Clinical prediction rule

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Editor-In-Chief: C. Michael Gibson, M.S., M.D. [1]

Overview

A clinical prediction rule is type of medical research study in which researchers try to identify the best combination of medical sign, symptoms, and other findings in predicting the probability of a specific disease or outcome.

Physicians have difficulty in estimated risks of diseases; frequently erring towards overestimation, perhaps due to cognitive biases such as base rate fallacy in which the risk of an adverse outcome is exaggerated.

Methods

In a prediction rule study, investigators identify a consecutive group of patients who are suspected of a having a specific disease or outcome. The investigators then compare the value of clinical findings available to the physician versus the results of more intensive testing or the results of delayed clinical follow up.

Effect on health outcomes

Few prediction rules have had the consequences of their usage by physicians quantified.

When studied, the impact of providing the information alone (for example, providing the calculated probability of disease) has been negative.

However, when the prediction rule is implemented as part of a critical pathway, so that a hospital or clinic has procedures and policies established for how to manage patients identified as high or low risk of disease, the prediction rule has more impact on clinical outcomes.

The more intensively the prediction rule is implemented the more benefit will occur.

Examples of prediction rules

Rules predicting the probability of a disease.
Risk Score	Purpose
Cardiovascular diseases
TIMI risk score	Unstable Angina
TIMI risk score	STEMI
CHADS2	Risk of stroke with AFIB
Wells score	Pulmonary embolism
Schnabel et al Framingham Heart Study [2]	Atrial fibrillation
Pencina et al Framingham Heart Study [3]	30-year risk of cardiovascular disease.
Wilson et al Framingham Heart Study [4]	10-year risk of coronary heart disease.
Parikh et al Framingham Heart Study [5]	Hypertension Risk Score
Gastroentestinal diseases
Ranson criteria	To predict the severity of acute pancreatitis.
Tygerberg score	To diffrentiate tuberculosis as a cause of pericarditis.
Orthopedic diseases
QFracture score	Osteoporosis [6]
Ottawa ankle rules	To decide for offering Xray to patient with foot or ankle pain.
Rules predicting complications in diseased patients
Pneumonia severity index	To calculate the probability of morbidityand mortality among patients with community acquired pneumonia.
CURB-65	To predict mortality in community-acquired pneumonia.
MELD	To assess the severity of chronic liver disease.
Apnea-hypopnea index	To assess the overall severity of sleep apnea.
Amar et al	To calculate pulmonary complications after thoracic surgery for primary Lung Cancer

• Various rules are used in the Intensive Care Unit and are grouped as ICU scoring systems (Glasgow coma scale, Pediatric Glasgow Coma Scale, APACHE II, SAPS II, PIM2).