Clinical prediction rule

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Editor-In-Chief: C. Michael Gibson, M.S., M.D. [1]; Associate Editor(s)-In-Chief: Ujjwal Rastogi, M.B.B.S. [2]

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.[1]

Physicians have difficulty in estimated risks of diseases; frequently erring towards overestimation[2], 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.[3]

When studied, the impact of providing the information alone (for example, providing the calculated probability of disease) has been negative.[4][5]

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.[6]

The more intensively the prediction rule is implemented the more benefit will occur.[7]

Examples of prediction rules

Cardiovascular diseases

Acute MI / unstable angina

Risk Score Year published Purpose
TIMI risk score 2000 Unstable Angina
TIMI risk score 2000 STEMI
Morrow et al (TIME II substudy) [8] 2001 Predicting mortality in STEMI
Silver et al [9] 1994 To predict preserved left ventricular ejection fraction in patients after MI
The GRACE risk score 2003 For risk of death in NSTEMI
ACI-TIPI risk score [10] 1991 To assess the likelihood of patients having acute cardiac ischemia and thus the appropriateness of admitting them to the coronary care unit (CCU).
Goldman algorithm [11] 1988 To predict the likelihood that a patient has a myocardial infarction.
Hathaway et al [12] 1998 Prognosis based on initial ECG
Selker et al [13] 1991 Risk of death in AMI
Piombo et al [14] 2003 To stratify risk in unstable angina.
Solomon et al [15] 2001 To identify which patients benefit from immediate coronary angiography and revascularization.
Sabatine et al [16] 2001 Benefit with glycoprotein IIb/IIIa inhibitor therapy in patients with unstable angina pectoris.

Stroke, Atrial fibrillation

Risk Score Year published Purpose
HAS-BLED 2010 Bleeding risk stratification score for those on oral anticoagulants in atrial fibrillation.
ABCD 2 [17] 2010 Stroke risk with TIA
CHA2DS2-VASc Score 2009 To predict clinical risk of stroke and thromboembolism in atrial fibrillation.
Schnabel et al [18] Framingham Heart Study [3] 2009 10 years risk of Atrial fibrillation
HEMORR2HAGES [19] 2006 Bleeding Risk Score
ABCD [20] 2005 Stroke risk after TIA
van Walraven et al [21] 2003 Stroke risk - atrial fib
Wang et al [22] 2003 To predict 1 year stroke mortality
Counsel et al [23] 2003 Acute stroke prognosis (6 variable score)
Wang et al [24] Framingham Heart Study [4] 2003 Stroke after Atrial fibrillation
Wang et al [24] Framingham Heart Study [5] 2003 Stroke or death after Atrial fibrillation.
Efstathiou et al [25] 2002 To differentiate Ischemic from hemorrhagic stroke
Lumley et al [26] 2002 To predict stroke in elderly.
CHADS2 2001 Risk of stroke with AFIB
Baird et al [27] 2001 To predict stroke recovery.
Wang et al [28] 2001 To predict 30 days stroke mortality
NIH Stroke Scale [29] 1999 To predicts the likelihood of a patient's recovery after stroke.
Cincinnati stroke scale [30] 1999 Stroke diagnosis
D'Agostino et al [31] Framingham Heart Study [6] 1994 Risk of stroke

Deep veinous thrombosis & PE

Risk Score Year published Purpose
Wells score 2000 Pulmonary embolism

Hypertension, Lipid & Screening

Risk Score Year published Purpose
Parikh et al [32] Framingham Heart Study [7] 2008 Hypertension Risk Score
NCEP ATP III [33] 2001 Screening: lipid guideline
Krijnen et al [34] 1998 To predict renal artery stenosis.
Murabito et al [35] Framingham Heart Study [8] 1997 Intermittent claudication

Chest pain and CAD

Risk Score Year published Purpose
Panic Screening Score [36] 2011 Screening score to improve recognition of panic-like anxiety in emergency department (ED) patients with unexplained chest pain.
Pencina et al [37] Framingham Heart Study [9] 2009 30-year risk of cardiovascular disease.
North American Chest Pain Rule [38] 2008 For early discharge of patients with chest pain.
Vancouver chest pain rule [39] 2006 For early discharge of patients with chest pain.
Duke treadmill score [40] 1999 To risk-stratify patients with ST-T abnormalities on the resting ECG
Wilson et al [41] Framingham Heart Study [10] 1998 10-year risk of coronary heart disease.
Diamond et al [42] 1979 Pretest probability of CAD.

Angioplasty

Risk Score Year published Purpose
Halkin et al [43] 2005 Angioplasty complication rate
Fortescue et al [44] 2003 Angioplasty complication rate
Singh et al [45] 2002 Angioplasty complication rate
Resnic et al [46] 2001 Angioplasty complication rate
Moscucci et al [47] 2001 Mortality after angioplasty.

Valve and endocarditis

Risk Score Year published Purpose
Otto et al [48] 1988 AV replacement in aortic stenosis.
Koplan et al [49] 2003 To predict the need for permanent pacing after cardiac valve surgery.
Hasbun et al [50] 2003 Endocarditis prognosis.

Others

Risk Score Year published Purpose
Feringa et al [51] 2007 Peripheral vascular disease prognosis.



Other organ system

Risk Score Purpose
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 [11]
Ottawa ankle rules To decide for offering Xray to patient with foot or ankle pain.


Rules predicting complications in diseased patients
Risk Score Purpose
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 [52] To calculate pulmonary complications after thoracic surgery for primary Lung Cancer

Adverse effects

Patients may not be comfortable with the way a doctor may integrate decision support into practice.[53]

References

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  53. Shaffer VA, Probst CA, Merkle EC, Arkes HR, Medow MA (2013). "Why do patients derogate physicians who use a computer-based diagnostic support system?". Med Decis Making. 33 (1): 108–18. doi:10.1177/0272989X12453501. PMID 22820049.

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