Cuestionario vinculado a una guía · Medio Nivel

Prueba de predicción de IA de lesión renal aguda

Prueba la definición de IRA de KDIGO, lo que realmente hicieron el estudio DeepMind-VA y la aplicación Streams, y por qué las alertas de IRA no han mejorado los resultados de manera confiable.

Rutas de guía relacionadasPredicción de lesión renal aguda por IA
Pregunta 1 de 8

Under the KDIGO criteria described in this guide, which creatinine change within 48 hours qualifies as acute kidney injury?

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  1. Under the KDIGO criteria described in this guide, which creatinine change within 48 hours qualifies as acute kidney injury?
    • A rise of 0.1 mg/dL
    • A rise of at least 0.3 mg/dL
    • A fall of at least 0.3 mg/dL
    • Any value above 1.0 mg/dL
  2. Why do AKI models try to predict injury instead of waiting for creatinine to rise?
    • Creatinine tests are too expensive to repeat
    • Creatinine can only be measured in the ICU
    • Creatinine is a lagging marker, so the injury may already be a day or more old when it rises
    • Creatinine falls during kidney injury
  3. In the 2019 DeepMind and VA study, roughly how many false alerts came with each correct AKI prediction?
    • About two
    • About twenty
    • Ninguno
    • About one false alert per hundred true ones
  4. Which group did the VA-trained AKI model perform worse for, and why?
    • Older patients, because they have less lab data
    • Women, because they were a small share of the VA training population
    • ICU patients, because their creatinine is measured too often
    • Surgical patients, because anesthesia hides creatinine changes
  5. What did DeepMind's Streams app at the Royal Free Hospital actually deliver to clinicians?
    • Deep learning predictions of AKI 48 hours ahead
    • Automated dialysis orders
    • Genetic risk scores for kidney disease
    • Alerts from the rule-based NHS England AKI algorithm
  6. What did the Yale randomized trials of electronic AKI alerts find?
    • Alerts halved the need for dialysis
    • Alerts did not improve outcomes such as dialysis or death overall
    • Alerts only worked when sent by text message
    • Alerts made creatinine measurements more accurate
  7. Why does the guide call missing lab data 'informative' in AKI models?
    • Missing values are always errors in the database
    • Labs are missing only for patients who died
    • A lab that was never ordered often means the clinician wasn't worried, so the ordering pattern itself predicts risk
    • Missing values are filled in by the laboratory later
  8. Why should an AKI model's evaluation exclude patients who already meet AKI criteria when the prediction is made?
    • To avoid giving the model credit for spotting injuries that are already known
    • Because those patients have no creatinine data
    • Because the law forbids scoring them
    • Because they always go on to need dialysis