[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"respiratory-failure-pediatric-patients\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:respiratory-failure-pediatric-patients":30},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,44,75],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":16,"sex":17,"minAge":18,"maxAge":19,"enrollmentInfo":20,"targetDuration":4,"studyType":23,"phases":24,"briefSummary":26,"conditions":27,"keywords":4,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":33,"lastUpdatePostDateStruct":34,"startDateStruct":37,"completionDateStruct":39,"leadSponsor":41,"locationsCount":4},"100648852","ai-guided-mechanical-ventilation-in-children-a-randomized-controlled-trial-100648852",false,"NCT07728136","AI-Guided Mechanical Ventilation in Children: A Randomized Controlled Trial","Randomized Controlled Study on Intelligent Optimization of Ventilator Parameters for Pediatric Patients Undergoing Mechanical Ventilation Based on Large Language Models","Inclusion Criteria:\n\n1. PICU patients aged 1 month to 18 years.\n2. Receiving invasive mechanical ventilation, expected to last ≥ 24 hours.\n3. Informed consent signed before enrollment.\n\nExclusion Criteria:\n\n1. Expected survival \\\u003C 24 hours\n2. Irreversible brain injury (GCS = 3 + absence of brainstem reflexes)\n3. Severe congenital cardiopulmonary malformations affecting ventilation assessment\n4. Pregnancy (must be ruled out in adolescent girls)\n5. Currently participating in other ventilation intervention trials\n6. Guardian refusal to participate",true,"ALL","1 Month","18 Years",{"count":21,"type":22},200,"ESTIMATED","INTERVENTIONAL",[25],"NA","This prospective, randomized controlled trial aims to evaluate whether an AI-driven decision support system can improve clinical outcomes for mechanically ventilated pediatric patients (aged 1 month to 18 years) in the PICU, compared to standard care. The primary question addressed is: Do patients whose ventilator parameter optimization decisions are guided by AI assistance achieve a greater number of ventilator-free days within 28 days compared to those managed with standard care by medical staff? Eligible pediatric patients requiring mechanical ventilation following tracheal intubation will be randomly assigned (1:1) to either the AI-guided intervention group or the standard care control group. In the intervention group, physicians will receive real-time, AI-generated recommendations for ventilator parameters to inform clinical adjustments. In contrast, the control group will be managed according to standard clinical protocols. This study seeks to assess whether AI-driven ventilator optimization can effectively improve clinical outcomes and shorten ventilation duration for pediatric patients in the PICU.",[28,29,30,31],"Acute Respiratory Distress Syndrome","Pneumonia in Children","Respiratory Failure (Pediatric Patients)","Congenital Heart Disease in Children","NOT_YET_RECRUITING","2026-07-22",{"date":35,"type":36},"2026-07-27","ACTUAL",{"date":38,"type":22},"2026-09-01",{"date":40,"type":22},"2027-12-31",{"name":42,"class":43},"Wu Rongzhou","OTHER",{"id":45,"slug":46,"hasResults":11,"nctId":47,"briefTitle":48,"officialTitle":49,"acronym":50,"eligibilityCriteria":51,"healthyVolunteers":11,"sex":17,"minAge":19,"maxAge":4,"enrollmentInfo":52,"targetDuration":4,"studyType":23,"phases":54,"briefSummary":55,"conditions":56,"keywords":58,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":65,"lastUpdatePostDateStruct":66,"startDateStruct":68,"completionDateStruct":70,"leadSponsor":72,"locationsCount":4},"100610657","ai-assisted-bronchoscopy-navigation-and-diagnostic-system-for-severe-pneumonia-a-multicenter-prospective-study-100610657","NCT07230431","AI-Assisted Bronchoscopy Navigation and Diagnostic System for Severe Pneumonia: A Multicenter Prospective Study","Development and Clinical Validation of an Embodied-Intelligence-Assisted Bronchoscopy Navigation and Diagnostic System: A Multicenter Prospective Study","EIBRONCH","Inclusion Criteria:\n\n1. Age ≥18 years.\n2. Severe pneumonia requiring clinically indicated bronchoscopy for diagnosis and\u002For therapy, as determined by the treating team.\n3. Written informed consent from the patient or a legally authorized representative.\n4. Expected to tolerate bronchoscopy with current respiratory support (e.g., HFNC\u002FNIV\u002FIMV) per site protocol\n\nExclusion Criteria:\n\n1. Standard contraindications to bronchoscopy, such as uncontrolled hypoxemia despite support (SpO2 \\\u003C90% for ≥30 s on FiO2 ≥0.60), hemodynamic instability requiring escalating vasopressors, or malignant arrhythmia not controlled.\n2. Uncorrected coagulopathy likely to increase bleeding risk (e.g., platelets \\\u003C50×10\\^9\u002FL or INR \\>1.5) per site policy.\n3. Known pregnancy or breastfeeding if the investigator judges risk outweighs benefit according to site policy.\n4. Participation in another interventional drug\u002Fdevice study that could interfere with outcomes.