Background The aim of this study was to evaluate the effectiveness and safety of different treatment strategies for endogenic caesarean scar pregnancy (CSP) patients. Methods According to Vial’s standard, we defined endogenic-type CSP as (1) the gestational sac growing towards the uterine cavity and (2) a greater than 0.3 cm thickness of myometrial tissue at the caesarean scar. A total of 447 endogenic CSP patients out of 527 patients from 4 medical centres in China were enrolled in this study. A total of 120 patients were treated with methotrexate (MTX) followed by surgery, 106 received ultrasound-guided curettage directly and 221 received curettage combined with hysteroscopy. The clinical information and clinical outcomes of these patients were reviewed. Successful treatment was defined as (1) no additional treatment needed, (2) no retained mass of conception and (3) serum β subunit of human chorionic gonadotropin (β-hCG) level returning to a normal level within 4 weeks. The success rate was analysed based on these factors. Result Among 447 patients, no significant difference was observed in baseline characteristics between groups except for foetal heartbeat. The success rate was significantly different (p<0.001) among the three groups. The highest success rate of 95.9% was noted in the hysteroscopy group, and the lowest success rate of 84.0% was noted in the curettage group. In addition, the MTX group reported the longest hospital stay and highest expenses, but the curettage group showed the shortest and lowest expenses, respectively. Nevertheless, no difference in blood loss was observed between the groups. Conclusion The combination of curettage and hysteroscopy represents the most effective strategy. Pretreatment with MTX did not result in better clinical outcomes. Ultrasound-guided curettage directly should not be considered a first-line treatment choice for endogenic CSP patients.
IntroductionThe effectiveness of superficial cervical plexus block (SCPB) at decreasing opioid use and improving hemodynamic stability during suboccipital retrosigmoid craniotomy has not been established. The aim of this study is to evaluate the analgesic effect of preoperative ultrasound-guided SCPB for craniotomy via a suboccipital retrosigmoid approach.MethodsThis was a prospective, single-center, randomized, double-blind, parallel-group controlled trial. One hundred and six adult patients undergoing suboccipital retrosigmoid craniotomy were randomly allocated into either the SCPB group (n=53) to receive 10 mL of 0.5% ropivacaine or the control group (n=53) to receive 0.9% normal saline injected into the superficial layer of prevertebral fascia guided by ultrasound. The primary outcome was the cumulative consumption of sufentanil with patient-controlled intravenous analgesia (PCIA) within 24 hours. Secondary outcomes included the overall perioperative consumption of opioids, the area under the curve of the pain score from 1 hour to 48 hours (AUC1–48), intraoperative hemodynamic parameters, and anesthesia depth.ResultsThe mean PCIA pump cumulative consumption of sufentanil in the first 24 hour postoperative period was significantly lowered by SCPB (5.0 µg vs 9.8 µg, 95% CI: −8.0 to –2.4; p=0.001). The total perioperative consumption of sufentanil (45.0 µg vs 54.5 µg, 95% CI: –14.8 to –4.1; p=0.001) was also significantly decreased by SCPB. The incidence of severe pain within 24 hours was decreased by SCPB (7.5% vs 26.4%, p=0.01). SCPB significantly decreased the AUC1–48 of the pain score. Intraoperative hemodynamic parameters and anesthesia depth were similar between groups (p>0.05).DiscussionSCPB provides effective analgesia in patients undergoing craniotomy and tumor resection via suboccipital retrosigmoid approach. SCPB demonstrates an opioid-sparing effect and allows for the maintenance hemodynamic stability at an appropriate depth of anesthesia.Trial registration numberNCT04036812.
Background: The coronavirus disease (COVID-19) pandemic is currently a major challenge for health care systems around the world. For a time-sensitive emergency such as acute ischemic stroke (AIS), streamlined workflow times are essential to ensure good clinical outcomes. Methods: The aim of this single-center, retrospective, observational study was to describe changes in stroke workflow patterns and clinical care during the COVID-19 pandemic. Data from AIS patients undergoing emergent endovascular treatment (EVT) between 23 January and 8 April 2020 were retrospectively collected and compared with data from patients admitted during a similar period in 2019. The primary outcome was difference in time from symptom onset to recanalization. Secondary outcomes included workflow times, clinical management, discharge outcomes, and health-economic data. Results: In all, 21 AIS patients were admitted for emergent EVT during the 77-day study period, compared with 42 cases in 2019. Median time from symptom onset to recanalization was 132 minutes longer during the pandemic compared with the previous year (672 vs. 540 min, P =0.049). Patients admitted during the pandemic had a higher likelihood of endotracheal intubation (84.6% vs. 42.4%, P <0.05) and a higher incidence of delayed extubation after EVT (69.2% vs. 45.5%, P <0.05). National Institutes of Health Stroke Scale at hospital discharge was similar in the 2 cohorts, whereas neurointensive care unit stay was longer in patients admitted during the pandemic (10 vs. 7 days, P =0.013) and hospitalization costs were higher (123.9 vs. 95.2 thousand Chinese Yuan, P =0.052). Conclusion: Disruptions to medical services during the COVID-19 pandemic has particularly impacted AIS patients undergoing emergent EVT, resulting in increased workflow times. A structured and multidisciplinary protocol should be implemented to minimize treatment delays and maximize patient outcomes.
