Rhode Island medical journal (2013) · 2025
Improving Diagnostic Efficiency for Knee Osteoarthritis with the Knee Intake Patient Survey (KIPS).
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Liu Jonathan, Daher Mohammad, Callanan Tucker, Gilreath Noah, Milner John, Caus Sandi, Molino Janine, Antoci Valentin
Аннотация
OBJECTIVES: Knee Osteoarthritis (OA) is one of the most frequently encountered conditions in orthopedic practice. This study aimed to validate the Knee Intake Patient Survey (KIPS), a short-form questionnaire designed to assist in the initial diagnosis and treatment stratification for knee OA.
METHODS: Patient intake survey results from a single adult reconstruction clinic were retrospectively analyzed alongside clinical diagnoses and treatment recommendations. The KIPS total score and individual question responses were assessed for their correlation with a diagnosis of knee OA versus other knee pathologies, as well as treatment decisions.
RESULTS: Higher total KIPS scores were significantly associated with a diagnosis of knee OA and increased likelihood of surgical recommendation, while lower scores correlated with alternative diagnoses (e.g., patellofemoral arthritis or knee internal derangement) and physical therapy recommendations. A KIPS threshold score of ≥10 maximized the specificity (94.4%) for diagnosing knee OA.
CONCLUSIONS: The KIPS questionnaire effectively differentiates knee OA from other pathologies and stratifies patients for treatment recommendations. Incorporating validated tools like KIPS may enhance clinical efficiency and support future AI-driven diagnostic models in orthopedic care.
METHODS: Patient intake survey results from a single adult reconstruction clinic were retrospectively analyzed alongside clinical diagnoses and treatment recommendations. The KIPS total score and individual question responses were assessed for their correlation with a diagnosis of knee OA versus other knee pathologies, as well as treatment decisions.
RESULTS: Higher total KIPS scores were significantly associated with a diagnosis of knee OA and increased likelihood of surgical recommendation, while lower scores correlated with alternative diagnoses (e.g., patellofemoral arthritis or knee internal derangement) and physical therapy recommendations. A KIPS threshold score of ≥10 maximized the specificity (94.4%) for diagnosing knee OA.
CONCLUSIONS: The KIPS questionnaire effectively differentiates knee OA from other pathologies and stratifies patients for treatment recommendations. Incorporating validated tools like KIPS may enhance clinical efficiency and support future AI-driven diagnostic models in orthopedic care.