Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

OBJECTIVE: To investigate the current status of early pain and agitation management in critically ill patients in Guizhou Province. METHODS: A retrospective study was performed using data collected from a quality control activity conducted between April and June 2021 in non-provincial public hospitals with general intensive care unit (ICU) in Guizhou Province. Hospital-level data included hospital name and grade, ICU staffing, and number of ICU beds. Patient-level data included characteristics of patients treated in the general ICU on the day of the survey (e.g., age, sex, primary diagnosis), as well as pain and agitation assessments and the types of analgesic and sedative medications administered within 24 hours of ICU admission. RESULTS: A total of 947 critically ill ICU patients from 145 hospitals were included, among which 104 were secondary-level hospitals and 41 were tertiary-level hospitals. Within 24 hours of ICU admission, 312 (32.9%) critically ill patients received pain assessments, and 277 (29.3%) received agitation assessments. Among the pain assessment tools, the critical care pain observation tool (CPOT) was used in 44.2% (138/312) of critically ill ICU patients, with a significantly higher usage rate in tertiary hospitals compared to secondary hospitals [52.3% (69/132) vs. 38.3% (69/180), P < 0.05]. The Richmond agitation-sedation scale (RASS) was used in 93.8% (260/277) of critically ill ICU patients for agitation assessment, with no significant difference between hospital levels. Among the 947 critically ill patients, 592 (62.5%) received intravenous analgesics within 24 hours, with remifentanil being the most commonly used [42.9% (254/592)]; 510 (53.9%) received intravenous sedatives, with midazolam being the most frequently used [60.8% (310/510)]. Mechanical ventilation data were available for 932 critically ill patients, of whom 579 (62.1%) received mechanical ventilation and 353 (37.9%) did not. Compared with non-ventilated patients, ventilated patients had significantly higher rates of analgesic and sedative use [analgesics: 77.9% (451/579) vs. 38.8% (137/353); sedatives: 71.8% (416/579) vs. 25.8% (91/353); both P < 0.05]. In terms of analgesic selection, ventilated patients were more likely to receive strong opioids than non-ventilated patients [85.8% (95/137) vs. 69.3% (387/451), P < 0.05]. For sedatives, ventilated patients preferred midazolam [66.6% (277/416)], whereas non-ventilated patients more often received dexmedetomidine [45.1 (41/91)]. Blood pressure within 24 hours of ICU admission were available for 822 critically ill patients, of whom 245 (29.8%) had hypotension and 577 (70.2%) did not. Compared with non-hypotensive patients, hypotensive patients had significantly higher rates of analgesic and sedative use [analgesics: 74.7% (183/245) vs. 59.8% (345/577); sedatives: 65.7% (161/245) vs. 51.3% (296/577); both P < 0.05], but there was no significant difference in the choice of analgesic or sedative agents between the two groups. CONCLUSIONS The proportion of critically ill ICU patients in Guizhou Province who received standardized pain and agitation assessments was relatively low. The most commonly used assessment tools were CPOT and RASS, while remifentanil and midazolam were the most frequently used analgesic and sedative agents, respectively. Secondary-level hospitals had a lower rate of using standardized pain assessment tools compared to tertiary-level hospitals. Mechanical ventilation and hypotension were associated with the use of analgesic and sedative medications.
