Robot-assisted radical nephroureterectomy using the KangDuo Surgical Robot-01 System versus the da Vinci System: a multicenter prospective randomized controlled trial

ABSTRACT Introduction: We aim to compare the safety and effectiveness of the KangDuo (KD)-Surgical Robot-01 (KD-SR-01) system and the da Vinci (DV) system for robot-assisted radical nephroureterectomy (RARNU). Materials and Methods: This multicenter prospective randomized controlled trial was conducted between March 2022 and September 2023. Group 1 included 29 patients undergoing KD-RARNU. Group 2 included 29 patients undergoing DV-RARNU. Patient demographic and clinical characteristics, perioperative data, and follow-up outcomes were collected prospectively and compared between the two groups. Results: There were no significant differences in patient baseline demographic and preoperative characteristics between the two groups. The success rates in both groups were 100% without conversion to open or laparoscopic surgery or positive surgical margins. No significant difference was observed in docking time [242 (120-951) s vs 253 (62-498) s, P = 0.780], console time [137 (55-290) min vs 105 (62-220) min, P = 0.114], operative time [207 (121-460) min vs 185 (96-305) min, P = 0.091], EBL [50 (10-600) mL vs 50 (10-700) mL, P = 0.507], National Aeronautics and Space Administration Task Load Index scores, and postoperative serum creatinine levels between the two groups. None of the patients showed evidence of distant metastasis, local recurrence, or equipment-related adverse events during the four-week follow-up. One (3.4%) patient in Group 2 experienced postoperative enterovaginal and enterovesical fistulas (Clavien-Dindo grade III). Conclusions: The KD-SR-01 system is safe and effective for RARNU compared to the DV Si or Xi system. Further randomized controlled studies with larger sample sizes and longer durations are required.

Development of fully automated models for staging liver fibrosis using non-contrast MRI and artificial intelligence: a retrospective multicenter study.

Background: Accurate staging of liver fibrosis (LF) is essential for clinical management in chronic liver disease. While non-contrast MRI (NC-MRI) yields valuable information for liver assessment, its effectiveness in predicting LF remains underexplored. This study aimed to develop and validate artificial intelligence (AI)-powered models utilizing NC-MRI for staging LF. Methods: A total of 1726 patients from Shengjing Hospital of China Medical University, registered between October 2003 and October 2022, were retrospectively collected, and divided into development (n = 1208) and internal test (n = 518) cohorts. An external test cohort consisting of 337 individuals from six centers, registered between June 2015 and November 2022, were also included. All participants underwent NC-MRI (T1-weighted imaging, T1WI; and T2-fat-suppressed imaging, T2FS) and liver biopsies. Two classification models (CMs), named T1 and T2FS, were trained on respective image types using 3D contextual transformer networks and evaluated on both test cohorts. Additionally, three CMs-Clinic, Image, and Fusion-were developed using clinical features, T1 and T2FS scores, and their integration via logistic regression. Classification effectiveness of CMs was assessed using the area under the receiver operating characteristic curve (AUC). A comparison was conducted between the optimal models (OMs) with highest AUC and other methods (transient elastography, five serum biomarkers, and six radiologists). Findings: Fusion models (i.e., OM) yielded the highest AUC among the CMs, achieving AUCs of 0.810 for significant fibrosis, 0.881 for advanced fibrosis, and 0.918 for cirrhosis in the internal test cohort, and 0.808, 0.868, and 0.925, respectively, in the external test cohort. The OMs demonstrated superior performance in AUC, significantly surpassing transient elastography (only for staging ≥ F2 and ≥ F3 grades), serum biomarkers, and three junior radiologists for staging LF. Radiologists, with the aid of the OMs, can achieve a higher AUC in LF assessment. Interpretation: AI-powered models utilizing NC-MRI, including T1WI and T2FS, accurately stage LF. Funding: National Natural Science Foundation of China (No. 82071885); General Program of the Liaoning Provincial Department of Education (LJKMZ20221160); Liaoning Province Science and Technology Joint Plan (2023JH2/101700127); the Leading Young Talent Program of Xingliao Yingcai in Liaoning Province (XLYC2203037).

An Integrated Nomogram Combining Deep Learning and Radiomics for Predicting Malignancy of Pulmonary Nodules Using CT-Derived Nodules and Adipose Tissue: A Multicenter Study.

