1/2 and MRT were shortened， tmax was extended， cmax was increased， while Vd was decreased， but there was no statistical significance （P＞0.05）. CONCLUSIONS Rivaroxaban combined with Tongxinluo capsules significantly increases the plasma exposure of rivaroxaban in rats. Potential drug-drug interactions should be considered in clinical practice based on the co-administration conditions.