Humans ; Critical Illness ; Intensive Care Units ; Analgesics/therapeutic use* ; Hypnotics and Sedatives/therapeutic use* ; Retrospective Studies ; China ; Pain Measurement ; Pain Management ; Female ; Male ; Critical Care ; Middle Aged

OBJECTIVE: To explore the timing of weaning extracorporeal membrane oxygenation (ECMO) and analyze the risk factors that affect survival outcomes before weaning. METHODS: A retrospective case-control study was conducted. Patients who received ECMO treatment and were weaned according to physicians' orders at the Second Xiangya Hospital of Central South University from January 2020 to June 2024 were enrolled as the study subjects. The general information, underlying diseases, indications and processes of ECMO, vital signs and arterial blood gas analysis 1 hour before weaning test, and biochemical indicators 24 hours before weaning test were collected through the hospital electronic medical record system. The primary outcome measure was the hospital mortality. The variables with P < 0.1 in univariate analysis and correlation analysis were included into binary Logistic regression analysis to identify risk factors. A nomogram model was constructed to predict the risk of weaning death in patients with ECMO, and receiver operator characteristic curve (ROC curve) and calibration curve were drawn to evaluate the model. Decision curve analysis (DCA) was used to evaluate the clinical net benefit rate of the model. RESULTS: A total of 32 ECMO patients were included, among whom 10 received veno-arterial ECMO (VA-ECMO) and 22 received veno-venous ECMO (VV-ECMO). During the hospitalization period, 23 patients survived, while 9 died. The time from mechanical ventilation to ECMO activation in the death group was significantly longer than that in the survival group, and the time from ECMO cessation to discharge was significantly shorter than that in the survival group. The levels of diastolic blood pressure (DBP) and albumin (Alb) before weaning were significantly lower than those in the survival group, and the level of procalcitonin (PCT) was significantly higher than that in the survival group (all P < 0.05). Spearman correlation analysis showed that DBP, PCT, Alb, and thrombin time (TT) were correlated with the weaning outcomes of ECMO patients (r values were -0.450, 0.373, -0.376, -0.346, all P < 0.1). Binary Logistic regression analysis showed that the final indicators entering the regression equation included DBP [odds ratio (OR) = 0.864, 95% confidence interval (95%CI) was 0.756-0.982], PCT (OR = 1.157, 95%CI was 0.679-1.973), and TT (OR = 0.852, 95%CI was 0.693-1.049), and a nomogram model was constructed to predict the weaning outcomes of ECMO patients. ROC curve analysis showed that the area under the curve (AUC) of the nomogram model for predicting the weaning outcome of ECMO patients was 0.831, with a sensitivity of 77.8% and a specificity of 65.2%. Its predictive value was better than that of single indicators DBP, PCT, and TT (AUC of 0.787, 0.739, and 0.722, respectively). The calibration curve showed that the prediction probability of the model was in good consistency with the actual observed results, the Hosmer-Lemeshow goodness of fit test showed that, χ ² = 8.3521, P = 0.400, indicating that the model fits well. DCA showed that across risk threshold of 0-0.8, the net benefit rate was greater than 0, which was significantly better than that of single indicator. CONCLUSIONS The nomogram model constructed with DBP, PCT, and TT has certain predictive value for the weaning outcomes of ECMO patients and can be used as a screening indicator for ECMO weaning timing.
Humans ; Extracorporeal Membrane Oxygenation ; Retrospective Studies ; Risk Factors ; Case-Control Studies ; Hospital Mortality ; Male ; Female ; Nomograms ; Logistic Models ; ROC Curve ; Middle Aged ; Adult ; Ventilator Weaning ; Time Factors

OBJECTIVE: To identify the risk factors related to the timing of patients receiving extracorporeal membrane oxygenation (ECMO) initiation and construct a risk prediction model for ECMO initiation timing. METHODS: Patients who received ECMO admitted to the Second Xiangya Hospital of Central South University from January 2020 to January 2024 were retrospectively collected. The case data mainly included physiological and biochemical indicators 1 hour before ECMO initiation. According to the outcome of the patients, they were divided into survival group and death group. Univariate and multivariate Logistic regression analysis were used to analyze the predictors of mortality risk in patients with ECMO, and a nomogram prediction model was constructed. The discrimination, calibration accuracy, and goodness of the model were evaluated by the receiver operator characteristic curve (ROC curve), calibration curve, and the Hosmer-Lemeshow test, respectively. Decision curve analysis (DCA) evaluated the clinical net benefit rate of the model. RESULTS: A total of 81 ECMO patients were included, including 59 males and 22 females; age range from 16 to 61 years old, with a median age of 56.0 (39.5, 61.5) years old; 20 patients received veno-arterial (V-A) ECMO, and 61 patients received veno-venous (V-V) ECMO; 23 patients ultimately survived and 58 patients died. Univariate analysis showed that age, blood urea nitrogen, serum creatinine, D-dimer, arterial blood carbon dioxide partial pressure, and prothrombin time of the death group were all higher than those of the survival group, while albumin was slightly lower than that of the survival group. There was a statistically significant difference in the direct cause of ECMO initiation between the two groups. Multivariate Logistic regression analysis showed that age [odds ratio (OR) = 1.069, 95% confidence interval (95%CI) was 1.015-1.125, P = 0.012], direct cause of ECMO initiation [with heart failure as the reference, return of spontaneous circulation (ROSC) after cardiopulmonary support (OR = 30.672, 95%CI was 1.265-743.638, P = 0.035), novel coronavirus infection (OR = 8.666, 95%CI was 0.818-91.761, P = 0.073), other severe pneumonia (OR = 4.997, 95%CI was 0.558-44.765, P = 0.150)], pre-ECMO serum creatinine (OR = 1.008, 95%CI was 1.000-1.016, P = 0.044), prothrombin time (OR = 1.078, 95%CI was 0.948-1.226, P = 0.252), and D-dimer (OR = 1.135, 95%CI was 1.047-1.231, P = 0.002) were entered into the final regression equation. A nomogram prediction model was developed based on these five factors. The area under the ROC curve (AUC) of the model was 0.889 (95%CI was 0.819-0.959), higher than the AUC of the sequential organ failure assessment (SOFA; AUC = 0.604, 95%CI was 0.467-0.742). The calibration curve showed good consistency between the model predictions and the observed results. The Hosmer-Lemeshow goodness-of-fit test showed that χ ² = 4.668, P = 0.792. DCA analysis showed that when the risk threshold was 0-0.8, the net benefit rate was greater than 0, which was significantly better than that of SOFA score. CONCLUSIONS The risk prediction model for the timing of ECMO initiation, constructed using five factors (age, direct cause of ECMO initiation, thrombin time, serum creatinine, and D-dimer), demonstrated good discrimination and calibration. It can serve as a pre-initiation assessment tool to identify and predict post-initiation mortality risk in ECMO patients.