BACKGROUND: Correctly distinguishing between benign and malignant pulmonary nodules can avoid unnecessary invasive procedures. This study aimed to construct a deep learning radiomics clinical nomogram (DLRCN) for predicting malignancy of pulmonary nodules. METHODS: One thousand and ninety-eight patients with 6-30 mm pulmonary nodules who received histopathologic diagnosis at 3 centers were included and divided into a primary cohort (PC), an internal test cohort (I-T), and two external test cohorts (E-T1, E-T2). The DLRCN was built by integrating adipose tissue radiomics features, intranodular and perinodular deep learning features, and clinical characteristics for diagnosing malignancy of pulmonary nodules. The least absolute shrinkage and selection operator (LASSO) was used for feature selection. The performance of DLRCN was assessed with respect to its calibration curve, area under the curve (AUC), and decision curve analysis (DCA). Furthermore, we compared it with three radiologists. The net reclassification improvement (NRI), integrated discrimination improvement (IDI), and subgroup analysis were also taken into account. RESULTS: The incorporation of adipose tissue radiomics features led to significant NRI and IDI (NRI = 1.028, p < 0.05, IDI = 0.137, p < 0.05). In the I-T, E-T1, and E-T2, the AUCs of DLRCN were 0.946 (95% CI: 0.936, 0.955), 0.948 (95% CI: 0.933, 0.963) and 0.962 (95% CI: 0.945, 0.979), The calibration curve revealed good predictive accuracy between the actual probability and predicted probability (p > 0.05). DCA showed that the DLRCN was clinically useful. Under equal specificity, the sensitivity of DLRCN increased by 8.6% compared to radiologist assessments. The subgroup analysis conducted on adipose tissue radiomics features further demonstrated their supplementary value in determining the malignancy of pulmonary nodules. CONCLUSION: The DLRCN demonstrated good performance in predicting the malignancy of pulmonary nodules, which was comparable to radiologist assessments. The adipose tissue radiomics features have notably enhanced the performance of DLRCN.

Sociodemographic, economic, and academic factors linked with resilience in university students during covid-19 pandemic: a Brazilian cross-sectional study.

BACKGROUND: Resilience is a crucial factor in students' mental health, playing an important role in their successful adaptation to the academic environment. However, there is a lack of understanding about resilience and its associated factors in students from different undergraduate courses. This study aimed to describe the resilience profile of undergraduate students from various courses in Brazil and identify sociodemographic, economic, and academic factors associated with resilience. METHODS: This study has data from a cross-sectional multicenter study involving undergraduate students from eight Federal Institutions of Higher Education in Minas Gerais, Brazil. The dependent variable was resilience, measured using the Connor-Davidson Resilience Scale (CD-RISC) 10-item version, with sociodemographic, economic, and academic factors considered independent variables. Data was collected virtually via a self-administered questionnaire between October 2021 and February 2022 (during the covid-19 pandemic). Independent samples t-tests and ANOVAs were conducted to compare resilience scores between independent variables, and Tukey's post-hoc test was performed when necessary. Multiple linear regression was performed to create three models. RESULTS: 8,650 undergraduate students were included in this study. The average score on the resilience scale was 19.86 ± 8.15, with a normal distribution. The respondents ranged from 18 to 71 years old, averaging 23.9 ± 6.33. Being female, not having a religious belief, having low per capita family income, having had a decrease in the family income, not being heterosexual, or having the head of the family with a low education level were the main factors associated, individually, with low resilience scores in the sociodemographic and economic multiple linear regression model constructed. Being from linguistics, letters and arts courses, being enrolled in fewer subjects, or being from UFMG were the main factors associated, individually, with low resilience scores in the academic multiple linear regression model constructed. CONCLUSIONS: The study's findings revealed that sociodemographic, economic, and academic variables were significantly associated with resilience scores in undergraduates from Minas Gerais during the covid-19 pandemic. These findings can help universities develop target strategies to promote students' resilience and reduce the risk of poor mental health among this population.

Institutional influence on length of stay in German forensic hospitals: a multilevel analysis of patients with schizophrenia spectrum disorders.

