To investigate the prevalence of Enterococcus faecalis in saliva and filled root canals of patients requiring endodontic retreatment for apical periodontitis. Patients with apical periodontitis who were referred for endodontic retreatment were examined. The type and quality of the restoration, symptoms, quality of obturation were recorded. During retreatment, an oral rinse sample and root canal sample were cultured using brain-heart infusion agar and bile esculinazide agar to select for E. faecalis. The 16S rRNA technique was used to identify E. faecalis. A total of 32 women and 22 men (mean age: 38 years; s.d.: 11 years) and 58 teeth were studied. The prevalence of E. faecalis was 19% in the saliva and 38% in the root canals. The odds that root canals harbored E. faecalis were increased if the saliva habored this bacterium (odds ratio=9.7; 95% confidence interval=1.8-51.6; P<0.05). Teeth with unsatisfactory root obturation had more cultivable bacterial species in root canals than teeth with satisfactory root obturation (P<0.05). E. faecalis is more common in root canals of teeth with apical periodontitis than in saliva. The prevalence of E. faecalis in root canals is associated with the presence of E. faecalis in saliva.
Adolescent ; Adult ; Aged ; Chi-Square Distribution ; Colony Count, Microbial ; Dental Pulp Cavity ; microbiology ; Dental Restoration Failure ; Enterococcus faecalis ; isolation & purification ; Female ; Humans ; Logistic Models ; Male ; Middle Aged ; Multivariate Analysis ; Periapical Periodontitis ; microbiology ; therapy ; Quality of Health Care ; RNA, Ribosomal, 16S ; genetics ; Retreatment ; Root Canal Obturation ; Saliva ; microbiology ; Young Adult

BACKGROUNDAcupuncture has been shown to be effective in pain relief and anesthesia, and has been suggested for treating various kinds of functional disabilities in traditional Chinese medicine, including knee osteoarthritis (OA). The study aimed to investigate the immediate effects of acupuncture on gait patterns in patients with knee OA.

METHODSTwenty patients with bilateral medial knee OA were assigned evenly and randomly to a sham group and an experimental group. During the experiment, the experimental group underwent a 30-minute formula electro-acupuncture treatment while the sham group received a sham treatment. Before and after treatment, each subject was evaluated for their knee pain using visual analog scales (VAS) and then their performance of level walking using gait analysis. For all the obtained variables, the independent t-test was used for between-group comparisons, while paired t-test was used to investigate the before and after changes.

RESULTSAll the measured data before acupuncture treatment between the groups were not significantly different. The VAS scores were decreased significantly after acupuncture in both groups, and the mean change of the VAS values of the experiment group was 2 times greater than that of the sham group. After formula acupuncture stimulation, while no significant changes were found in all the gait variables in the sham group, the experimental group had significant increases in the gait speed, step length, as well as in several components of the joint angles and moments.

CONCLUSIONSThe results of the study suggest that significantly improved gait performance in the experimental group may be associated with pain relief after treatment, but the relatively small decrease of pain in the sham group was not enough to induce significant improvements in gait patterns. Gait analysis combined with the VAS can be useful for the evaluation of the effect of acupuncture treatment for patients with neuromusculoskeletal diseases and movement disorder.

Acupuncture Therapy ; Aged ; Biomechanical Phenomena ; Female ; Gait ; physiology ; Humans ; Male ; Middle Aged ; Models, Biological ; Osteoarthritis, Knee ; therapy ; Treatment Outcome