Humans ; Extracorporeal Membrane Oxygenation ; Middle Aged ; Male ; Female ; Retrospective Studies ; Adult ; Risk Factors ; Adolescent ; Young Adult ; Logistic Models ; Nomograms ; ROC Curve ; Time Factors ; Risk Assessment

Objective To evaluate the safety and efficacy of the Neuroform EZ self expanding stent for severe symptomatic intracranial atherosclerotic stenosis(sICAS).Methods Retrospectively enrolled consecutive patients with severe sICAS who underwent percutaneous transluminal angioplasty and stenting(PTAS)with a Neuroform EZ stent in the Department of Cerebrovascular Disease,Henan Provincial People's Hospital,from March 2020 to December 2022.Baseline demographic and clinical data were collected,including age,sex,hypertension,diabetes mellitus,coronary artery disease,dyslipidemia,hyperhomocysteinemia,transient ischemic attack(TIA)and ischemic stroke,smoking history,modified Rankin scale(mRS)score at admission,and National Institutes of Health stroke scale(NIHSS)score.Preoperative imaging data included target vessel(basilar artery,intracranial segment of the internal carotid artery,middle cerebral artery,and intracranial vertebral artery),lesion length,degree of stenosis,and vascular morphology according to the Mori classification(type A,lesion length＜5 mm with concentric or moderately eccentric stenosis;type B,lesion length＜10 mm with severely eccentric stenosis;type C,lesion length＞10 mm or arterial angulation＞90°).Technical success was defined as accurate delivery and deployment of the stent with complete coverage of the target lesion and immediate post deployment residual stenosis＜50%.Postoperative head CT was performed to detect intracranial hemorrhage.Periprocedural complications were recorded,including intracranial hemorrhage,arterial dissection,in stent thrombosis,and perforator occlusion occurring intraoperatively within 72 hours after the procedure.At one-month post-operation,patients were seen through outpatient follow-up for TIA,hemorrhagic or ischemic stroke,and all cause death.At 6 months after surgery,DSA or CT angiography(CTA)was performed to assess in stent restenosis(ISR,defined as＞50%stenosis within the stent or within5mm of its edges,or＞20%luminal loss).At 1 and 2 years postoperatively,ipsilateral ischemic stroke or TIA recurrence was assessed by outpatient visit or telephone follow up.Results A total of 76 patients with severe sICAS underwent PTAS with a Neuroform EZ stent(56 males,20 females,age 47-80 years,with a mean age of[61±10]years).(1)Within all patients enrolled,40 had middle cerebral artery,16 with basilar artery,6 with intracranial vertebral artery and 14 with intracranial internal carotid artery.The preprocedural lesion length was 2-15 mm,with a mean length of(6.2±2.5)mm,and stenosis severity was70%-99%,the mean severity was(83.2±6.9)%,with Mori type B being the most common type(57.9%[44/76]).(2)PTAS was successfully completed on all patients(technical success 100%).Pre dilation with a conventional balloon was performed in all cases(using balloon with diameter of 1.5-3.5mm,and stent with diameter of 2.5-4.5 mm and length of 15-30 mm).Immediate post procedural residual stenosis was(17.4±9.0)%,significantly lower than baseline(t=52.9,P＜0.05),with a mean difference of 65.8%(95%CI63.3%-68.3%).(3)Among all 76patients,one patient developed a flow limiting dissection post balloon angioplasty,which recovered after stent deployment.One patient with basilar artery stenosis experienced recurrent ischemic stroke at 5-day postoperatively,presenting with right sided weakness and coughing on liquids.Imaging showed an acute infarct in the left pons,considered perforator occlusion.The overall periprocedural complication rate was 2.6%(2/76).(4)No deaths occurred within 30 days after surgery.Sixty nine patients(90.8%)underwent 6 month imaging follow up with DSA(52 cases)or CTA(17 cases).ISR occurred in 12 patients(17.4%),including 6 asymptomatic and 6symptomatic cases.The ipsilateral ischemic stroke recurrence rate was 6.6%(5/76)at1 year and13.2%(10/76)at2years.Conclusions Neuroform EZstent assisted PTASappears safe and feasible for the treatment of severe sICAS.The long term effectiveness requires confirmation in large,multicenter,prospective studies.