Introduction: Scientific studies have focused on patient-related characteristics as predictors of length of stay in forensic psychiatry. However, little attention has been paid to the specificities of forensic psychiatric settings. This study aims to test whether differences in forensic admissions transcend individual factors by comparing length of stay between different psychiatric units, controlling for hospital characteristics and patient characteristics. Methods: The dataset was derived from a forensic documentation system containing a wide range of information on forensic psychiatric patients. N = 594 patients with schizophrenia spectrum disorders discharged from 6 forensic hospitals in southern Germany were included in a linear mixed regression model. Linear mixed models were calculated, allowing for the simultaneous estimation of variance between patients and hospitals. Results: The final regression model explained 49% of the total variance. The only statistically significant patient-related predictors were age at admission, education and severity of the index offence. Hospital differences explained 41% (ICC) of the variance in length of stay without finding a significant hospital effect in the data. Discussion: Previous research has primarily analyzed predictors of length of stay in terms of individual patient characteristics. This work suggests that variables other than patient-related factors need to be considered when assessing the length of stay in forensic units. Further multi-center studies are needed to gain a better understanding of how forensic psychiatric hospitals and other institutional influences affect length of stay.

Development and Validation of a Novel Classification System and Prognostic Model for Open Traumatic Brain Injury: A Multicenter Retrospective Study.

INTRODUCTION: Open traumatic brain injury (OTBI) is associated with high mortality and morbidity; however, the classification of these injuries and the determination of patient prognosis remain uncertain, hindering the selection of optimal treatment strategies. This study aimed to develop and validate a novel OTBI classification system and a prognostic model for poor prognosis. METHODS: This retrospective study included patients with isolated OTBI who received treatment at three large medical centers in China between January 2020 and June 2022 as the training set. Data on patients with OTBI collected at the Fuzong Clinical Medical College of Fujian Medical University between July 2022 and June 2023 were used as the validation set. Clinical parameters, including clinical data at admission, radiological and laboratory findings, details of surgical methods, and prognosis were collected. Prognosis was assessed through a dichotomized Glasgow Outcome Scale (GOS). A novel OTBI classification was proposed, categorizing patients based on a combination of intracranial hematoma and midline shift observed on imaging, and logistic regression analyses were performed to identify risk factors associated with poor prognosis and to investigate the association between the novel OTBI classification and prognosis. Finally, a nomogram suitable for clinical application was established and validated. RESULTS: Multivariable logistic regression analysis identified OTBI classification type C (p < 0.001), a Glasgow Coma Scale score (GCS) ≤ 8 (p < 0.001), subarachnoid hemorrhage (SAH) (p = 0.004), subdural hematoma (SDH) (p = 0.011), and coagulopathy (p = 0.020) as independent risk factors for poor prognosis. The addition of the OTBI classification to a model containing all the other identified prognostic factors improved the predictive ability of the model (Z = 1.983; p = 0.047). In the validation set, the model achieved an area under the curve (AUC) of 0.917 [95% confidence interval (CI) = 0.864-0.970]. The calibration curve closely approximated the ideal curve, indicating strong predictive performance of the model. CONCLUSIONS: The implementation of our proposed OTBI classification system and its use alongside the other prognostic factors identified here may improve the prediction of patient prognosis and aid in the selection of the most suitable treatment strategies.

Effectiveness of CI as an alternative to ABI for hearing loss in patients with vestibular schwannomas: A multicenter study in Japan.

OBJECTIVE: NF2-related schwannomatosis (NF2) is characterized by bilateral vestibular schwannomas (VS), often causing severe damage to the bilateral auditory function. Auditory brainstem implantation (ABI) provides hearing-impaired patients with an opportunity to reacquire auditory sensation through electrical stimulation of auditory neurons in the cochlear nucleus. However, ABI is not covered by public health insurance in Japan, leading to a large difference in financial burden compared to cochlear implantation (CI). The aim of the present study was to demonstrate the effectiveness of CI as an alternative to ABI for hearing reacquisition in patients with profound hearing loss caused by VS. METHODS: To investigate the current situation of ABI and CI for hearing reconstruction in VS patients, we conducted a questionnaire survey of 102 facilities in Japan. Based on the responses to the questionnaire, a multicenter research group consisting of otolaryngologists and neurosurgeons was established. We collected detailed data on patients with VS who underwent ABI (n = 7, all NF2) and CI (n = 14 [nine NF2, and five non-NF2]). RESULTS: Some sense of hearing was obtained in all patients but one with CI indicating the efficacy of CI and ABI for profound hearing loss caused by VS. The mean hearing levels were 45.4 dB HL in the ABI patients and 32.7 dB HL in the CI patients, indicating that CI was effective as an alternative to ABI. CONCLUSION: The results of the present study suggest the effectiveness of CI as an alternative to ABI for hearing reacquisition in patients with profound hearing loss caused by VS.

