[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"quality-health-care\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:quality-health-care":28},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,46,75],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":4,"maxAge":4,"enrollmentInfo":18,"targetDuration":21,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":29,"overallStatus":34,"whyStopped":4,"lastUpdateSubmitDate":35,"lastUpdatePostDateStruct":36,"startDateStruct":39,"completionDateStruct":41,"leadSponsor":43,"locationsCount":4},"100617000","machine-learning-and-artificial-intelligence-algorithms-to-optimize-the-performance-and-delivery-of-acute-dialysis-100617000",false,"NCT07312929","Machine Learning and Artificial Intelligence Algorithms to Optimize the Performance and Delivery of Acute Dialysis","SMART DIALYSIS - Scaling Machine Learning and Artificial Intelligence AlgoRithms to OpTimize the Performance and Delivery of Acute DIALYSIS.","SMART DIALYSIS","Inclusion Criteria\n\nPatients admitted to an intensive care unit (ICU) who require acute renal replacement therapy, either intermittent or continuous.\n\nExclusion Criteria\n\nReceipt of renal replacement therapy for less than 24 hours.\n\nPre-existing end-stage kidney disease.","ALL",{"count":19,"type":20},7500,"ESTIMATED","90 Days","OBSERVATIONAL","SMART DIALYSIS - Scaling Machine Learning and Artificial Intelligence AlgoRithms to OpTimize the Performance and Delivery of Acute DIALYSIS.\n\nHypothesis:\n\nCan the investigators develop and implement Machine Learning and Artificial Intelligence Algorithms into Clinical Information Systems to Optimize the Prescription, Delivery, and Performance of Acute Dialysis?\n\nObjective(s):\n\n1. Identify variables surrounding identified Key Performance Indicators that may be used by Machine Learning and Artificial Intelligence algorithms to optimize the prescription and performance of acute dialysis.\n2. Develop Machine Learning and Artificial Intelligence algorithms to help guide the prescription and delivery of acute dialysis in the development of Clinical Decision Support tools and Best Practice Advisories and create a ML\u002FAI Augmented SMART DIALYSIS Digital Dashboard.\n3. Implement and evaluate the performance of the developed Machine Learning and Artificial Intelligence algorithms on patient-centered and health economic outcomes.\n4. Validate and benchmark the performance of the evaluated Machine Learning and Artificial Intelligence algorithms across multiple jurisdictions.",[25,26,27,28],"Renal Dialysis","Renal Replacement Therapy","Renal Diseases","Quality Health Care",[30,31,32,33],"Dialysis","Articfical Inteligence","Key performance indicators","Machine Learning","NOT_YET_RECRUITING","2026-01-08",{"date":37,"type":38},"2026-01-12","ACTUAL",{"date":40,"type":20},"2026-06-01",{"date":42,"type":20},"2031-06-30",{"name":44,"class":45},"University of Alberta","OTHER",{"id":47,"slug":48,"hasResults":11,"nctId":49,"briefTitle":50,"officialTitle":51,"acronym":52,"eligibilityCriteria":53,"healthyVolunteers":54,"sex":17,"minAge":55,"maxAge":4,"enrollmentInfo":56,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":58,"conditions":59,"keywords":61,"overallStatus":34,"whyStopped":4,"lastUpdateSubmitDate":66,"lastUpdatePostDateStruct":67,"startDateStruct":69,"completionDateStruct":71,"leadSponsor":73,"locationsCount":4},"100605035","quality-indicators-in-obstetrics-100605035","NCT07157280","Quality Indicators in Obstetrics","Quality Indicators as a Tool for Continuous Improvement Process in Clinical Obstetrics","QUIG","Inclusion Criteria:\n\n* 18 years and older\n* staff in clinical obstetrics (midwife, physician)\n\nExclusion Criteria:\n\n* nurse in clinical obstetrics\n* staff in outpatient obstetrics",true,"18 Years",{"count":57,"type":20},150,"The study examines whether midwives and doctors are familiar with quality indicators in clinical obstetrics and whether these are used as a tool for continuous improvement process.",[28,60],"Quality Indicators, Health Care",[62,63,64,65],"quality management","quality indicators","obstetrics","staff","2025-08-28",{"date":68,"type":38},"2025-09-05",{"date":70,"type":20},"2025-09-01",{"date":72,"type":20},"2026-05-01",{"name":74,"class":45},"Martin-Luther-Universität Halle-Wittenberg",{"id":76,"slug":77,"hasResults":11,"nctId":78,"briefTitle":79,"officialTitle":80,"acronym":4,"eligibilityCriteria":81,"healthyVolunteers":54,"sex":82,"minAge":55,"maxAge":4,"enrollmentInfo":83,"targetDuration":4,"studyType":85,"phases":86,"briefSummary":88,"conditions":89,"keywords":90,"overallStatus":93,"whyStopped":4,"lastUpdateSubmitDate":94,"lastUpdatePostDateStruct":95,"startDateStruct":97,"completionDateStruct":99,"leadSponsor":101,"locationsCount":103},"100566273","dural-puncture-epidural-vs-standard-epidural-technique-in-parturient-receiving-continuous-labour-epidural-infusion-100566273","NCT06653036","Dural Puncture Epidural Vs Standard Epidural Technique in Parturient Receiving Continuous Labour Epidural Infusion","Dural Puncture Epidural Vs Standard Epidural Technique in Parturient Receiving Continuous Labour Epidural Infusion: a Randomized Controlled Trial","Inclusion Criteria:\n\n* Nulliparous \u002F Multiparous women\n* Age \\>18 years\n* ASA 1 \\& 2\n* Singleton vertex presentation\n* Gestational age 37-42 weeks\n* Parturient with established labor and pain score ≥ 3\n\nExclusion Criteria:\n\n* Major cardiac disease\n* History of chronic pain\n* Chronic opioid user\n* Platelet count \\\u003C 70 x 109\u002FL\n* spinal cord anomalies\n* Use of anticoagulants\n* Allergic to local anesthetics\n* Patients with preeclampsia\u002F eclampsia\n* Known fetal anomalies","FEMALE",{"count":84,"type":20},38,"INTERVENTIONAL",[87],"NA","The goal of this study is to evaluate the quality and safety of labor analgesia by comparing the use of Dural puncture epidural technique to Standard epidural technique while maintaining labor analgesia by means of continuous epidural infusion in parturient. The main questions it aims to answer are\n\n* Effectiveness and quality of labor analgesia\n* Frequency of catheter adjustments\n* Need for catheter replacements\n* Incidence of failed regional anesthesia requiring conversion to general anesthesia",[28],[91,92],"Quality Labor Analgesia","Maternal Adverse Events","RECRUITING","2025-01-28",{"date":96,"type":38},"2025-01-30",{"date":98,"type":38},"2024-11-28",{"date":100,"type":20},"2025-12-31",{"name":102,"class":45},"Aga Khan University",1]