The clinical detection of paroxysmal atrial fibrillation(PAF)remains challenging due to its transient and stochastic characteristics,and existing dynamic mode decomposition methods have limitations in modal redundancy reduction and feature extraction when processing single-channel noisy electrocardiogram(ECG)signals.Therefore,a signal analysis method based on high-order dynamic mode decomposition is proposed.It captures high-order correlations within ECG signals through tensor decomposition techniques and decomposes complex signals into physically interpretable dynamic modes.A stability evaluation framework for signal subsystem is established based on modal interaction relationships.By incorporating quantitative indicators including proportion of modes reflecting system instability,modal distribution entropy,and eigenvalue spectrum divergence,a feature discrimination model for PAF is developed.Experimental validation using the MIT-BIH atrial fibrillation database reveals statistically significant differences(P<0.05)in stability-related features between PAF episodes and normal sinus rhythms.The classification model based on support vector machine achieves an average recognition accuracy of 96.15%.These results demonstrate that the proposed method can effectively analyze nonlinear dynamic characteristics in noisy single-lead ECG signals,thereby establishing a novel quantitative analytical framework for early detection and accurate diagnosis of PAF.

Objective To investigate the incidence and types of patient-ventilator asynchrony(PVA)in mechanically ventilated patients within the intensive care unit(ICU),and to identify associated high-risk factors,thereby providing a basis for reducing PVA,enhancing mechanical ventilation efficiency,and refining ventilation strategies.Methods A prospective observational study was conducted among patients admitted to the general ICU of the Affiliated Hospital of Guizhou Medical University from October to December 2024 who were receiving mechanical ventilation.Inclusion criteria were as follows:age ≥18 years and mechanical ventilation duration ≥12 hours.Exclusion criteria included complete controlled mechanical ventilation,palliative care or do-not-resuscitate status,and lack of informed consent.Senior respiratory therapists performed daily bedside observations of ventilator waveforms for 10～15 minutes between 08:00 and 12:00.PVA was diagnosed based on pressure-time and flow-time waveforms,with the types of PVA being recorded.Demographic and clinical data,including age,sex,body mass index(BMI),primary diagnosis,comorbidities,APACHEⅡ score at ICU admission,blood gas analysis,ventila-tion mode and parameters,analgesia and sedation status,duration of mechanical ventilation,and length of ICU stay,were collected.The incidence and types of PVA during the observation period were analyzed.Univariate and multivariate logistic regression analyses were performed to identify high-risk factors for PVA.Clinical outcomes were compared between patients with and without PVA.Results A total of 105 patients and 453 episodes of assisted mechanical ventilation waveforms were analyzed.Among these,60.95％(64/105)experienced at least one episode of PVA.Of the 453 ventilation waveforms assessed,35.76％(162/453)demonstrated PVA.The types of PVA,ranked by incidence,were as follows:cycling mismatch(12.58％,57/453),double triggering(11.92％,54/453),ineffective triggering(9.49％,43/453),flow starvation(5.30％,24/453),and exhalation flow limitation(1.77％,8/453).The incidence of PVA varied significantly across different ventilation modes:45.7％in volume-assist/control ventilation(V-A/C),38.1％in pressure-assist/control ventilation(P-A/C),42.9％in synchronized intermittent mandatory ventilation(SIMV),and 16.7％in pressure support ventilation(PSV)(P<0.001).Multi-variate logistic regression analysis revealed that the mechanical ventilation mode[reference:PSV;V-A/C:OR=4.687,95％CI:2.140～10.263,P<0.001;P-A/C:OR=2.922,95％CI:1.489～5.734,P=0.002;SIMV:OR=4.682,95％CI:1.758～12.466,P=0.002]and actual respiratory rate(OR=1.07,95％CI:1.016～1.127,P=0.011)were significant high-risk factors for PVA.Patients with PVA had a significantly longer duration of mechanical ventilation[8.21(5.35,13.91)days vs.3.00(1.96,5.71)days,P<0.001]compared to those without PVA.Conclusions PVA is commonly observed in ICU patients receiving assisted invasive mechanical ventilation,with cycling mismatch,double triggering,and ineffective triggering being the most prevalent types.The incidence of PVA tends to be lower when using the PSV mode.Clinically,real-time monitoring of patient-ventilator synchrony via ventilator waveforms,along with the optimization of ventilator modes and parameters,should be employed to minimize the occurrence of PVA and enhance the efficiency of mechanical ventilation.