Experiences in robotic colorectal surgery: comprehensive insights from a multi-center analysis using the Senhance Robotic System.

Robotic-assisted surgery has revolutionised minimally invasive approaches, particularly in colorectal surgery. While many single-center studies on colorectal surgeries exist in present literature, including experiences with Senhance® Robotic Systems, comprehensive multi-center studies are lacking. This study, conducted through the TransEnterix European Patient Registry ("TRUST"), aims to assess the safety and feasibility in this context. The present study explored procedural times, complications, robotic malfunction and limitations, adverse events and pain management outcomes for colorectal procedures, including sigmoid resection, right hemicolectomy and rectal surgery collected in two European centers. Data from 355 colorectal surgeries showed that the median duration of surgery was 147.2 min (IQR: 124.3-183.0), the docking time was reported with a median of 3.4 min (IQR: 2.0-5.4) and the console time was found at a mean of 84.4 min (SD: 33.6). Despite minimal blood loss, pain scores, and robotic malfunction, 2.9% of the cases (10 instances) required conversions to either an open or laparoscopic approach. Further, most robotic limitations were attributed to limited motion (18.9%, 67 cases) and collisions (11.5%, 41 cases). Adverse events (24 cases, 6.8%) were effectively managed, with 23 instances judged completely unrelated to the robotic system. This study underscores the positive outcomes and safety profile of Senhance® Robotic Systems in colorectal surgery, contributing valuable insights for future research and clinical practice.

Critical windows for exposure to chemical composition of ambient particulate matter and human semen quality decline.

BACKGROUND: Critical windows for exposure to chemical components of particulate matter (PM <2.5 µm in diameter [PM2.5]) associated with the human semen quality decline remain unclear. OBJECTIVES: To address this gap, we developed a new analytical framework by integrating a Linear Mixed Model (LMM) with subject- and center-specific intercepts and a Distributed Lag Model (DLM) to fully account for correlations between finely vulnerable exposure windows based on complete profile of the spermatogenesis cycle. METHODS: We constructed a multicenter cohort involving 33,234 sperm donors with 78,952 semen samples covering 6 representative regions across China from 2014 to 2020 to investigate the week-scale critical windows for the exposure. Daily exposure to PM2.5 chemical components of donors was derived from grid data based on 1-km spatial resolution surface measurements. RESULTS: Decreased sperm count was significantly associated with NO3- and SO42- at 9-10 weeks (e.g., ß: -0.05 %, 95%CI: [-0.10 %, -0.00 %] at the 9th week) and 0-2 weeks (e.g., ß: -0.66 %, 95%CI: [-1.24 %, -0.07 %] at the 1st week), respectively. Critical windows of progressive motility decline were 0-10 weeks for BC (e.g., ß: -0.07 %, 95%CI: [-0.11 %, -0.03 %] at the 5th week), Cl- at 1-4 weeks (e.g., ß: -2.21 %, 95%CI: [-3.77 %, -0.66 %] at the 2nd week), 0-6 weeks and 9-10 weeks for NO3- (e.g., ß: -0.05 %, 95%CI: [-0.09 %, -0.01 %] at the 4th week), 1-3 weeks and the 8th week for NH4+ (e.g., ß: -0.06 %, 95%CI: [-0.11 %, -0.01 %] at the 2nd week). Total motility is significantly negatively associated with BC at entire windows, Cl- at 0-3 weeks, the 5th week and 9-10 weeks. CONCLUSIONS: There are week-scale vulnerable windows of exposure to PM2.5 chemical components for human semen quality. This highlights the need for more targeted pollution control strategies addressing PM2.5 and its chemical components.

