Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
142 participants
OBSERVATIONAL
2021-11-01
2022-11-30
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Surgical Patients
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
No
Sponsors
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University of Parma
OTHER
Responsible Party
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Elena Giovanna Bignami
Chief of 2^ UO Anesthesua and Intensive Care, Full Professor of University of Parma
Locations
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Azienda Ospedaliera-Universitaria di Parma
Parma, , Italy
Countries
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Central Contacts
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Facility Contacts
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References
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Evans RS, Burke JP, Classen DC, Gardner RM, Menlove RL, Goodrich KM, Stevens LE, Pestotnik SL. Computerized identification of patients at high risk for hospital-acquired infection. Am J Infect Control. 1992 Feb;20(1):4-10. doi: 10.1016/s0196-6553(05)80117-8.
Redfern RO, Langlotz CP, Abbuhl SB, Polansky M, Horii SC, Kundel HL. The effect of PACS on the time required for technologists to produce radiographic images in the emergency department radiology suite. J Digit Imaging. 2002 Sep;15(3):153-60. doi: 10.1007/s10278-002-0024-5. Epub 2002 Nov 6.
Lee TT, Liu CY, Kuo YH, Mills ME, Fong JG, Hung C. Application of data mining to the identification of critical factors in patient falls using a web-based reporting system. Int J Med Inform. 2011 Feb;80(2):141-50. doi: 10.1016/j.ijmedinf.2010.10.009. Epub 2010 Nov 5.
Martins M. Use of comorbidity measures to predict the risk of death in Brazilian in-patients. Rev Saude Publica. 2010 Jun;44(3):448-56. doi: 10.1590/s0034-89102010005000003. Epub 2010 Apr 30.
Izad Shenas SA, Raahemi B, Hossein Tekieh M, Kuziemsky C. Identifying high-cost patients using data mining techniques and a small set of non-trivial attributes. Comput Biol Med. 2014 Oct;53:9-18. doi: 10.1016/j.compbiomed.2014.07.005. Epub 2014 Jul 22.
Bottani E, Bellini V, Mordonini M, Pellegrino M, Lombardo G, Franchi B, Craca M, Bignami E. Internet of Things and New Technologies for Tracking Perioperative Patients With an Innovative Model for Operating Room Scheduling: Protocol for a Development and Feasibility Study. JMIR Res Protoc. 2023 Jul 5;12:e45477. doi: 10.2196/45477.
Other Identifiers
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1284/2020/OSS/AOUPR
Identifier Type: -
Identifier Source: org_study_id
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