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective To evaluate the safety and efficacy of the Neuroform EZ self expanding stent for severe symptomatic intracranial atherosclerotic stenosis(sICAS).Methods Retrospectively enrolled consecutive patients with severe sICAS who underwent percutaneous transluminal angioplasty and stenting(PTAS)with a Neuroform EZ stent in the Department of Cerebrovascular Disease,Henan Provincial People's Hospital,from March 2020 to December 2022.Baseline demographic and clinical data were collected,including age,sex,hypertension,diabetes mellitus,coronary artery disease,dyslipidemia,hyperhomocysteinemia,transient ischemic attack(TIA)and ischemic stroke,smoking history,modified Rankin scale(mRS)score at admission,and National Institutes of Health stroke scale(NIHSS)score.Preoperative imaging data included target vessel(basilar artery,intracranial segment of the internal carotid artery,middle cerebral artery,and intracranial vertebral artery),lesion length,degree of stenosis,and vascular morphology according to the Mori classification(type A,lesion length＜5 mm with concentric or moderately eccentric stenosis;type B,lesion length＜10 mm with severely eccentric stenosis;type C,lesion length＞10 mm or arterial angulation＞90°).Technical success was defined as accurate delivery and deployment of the stent with complete coverage of the target lesion and immediate post deployment residual stenosis＜50%.Postoperative head CT was performed to detect intracranial hemorrhage.Periprocedural complications were recorded,including intracranial hemorrhage,arterial dissection,in stent thrombosis,and perforator occlusion occurring intraoperatively within 72 hours after the procedure.At one-month post-operation,patients were seen through outpatient follow-up for TIA,hemorrhagic or ischemic stroke,and all cause death.At 6 months after surgery,DSA or CT angiography(CTA)was performed to assess in stent restenosis(ISR,defined as＞50%stenosis within the stent or within5mm of its edges,or＞20%luminal loss).At 1 and 2 years postoperatively,ipsilateral ischemic stroke or TIA recurrence was assessed by outpatient visit or telephone follow up.Results A total of 76 patients with severe sICAS underwent PTAS with a Neuroform EZ stent(56 males,20 females,age 47-80 years,with a mean age of[61±10]years).(1)Within all patients enrolled,40 had middle cerebral artery,16 with basilar artery,6 with intracranial vertebral artery and 14 with intracranial internal carotid artery.The preprocedural lesion length was 2-15 mm,with a mean length of(6.2±2.5)mm,and stenosis severity was70%-99%,the mean severity was(83.2±6.9)%,with Mori type B being the most common type(57.9%[44/76]).(2)PTAS was successfully completed on all patients(technical success 100%).Pre dilation with a conventional balloon was performed in all cases(using balloon with diameter of 1.5-3.5mm,and stent with diameter of 2.5-4.5 mm and length of 15-30 mm).Immediate post procedural residual stenosis was(17.4±9.0)%,significantly lower than baseline(t=52.9,P＜0.05),with a mean difference of 65.8%(95%CI63.3%-68.3%).(3)Among all 76patients,one patient developed a flow limiting dissection post balloon angioplasty,which recovered after stent deployment.One patient with basilar artery stenosis experienced recurrent ischemic stroke at 5-day postoperatively,presenting with right sided weakness and coughing on liquids.Imaging showed an acute infarct in the left pons,considered perforator occlusion.The overall periprocedural complication rate was 2.6%(2/76).(4)No deaths occurred within 30 days after surgery.Sixty nine patients(90.8%)underwent 6 month imaging follow up with DSA(52 cases)or CTA(17 cases).ISR occurred in 12 patients(17.4%),including 6 asymptomatic and 6symptomatic cases.The ipsilateral ischemic stroke recurrence rate was 6.6%(5/76)at1 year and13.2%(10/76)at2years.Conclusions Neuroform EZstent assisted PTASappears safe and feasible for the treatment of severe sICAS.The long term effectiveness requires confirmation in large,multicenter,prospective studies.