Development and Validation of a Computed Tomography-Based Model for Noninvasive Prediction of the T Stage in Gastric Cancer: Multicenter Retrospective Study.

BACKGROUND: As part of the TNM (tumor-node-metastasis) staging system, T staging based on tumor depth is crucial for developing treatment plans. Previous studies have constructed a deep learning model based on computed tomographic (CT) radiomic signatures to predict the number of lymph node metastases and survival in patients with resected gastric cancer (GC). However, few studies have reported the combination of deep learning and radiomics in predicting T staging in GC. OBJECTIVE: This study aimed to develop a CT-based model for automatic prediction of the T stage of GC via radiomics and deep learning. METHODS: A total of 771 GC patients from 3 centers were retrospectively enrolled and divided into training, validation, and testing cohorts. Patients with GC were classified into mild (stage T1 and T2), moderate (stage T3), and severe (stage T4) groups. Three predictive models based on the labeled CT images were constructed using the radiomics features (radiomics model), deep features (deep learning model), and a combination of both (hybrid model). RESULTS: The overall classification accuracy of the radiomics model was 64.3% in the internal testing data set. The deep learning model and hybrid model showed better performance than the radiomics model, with overall classification accuracies of 75.7% (P=.04) and 81.4% (P=.001), respectively. On the subtasks of binary classification of tumor severity, the areas under the curve of the radiomics, deep learning, and hybrid models were 0.875, 0.866, and 0.886 in the internal testing data set and 0.820, 0.818, and 0.972 in the external testing data set, respectively, for differentiating mild (stage T1~T2) from nonmild (stage T3~T4) patients, and were 0.815, 0.892, and 0.894 in the internal testing data set and 0.685, 0.808, and 0.897 in the external testing data set, respectively, for differentiating nonsevere (stage T1~T3) from severe (stage T4) patients. CONCLUSIONS: The hybrid model integrating radiomics features and deep features showed favorable performance in diagnosing the pathological stage of GC.

The IMproving Preclinical Assessment of Cardioprotective Therapies (IMPACT): multicenter pig study on the effect of ischemic preconditioning.

Numerous cardioprotective interventions have been reported to reduce myocardial infarct size (IS) in pre-clinical studies. However, their translation for the benefit of patients with acute myocardial infarction (AMI) has been largely disappointing. One reason for the lack of translation is the lack of rigor and reproducibility in pre-clinical studies. To address this, we have established the European IMproving Preclinical Assessment of Cardioprotective Therapies (IMPACT) pig AMI network with centralized randomization and blinded core laboratory IS analysis and validated the network with ischemic preconditioning (IPC) as a positive control. Ten sites in the COST Innovators Grant (IG16225) network participated in the IMPACT network. Three sites were excluded from the final analysis through quality control of infarct images and use of pre-defined exclusion criteria. Using a centrally generated randomization list, pigs were allocated to myocardial ischemia/reperfusion (I/R, N = 5/site) or IPC + I/R (N = 5/site). The primary endpoint was IS [% area-at-risk (AAR)], as quantified by triphenyl-tetrazolium-chloride (TTC) staining in a centralized, blinded core laboratory (5 sites), or IS [% left-ventricular mass (LV)], as quantified by a centralized, blinded cardiac magnetic resonance (CMR) core laboratory (2 sites). In pooled analyses, IPC significantly reduced IS when compared to I/R (57 ± 14 versus 32 ± 19 [%AAR] N = 25 pigs/group; p < 0.001; 25 ± 13 versus 14 ± 8 [%LV]; N = 10 pigs/group; p = 0.021). In site-specific analyses, in 4 of the 5 sites, IS was significantly reduced by IPC when compared to I/R when quantified by TTC and in 1 of 2 sites when quantified by CMR. A pig AMI multicenter European network with centralized randomization and core blinded IS analysis was established and validated with the aim to improve the reproducibility of cardioprotective interventions in pre-clinical studies and the translation of cardioprotection for patient benefit.

Clinical evaluation of direct composite versus zirconia resin-bonded fixed dental prostheses for a single missing anterior tooth: A short-term multicenter retrospective study.

