Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Клинические системы оценки в ветеринарной медицине× | Оценка риска анестезии в ветеринарии× | |
|---|---|---|
| Область | Ветеринарная медицина | Ветеринарная медицина |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2000s | 1941-present |
| Автор метода≠ | Veterinary Pain Society and AAFP | American Society of Anesthesiologists (ASA) |
| Тип≠ | Assessment pipeline | Risk assessment and stratification |
| Основополагающий источник≠ | Hansen, B. D., Lascelles, B. D., Keates, H., et al. (2015). Painful Osteoarthritis in Cats: Chronic Pain Assessment, Management, and Welfare Considerations. Journal of Feline Medicine and Surgery, 17(8), 637-646. link ↗ | American Society of Anesthesiologists (ASA) House of Delegates. (2020). ASA Physical Status Classification System. Retrieved from ASA official website: https://www.asahq.org/standards-and-guidelines/asa-physical-status-classification-system link ↗ |
| Другие названия≠ | clinical assessment scoring, veterinary patient scoring | surgical risk scoring, preoperative assessment, ASA scoring |
| Связанные | 3 | 3 |
| Сводка≠ | Clinical scoring systems provide standardized methods for objectively assessing animal health status, pain, disease severity, and treatment outcomes. Developed progressively by veterinary organizations and research groups since the early 2000s, these systems enable consistent documentation, comparison of cases, and evidence-based clinical decision-making across species and practice settings. | Anesthesia risk scoring is a systematic preoperative assessment method that stratifies patient risk based on medical history, physical findings, and health status. Adapted from the American Society of Anesthesiologists Physical Status classification (developed for humans in 1941) and refined for veterinary species through confidential enquiry data and clinical research, it guides anesthetic technique selection, identifies high-risk patients requiring optimization, and predicts perioperative morbidity and mortality. |
| ScholarGateНабор данных ↗ |
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