\n5. Any condition that, in the investigator's judgment, makes participation unsuitable (e.g., emergent life-saving bronchoscopy without time for consent).",{"count":53,"type":22},100,[25],"This study will evaluate an embodied-intelligence-assisted bronchoscopy navigation and diagnostic system for patients with severe pneumonia who require clinically indicated bronchoscopy. The system provides real-time visual cues and voice prompts to help physicians localize target lung segments and describe endobronchial findings; physicians remain fully responsible for all clinical decisions. The trial is designed as a prospective, multicenter, controlled study conducted at about ten hospitals in China, with an anticipated sample size of approximately 100 patients. The primary objective is to determine whether AI assistance improves diagnostic agreement compared with the reference assessment, while secondary objectives include navigation success (e.g., loss-of-path rate), procedure time, and complication rates. The results will provide evidence on the safety and effectiveness of AI-assisted bronchoscopy and support product validation and registration.",[30,57],"Pneumonia",[59,60,61,62,63,64],"Severe pneumonia","Bronchoscopy","Navigation system","Artificial intelligence","Computer-assisted","Diagnostic support","2025-11-13",{"date":67,"type":36},"2025-11-17",{"date":69,"type":22},"2025-11",{"date":71,"type":22},"2026-11",{"name":73,"class":74},"Chinese Medical Association","NETWORK",{"id":76,"slug":77,"hasResults":11,"nctId":78,"briefTitle":79,"officialTitle":80,"acronym":4,"eligibilityCriteria":81,"healthyVolunteers":16,"sex":17,"minAge":4,"maxAge":4,"enrollmentInfo":82,"targetDuration":4,"studyType":23,"phases":84,"briefSummary":85,"conditions":86,"keywords":4,"overallStatus":91,"whyStopped":4,"lastUpdateSubmitDate":92,"lastUpdatePostDateStruct":93,"startDateStruct":95,"completionDateStruct":97,"leadSponsor":99,"locationsCount":5},"100569837","artificial-intelligence-driven-virtual-standardized-pediatric-patients-trial-100569837","NCT06699433","Artificial Intelligence-driven Virtual Standardized Pediatric Patients Trial","Utilizing Artificial Intelligence-driven Virtual Standardized Pediatric Patients to Enhance the Capabilities of Primary Healthcare Doctors in China for Managing Common Pediatric Diseases: a Randomized Controlled Trial","1. Inclusion and Exclusion Criteria for Research Institutions\n\n   Inclusion Criteria:\n   * Primary and secondary hospitals\n   * Community health centers (stations) and clinics, as well as township health centers and village health clinics\n\n   Exclusion Criteria:\n   * Specialized medical institutions (such as specialized hospitals and dental clinics)\n   * Public health prevention and treatment institutions (such as tuberculosis prevention centers)\n   * Ethnic medicine institutions (such as Mongolian and Tibetan hospitals)\n   * Hospitals above the secondary level\n   * Hospitals that have not yet been graded (due to their short establishment time and potentially unstable operations)\n2. Inclusion and exclusion criteria for research subjects\n\nInclusion Criteria:\n\n* Practicing (assistant) doctors and rural doctors working in medical institutions that meet the above conditions\n* With a scope of practice only including general practice, internal medicine, surgery, and pediatrics\n\nExclusion Criteria:\n\n-None",{"count":83,"type":22},459,[25],"Background: China's healthcare system for children faces significant challenges, particularly due to the limited pediatric service capacity of primary healthcare institutions. A shortage of effective and accessible training tools for primary care doctors further hinders progress in addressing this gap. Technological advancements, especially in artificial intelligence, offer a potential solution to improve pediatric care. Artificial intelligence-driven virtual standardized patients (VSPs), leveraging internet and virtual simulation technologies, simulate clinical cases with specific disease characteristics, providing an innovative, efficient, and flexible training method. VSPs are increasingly utilized in medical education, clinical reasoning, and licensure exams. This study focuses on using VSPs to improve the management of common pediatric conditions, which are major health concerns for children and impose significant psychological and financial burdens on families.\n\nMethods: This study will involve a three-arm randomized controlled trial to evaluate the effectiveness of a virtual pediatric standardized patient platform in enhancing primary care doctors' management of common pediatric diseases. At least 459 participants, including general practitioners, internal medicine practitioners, surgeons, and pediatricians from more than 10 provinces across China, will be randomly assigned to one of three groups: the virtual patient platform group, the case teaching manual group, or the case teaching video group. Five virtual patient cases covering pneumococcal pneumonia, rotavirus enteritis with hypovolemic shock, hand-foot-and-mouth disease, acute appendicitis, and respiratory failure will be developed, along with corresponding case teaching materials. After a two-week learning period, participants' disease management abilities will be assessed using clinical vignettes. The primary outcome is adherence to best clinical practice guidelines, categorized into full adherence, partial adherence, and nonadherence.\n\nDiscussion: This study aims to leverage artificial intelligence for capacity enhancement, targeting the shortcomings of primary care pediatrics and using VSP to help enhance primary care pediatrics capacity. It is a randomized controlled trial involving over 300 primary healthcare institutions across more than 10 provinces in China, ensuring broad and representative participation from both developed and underdeveloped regions.",[87,88,89,90,30],"Pneumococcal Pneumonia","Rotavirus Enteritis With Hypovolemic Shock","Hand-foot-and-mouth Disease","Acute Appendicitis","RECRUITING","2024-12-15",{"date":94,"type":36},"2024-12-19",{"date":96,"type":22},"2024-12",{"date":98,"type":22},"2025-01",{"name":100,"class":43},"Southern Medical University, China"]