Objective: To investigate changes in the median nerve, retinaculum, and carpal tunnel on ultrasound after successful endoscopic carpal tunnel release (ECTR). Materials and Methods: This prospective study involved 37 wrists in 35 patients (5 male, 30 female; mean age ± standard deviation [SD], 56.9 ± 6.7 years) with primary carpal tunnel syndrome (CTS). An in-house developed scoring system (0–3) was used to gauge the clinical improvement after ECTR. Ultrasound was performed before ECTR, and at 1, 3, and 12 months post-ECTR. Changes in the median nerve, flexor retinaculum, and carpal tunnel morphology on ultrasound after ECTR were analyzed. Ultrasound parameters for different clinical improvement groups were compared. Results: All patients improved clinically after ECTR. The average clinical improvement score ± SD at 12 months post-ECTR was 2.2 ± 0.7. The median nerve cross-sectional area proximal and distal to the tunnel decreased at all time intervals postECTR but remained swollen compared to normal values. Serial changes in the median nerve caliber and retinacular bowing after ECTR were more pronounced at the tunnel outlet than at the tunnel inlet. The flexor retinaculum had reformed in 25 (68%) of 37 wrists after 12 months. Conclusion Postoperative changes in median nerve and retinaculum parameters were most pronounced at the tunnel outlet.Even in patients with clinical improvement after ECTR, nearly all ultrasound parameters remain abnormal at one year postECTR. These ultrasound parameters should not necessarily be relied upon to diagnose persistent CTS after ECTR.

Objective: To investigate changes in the median nerve, retinaculum, and carpal tunnel on ultrasound after successful endoscopic carpal tunnel release (ECTR). Materials and Methods: This prospective study involved 37 wrists in 35 patients (5 male, 30 female; mean age ± standard deviation [SD], 56.9 ± 6.7 years) with primary carpal tunnel syndrome (CTS). An in-house developed scoring system (0–3) was used to gauge the clinical improvement after ECTR. Ultrasound was performed before ECTR, and at 1, 3, and 12 months post-ECTR. Changes in the median nerve, flexor retinaculum, and carpal tunnel morphology on ultrasound after ECTR were analyzed. Ultrasound parameters for different clinical improvement groups were compared. Results: All patients improved clinically after ECTR. The average clinical improvement score ± SD at 12 months post-ECTR was 2.2 ± 0.7. The median nerve cross-sectional area proximal and distal to the tunnel decreased at all time intervals postECTR but remained swollen compared to normal values. Serial changes in the median nerve caliber and retinacular bowing after ECTR were more pronounced at the tunnel outlet than at the tunnel inlet. The flexor retinaculum had reformed in 25 (68%) of 37 wrists after 12 months. Conclusion Postoperative changes in median nerve and retinaculum parameters were most pronounced at the tunnel outlet.Even in patients with clinical improvement after ECTR, nearly all ultrasound parameters remain abnormal at one year postECTR. These ultrasound parameters should not necessarily be relied upon to diagnose persistent CTS after ECTR.

Background/Aims:  Rituximab is known to be associated with high hepatitis B virus (HBV) reactivation rate in patients with resolved HBV infection and hematologic malignancy. However, data regarding HBV reactivation (HBVr) in rheumatic patients receiving rituximab is limited. To assess the HBVr rate in hepatitis B surface antigen (HBsAg)-negative patients receiving rituximab for autoimmune diseases in a large real-world cohort. Methods:  From March 2006 to December 2019, 900 patients with negative HBsAg receiving at least one cycle of rituximab for autoimmune diseases in a tertiary medical center in Taiwan were retrospectively reviewed. Clinical outcome and factors associated with HBVr were analyzed. Results: After a median follow-up period of 3.3 years, 21 patients developed HBVr, among whom 17 patients were positive for hepatitis B core antibody (anti-HBc) and four were negative. Thirteen patients had clinical hepatitis flare, while eight patients had HBsAg seroreversion without hepatitis. Old age, anti-HBc positivity, undetectable serum hepatitis B surface antibody level at rituximab initiation and a higher average rituximab dose were associated with a higher HBVr rate. There was no significant difference in the HBVr risk between rheumatoid arthritis and other autoimmune diseases. Among anti-HBc-negative patients, subjects without HBV vaccination at birth had an increased risk of HBVr (4/368, 1.1%) compared with those who received vaccination (0/126, 0%). Conclusions In HBV endemic areas where occult HBV is prevalent, anti-HBc-negative patients, may still be at risk for HBVr after rituximab exposure. HBVr may still be considered in HBsAgnegative patients developing abnormal liver function after rituximab exposure, even in patients with negative anti-HBc.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.