IntroductionPostoperative delirium (POD) is a common complication. The incidence of POD is about 25% in non-cardiac surgery and ranges from 10% to 30% in neurological procedures. A lot of trials show that dexmedetomidine might help to reduce the incidence of delirium in patients undergoing non-cardiac surgery. However, the impact of dexmedetomidine on POD for patients undergoing craniotomy and tumour resections remains unclear.Methods and analysisThe study is a prospective, single-centre, randomised, double-blinded, paralleled-group controlled trial. Patients undergoing elective frontotemporal tumour resections will be randomly assigned to the dexmedetomidine group and the control group. After endotracheal intubation, patients in the dexmedetomidine group will be administered with a loading dose of dexmedetomidine 0.6 µg/kg in 10 min followed by continuous infusion at a rate of 0.4 µg/kg/hour until the start of dural closure. In the control group, patients will receive the identical volume of normal saline in the same setting. The primary outcome will be the cumulative incidence of POD within 5 days. The delirium assessment will be performed by using the confusion assessment method in the first 5 consecutive days after surgery. Secondary outcomes include the pain severity assessed by Numerical Rating Scale pain score, quality of postoperative sleep assessed by the Richards Campbell sleep questionnaire and postoperative quality of recovery from anaesthesia by the Postoperative Quality Recovery Scale.Ethics and disseminationThe protocol (V.1.0, 10 November 2020) has been approved by the Ethics Review Committee of the Chinese Clinical Trial Registry (number ChiECRCT-20200436). The findings of the study will be disseminated in a peer-reviewed journal and at a scientific conference.Trial registration numberNCT04674241.
Background. Cervical cancer ranks as the 4th most common female cancer worldwide. Early stage cervical cancer patients can be treated with operation, but clinical staging system is not a good predictor of patients’ survival. We aimed to develop a novel prognostic model to predict the prognosis for operable cervical cancer patients with better accuracy than clinical staging system. Methods. A total of 13,952 operable cervical cancer patients were retrospectively enrolled in this study. The whole dataset was randomly split into a training set ( n = 9,068 , 65%), validation set ( n = 2,442 , 17.5%), and testing set ( n = 2,442 , 17.5%). Cox proportional hazard (CPH) model and random survival forest (RSF) model were used as baseline models for the prediction of overall survival (OS). Then, a deep survival learning model (DSLM) was developed for OS prediction. Finally, a novel prognostic model was explored based on this DSLM. Results. The C-indexes for the CPH and RSF model were 0.731 and 0.753, respectively. DSLM, which had four layers that had 50 neurons in each layer, achieved a C-index of 0.782 in the validation set and a C-index of 0.758 in the testing set. The novel prognostic model based on DSLM showed better performances than the conventional clinical staging system (area under receiver operating curves were 0.826 and 0.689, respectively). Personalized survival curves for individual patient using this novel model also showed notably different survival slopes. Conclusions. Our study developed a novel, practical, personalized prognostic model for operable cervical cancer patients. This novel prognostic model may have the potential to provide a more prognostic information to oncologists.
Introduction: Ubiquitination is involved in many biological processes and its predictive value for prognosis in cervical cancer is still unclear.Methods: To further explore the predictive value of the ubiquitination-related genes we obtained URGs from the Ubiquitin and Ubiquitin-like Conjugation Database, analyzed datasets from The Cancer Genome Atlas and Gene Expression Omnibus databases, and then selected differentially expressed ubiquitination-related genes between normal and cancer tissues. Then, DURGs significantly associated with overall survival were selected through univariate Cox regression. Machine learning was further used to select the DURGs. Then, we constructed and validated a reliable prognostic gene signature by multivariate analysis. In addition, we predicted the substrate proteins of the signature genes and did a functional analysis to further understand the molecular biology mechanisms. The study provided new guidelines for evaluating cervical cancer prognosis and also suggested new directions for drug development.Results: By analyzing 1,390 URGs in GEO and TCGA databases, we obtained 175 DURGs. Our results showed 19 DURGs were related to prognosis. Finally, eight DURGs were identified via machine learning to construct the first ubiquitination prognostic gene signature. Patients were stratified into high-risk and low-risk groups and the prognosis was worse in the high-risk group. In addition, these gene protein levels were mostly consistent with their transcript level. According to the functional analysis of substrate proteins, the signature genes may be involved in cancer development through the transcription factor activity and the classical P53 pathway ubiquitination-related signaling pathways. Additionally, 71 small molecular compounds were identified as potential drugs.Conclusion: We systematically studied the influence of ubiquitination-related genes on prognosis in cervical cancer, established a prognostic model through a machine learning algorithm, and verified it. Also, our study provides a new treatment strategy for cervical cancer.
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