OBJECTIVES: This study aimed to compare the outcome of a simplified direct composite resin-bonded fixed dental prostheses without reinforcing fibers (CR-RBFDP) and resin-bonded fixed dental prostheses using zirconia (Zr-RBFDP). METHODS: The clinical records of five private practice dental clinics and one university hospital were analyzed. Failure was defined as a RBFDP that was removed or remade for any reason. Survival analyses were performed using log-rank tests. RESULTS: A total of 45 patients (CR-RBFDP, n = 17; Zr-RBFDP, n = 28) were followed up for 3 years. Among the CR-RBFDP cases, 1 case of framework fracture and 2 cases of discoloration occurred, whereas among the Zr-RBFDP cases, 1 case of debonding occurred. The mean duration of observation was 21.9 months. The 3-year survival rate was 92.3 % for CR-RBFDP and 91.7 % for Zr-RBFDP. Log-rank test showed no significant difference (p = 0.78). CONCLUSIONS: Within the limitations of this short-term retrospective study, the survival rate of CR-RBFDP was not significantly different from that of Zr-RBFDP. Contrary to concerns regarding material strength, CR-RBFDP showed reliable results. This direct composite restoration has the advantages of being less invasive and being completed in a single visit. CLINICAL SIGNIFICANCE: Despite differences in material strength, CR-RBFDPs without fiber reinforcement showed reliable short-term clinical results. This direct composite restoration has the advantage of being less invasive and can be restored in a single visit.

Factors prolonging antibiotic duration and impact of early surgery in thoracolumbar pyogenic spondylitis treated with minimally invasive posterior fixation.

PURPOSE: A standard 6-12-week course of antibiotics is recommended for pyogenic spondylitis. Recent evidence supports early minimally invasive posterior fixation surgery; however, its effect on antibiotic treatment duration is unclear. This study aims to identify factors associated with prolonged antibiotic treatment in thoracolumbar pyogenic spondylitis patients resistant to conservative treatment and assess whether early surgery can reduce treatment duration. METHODS: We retrospectively reviewed 74 patients with thoracolumbar pyogenic spondylitis undergoing minimally invasive posterior fixation at nine facilities. Patients were grouped based on antibiotic duration (≥ 6 or < 6 weeks) and timing of surgery (≤ 3 weeks or > 3 weeks of starting antibiotics). Univariable and multivariable logistic regression analyses were used to identify factors associated with prolonged antibiotic treatment and study the outcomes of patients undergoing early surgery. RESULTS: Forty-nine patients (66%) required prolonged antibiotic treatment. The presence of an iliopsoas abscess (p = 0.0006) and elevated C-reactive protein (CRP) levels (≥ 10 mg/dL, p = 0.015) were independently associated with prolonged antibiotic treatment. Early surgery significantly reduced total antibiotic duration (5.3 weeks vs. 9.9 weeks, p < 0.0001) without increasing the incidence of postoperative infection recurrences and unplanned additional surgeries. Despite factors associated with prolonged antibiotic treatment, early surgery consistently shortened the treatment duration compared to late surgery. CONCLUSIONS: Early surgery (within three weeks) with minimally invasive posterior fixation for thoracolumbar pyogenic spondylitis is associated with reduced antibiotic duration and overall treatment duration regardless of the presence of prolonging factors like iliopsoas abscess and elevated CRP levels.

Occurrence and predictors of laboratory abnormalities during outpatient parenteral antimicrobial therapy - A multicenter cohort study to inform laboratory test monitoring.

OBJECTIVES: Evidence on the optimal frequency of laboratory testing during outpatient parenteral antimicrobial therapy (OPAT) is lacking. Therefore, we investigated how often and when laboratory abnormalities occur during OPAT and which factors are associated with these abnormalities. METHODS: We performed a multicenter cohort study in four Dutch hospitals among adult patients receiving OPAT and collected routinely obtained laboratory test results. Incidence and incidence rates were calculated for various laboratory abnormalities. Survival analysis was performed to visualize the time to the first occurrence of laboratory abnormalities and Poisson regression analysis to compare the number of abnormalities in the first and second 30 OPAT days among patients receiving OPAT for ≥60 days. Predictors were identified using a multivariable Cox proportional hazard regression model. RESULTS: 45.1% of 1152 included patients developed laboratory abnormalities, but only 2% led to OPAT discontinuation. Hepatotoxicity was most common (33.9 events/1000 OPAT days), with a time-dependent decrease in the occurrence of the first hepatotoxic event, while hypokalemia was rare (1.7 events/1000 OPAT days). In the subgroup of patients receiving ≥60 days of OPAT, nephrotoxicity was more common in days 31-60. We observed partly toxicity-specific associations between antibiotic type, concomitant medication, baseline laboratory values, patient characteristics, and the occurrence of laboratory abnormalities. CONCLUSIONS: While laboratory abnormalities are frequently observed during OPAT, they rarely lead to discontinuation of OPAT. Specific patient, treatment and laboratory characteristics were associated with the occurrence of laboratory abnormalities. Based on our results, we recommend a more personalized laboratory monitoring policy with less blood sampling.

