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cliot (version 1.0.0)

fracture_index_score: Fracture Index (SOF) for Postmenopausal Women

Description

Calculates the Fracture Index (based on the Study of Osteoporotic Fractures) to predict the 5-year risk of hip, vertebral, or any non-vertebral fracture in postmenopausal women without using Bone Mineral Density (BMD). The score aggregates simple clinical risk factors including age, fracture history, maternal history, weight, smoking status, and functional mobility (chair rise).

Usage

fracture_index_score(age, history_fracture_after_50, maternal_hip_fracture,
                     weight_lt_57kg, smoker, uses_arms_to_stand)

Value

A list containing:

Fracture_Index_Score

The calculated score (Range 0-9+).

Est_5Yr_Hip_Fracture_Risk

Estimated percentage risk of hip fracture over 5 years.

Est_5Yr_Any_Fracture_Risk

Estimated percentage risk of any non-vertebral fracture over 5 years.

Bone_Density_Correlation

General correlation with BMD status (e.g., Osteoporosis likelihood).

Arguments

age

Numeric. Patient age in years. <65: 0 pts. 65-69: 1 pt. 70-74: 2 pts. 75-79: 3 pts. >=80: 4 pts.

history_fracture_after_50

Numeric (0 or 1). History of any fracture after age 50. (1 = Yes, +1 pt).

maternal_hip_fracture

Numeric (0 or 1). History of hip fracture in the patient's mother after age 50. (1 = Yes, +1 pt).

weight_lt_57kg

Numeric (0 or 1). Does the patient weigh less than 57 kg (125 lbs)? (1 = Yes, +1 pt).

smoker

Numeric (0 or 1). Is the patient a current smoker? (1 = Yes, +1 pt).

uses_arms_to_stand

Numeric (0 or 1). Does the patient need to use their arms to stand up from a chair? (1 = Yes, +1 pt).

References

Black DM, Steinbuch M, Palermo L, et al. An assessment tool for predicting fracture risk in postmenopausal women. Osteoporos Int. 2001;12(7):519-528. doi:10.1007/s001980170072

Examples

Run this code

# Example 1: High Risk
# 82yo (+4), Prior Fx (+1), Uses arms (+1)
# Score = 6
fracture_index_score(82, 1, 0, 0, 0, 1)

# Example 2: Low Risk
# 60yo (0), No risk factors
# Score = 0
fracture_index_score(60, 0, 0, 0, 0, 0)

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