Efficacy and safety of linaclotide in treatment-resistant chronic constipation: A multicenter, open-label study.

BACKGROUND: This study aimed to evaluate the efficacy and safety of linaclotide in patients with chronic constipation (CC) or irritable bowel syndrome with constipation (IBS-C) who did not respond to treatment with magnesium oxide (MgO). METHODS: This study was designed as a multicenter, open-label, single-arm, exploratory study. Patients with CC or IBS-C who took MgO and those meeting the medication initiation criteria were administered linaclotide at a daily dosage of 500 µg for 12 weeks. The primary endpoint was a change in the Japanese version of the Patient Assessment of Constipation Quality of Life (JPAC-QOL) score from baseline, which was evaluated by using a paired t-test. KEY RESULTS: The patients' mean age (± standard deviation) was 67.6 ± 13.82 years. The full analysis set included 61 patients. The JPAC-QOL total score was 1.60 at baseline and 0.70 at 12 weeks, with a significant mean change of -0.89 ± 0.721 (p < 0.001). Several secondary endpoints also showed improvement. The frequency of spontaneous bowel movement (SBM) and complete SBM increased by 2.70 ± 7.254 (p < 0.01) and 2.81 ± 5.254 times, respectively (p < 0.001). The Bristol Stool Form Scale, abdominal bloating severity, and straining severity scores improved by 1.33 ± 1.274 (p < 0.001), -0.16 ± 0.563 (p < 0.05), and -0.46 ± 0.795 (p < 0.001) points, respectively. The safety analysis set included 65 patients, 7 of whom had diarrhea, which improved with dose reduction and drug withdrawal. CONCLUSION & INFERENCES: The study was conducted in an older adult population, similar to real clinical practice. Linaclotide may be an option for treating CC that shows an inadequate response to conventional therapy.

A retrospective multicenter study of WHO 2021 classification-diagnosed solitary fibrous tumor of the CNS in a population from Lombardy, Italy.

In this retrospective, multicenter study, we collected patients with solitary fibrous tumor-SFT-of the CNS followed in eight hospitals in Lombardia from 2004 to 2019, revising the diagnosis according to the WHO 2021 classification. Clinical data were analyzed at diagnosis and during follow-up. Overall, 57 patients were enrolled, of whom 52.6% female. Median age was 54, 91% had an intracranial tumor and 9% a spinal location. 49% patients had grade 1, 31.5% grade 2 and 19% grade 3 tumor. After a median follow-up of 84 months, 49% of the patients had progressed and 8.7% had died. Gross tumor resection was obtained in 70%, subtotal in 26.3%, partial in 1.7% and biopsy in 1.7%. 15.7% (n = 9) of patients developed extra-CNS metastases, mainly involving bone, lung and liver, six of these were grade 3 and 3 were grade 2 at first diagnosis. 14 patients (24.5%) underwent radiation therapy, 3 chemotherapy and one received liver transplant. The 14 radiation-treated patients included all grade 3 and 3 grade 2 with partial or subtotal resection. Only tumor grade had a prognostically significant impact on PFS at univariate analysis, while age had not. All but one case displayed nuclear expression for STAT6, the remaining case showed diffuse expression of CD34. Whereas grade 3 was confirmed as a prognostically relevant factor, partially overlapping behaviours were detected in patients usually considered at low (all grade 1 and grade 2 with gross total resection) versus moderate risk (grade 2 with biopsy or non-gross total resection).

The effect of subjective postural vertical on forward flexed posture in Parkinson's disease.

BACKGROUND: We developed a novel method to measure the angle of subjective postural vertical (SPV) and showed that the SPV may be related to the exacerbation of the forward flexed posture. OBJECTIVES: The present study prospectively tested the effects of the subjective postural vertical on the exacerbation of the forward flexion of trunk (FFT) through long-term observation of Parkinson's disease patients. METHODS: Evaluation of the posture included measuring FFT, the angle of lateral flexion of trunk, and the angle at the position that the patient subjectively perceived as the vertical position at a stationary upright position immediately after standing up at the time of initial observation, 6 months later, and 1 year later. RESULTS: The SPV angles worsened significantly at 6 months and 1 year compared to the first measurements (9.3 ± 6.7° vs. 10.8 ± 8.2° and 10.6 ± 7.8°, P < 0.05), and the FFT angles worsened significantly at one year compared to the first measurements (11.1 ± 8.1° vs. 12.2 ± 8.8°, P = 0.004). Furthermore, using a hierarchical multiple regression model, the difference in SPV from the first visit to the first half year was considered a factor contributing to annual FFT change (P = 0.002). CONCLUSIONS: This longitudinal study of a large number of cases suggested that changes in SPV may precede changes in FFT.

Deep learning based automatic detection and dipole estimation of epileptic discharges in MEG: a multi-center study.

Magnetoencephalography (MEG) provides crucial information in diagnosing focal epilepsy. However, dipole estimation, a commonly used analysis method for MEG, can be time-consuming since it necessitates neurophysiologists to manually identify epileptic spikes. To reduce this burden, we developed the automatic detection of spikes using deep learning in single center. In this study, we performed a multi-center study using six MEG centers to improve the performance of the automated detection of neuromagnetically recorded epileptic spikes, which we previously developed using deep learning. Data from four centers were used for training and evaluation (internal data), and the remaining two centers were used for evaluation only (external data). We used a five-fold subject-wise cross-validation technique to train and evaluate the models. A comparison showed that the multi-center model outperformed the single-center model in terms of performance. The multi-center model achieved an average ROC-AUC of 0.9929 and 0.9426 for the internal and external data, respectively. The median distance between the neurophysiologist-analyzed and automatically analyzed dipoles was 4.36 and 7.23 mm for the multi-center model for internal and external data, respectively, indicating accurate detection of epileptic spikes. By training data from multiple centers, automated analysis can improve spike detection and reduce the analysis workload for neurophysiologists. This study suggests that the multi-center model has the potential to detect spikes within 1 cm of a neurophysiologist's analysis. This multi-center model can significantly reduce the number of hours required by neurophysiologists to detect spikes.

Comprehensive combined analysis of physician-initiated phase II and III clinical trials on a cultured human corneal endothelial cell product for treating bullous keratopathy.

To evaluate the efficacy and safety of a cultured human corneal endothelial cell (cHCEC) product in eyes with bullous keratopathy (BK). Combined analysis of multicenter phase II and III clinical trials. This analysis involved 15 BK eyes in the phase II trial and 12 BK eyes in the phase III trial that underwent cHCEC transplant therapy. Safety was assessed in all the cases. Efficacy was assessed in 17 cases with exclusion of the low- and medium-dose groups in the phase II trial. The primary endpoint was a corneal endothelial cell density of 1000 cells/mm2 or more at 24 weeks post-transplant, which was attained in 94.1% of the eyes (16 of 17), with a 95% CI of 71.3-99.9%. Additionally, 82.4% of the eyes (14 of 17) met the secondary endpoint of reduction in corneal thickness to less than 630 µm without corneal epithelial edema within the same time frame, with a 95% CI of 56.6-96.2%. The mean decrease in corneal thickness from baseline to 24 weeks post-transplant was -187.4 µm (95% CI, -240.2 µm to -134.5 µm). Furthermore, all the eyes exhibited improvement in best-corrected visual acuity from baseline to 24 weeks post-transplant (95% CI, 80.5-100.0%). By 24 weeks post-transplant, 88.9% of the patients (24 of 27) had experienced adverse events, which were mostly local, mild, and transient. The cHCEC product of this study reconstitutes the corneal endothelial layer with high cellular density and restores corneal thickness and improves visual acuity.