Bmi Bsa Calculator

BMI & BSA Calculator

Overview

Clinical calculator for anthropometric measurements used in health assessment, obesity screening, and chemotherapy dosing calculations.

Key Capabilities:

When to Use

✅ Use this skill when:

❌ Do NOT use when:

Integration:

Core Capabilities

1. BMI Calculation

Calculate Body Mass Index with classification:

from scripts.calculator import BMIBSACalculator
calc = BMIBSACalculator()
Calculate BMI
result = calc.calculate_bmi(
    weight_kg=70,
    height_cm=175,
    age=45,
    sex="male"
)
print(f"BMI: {result.bmi:.1f} kg/m²")
print(f"Category: {result.category}")  # Normal weight
print(f"Ideal weight range: {result.ideal_weight_range}")

BMI Categories (WHO): | Category | BMI Range | Clinical Significance | |----------|-----------|---------------------| | Underweight | < 18.5 | Malnutrition risk | | Normal | 18.5 - 24.9 | Healthy range | | Overweight | 25.0 - 29.9 | Increased risk | | Obese I | 30.0 - 34.9 | High risk | | Obese II | 35.0 - 39.9 | Very high risk | | Obese III | ≥ 40.0 | Extremely high risk |

Adjusted BMI:

2. BSA Calculation

Multiple formulas for different clinical scenarios:

# Calculate BSA using different formulas
bsa_results = calc.calculate_bsa(
    weight_kg=70,
    height_cm=175,
    formulas=["dubois", "mosteller", "haycock", "gehan_george"]
)
for formula, bsa in bsa_results.items():
    print(f"{formula}: {bsa:.2f} m²")

BSA Formulas: | Formula | Equation | Best For | |---------|----------|----------| | DuBois | 0.007184 × W^0.425 × H^0.725 | Adults (most common) | | Mosteller | √(W × H / 3600) | Adults (simplified) | | Haycock | 0.024265 × W^0.5378 × H^0.3964 | Pediatrics | | Gehan-George | 0.0235 × W^0.51456 × H^0.42246 | Oncology | | Yu | 0.015925 × W^0.5 × H^0.5 | Asian populations |

3. Drug Dosing Calculations

Apply BSA to medication dosing:

# Calculate chemotherapy dose
dose = calc.calculate_dose(
    bsa=bsa_results["dubois"],
    drug="carboplatin",
    dose_per_m2=400,  # mg/m²
    max_dose=800  # mg cap
)
print(f"Calculated dose: {dose:.0f} mg")
print(f"BSA used: {bsa_results['dubois']:.2f} m²")

Common BSA-Based Doses:

4. Pediatric Calculations

Age-appropriate calculations for children:

pediatric = calc.pediatric_mode(
    weight_kg=25,
    height_cm=120,
    age_years=8,
    sex="female"
)
print(f"BMI-for-age percentile: {pediatric.bmi_percentile}%")
print(f"Weight status: {pediatric.weight_status}")
print(f"BSA (Haycock): {pediatric.bsa:.2f} m²")

Pediatric Considerations:

Common Patterns

Pattern 1: Chemotherapy Dosing

Scenario: Calculate carboplatin dose for cancer patient.

# Calculate BSA and dose
python scripts/main.py \
  --weight 70 \
  --height 175 \
  --drug carboplatin \
  --target-auc 5 \
  --creatinine-clearance 80 \
  --output dose_calculation.txt

Output:

BSA (DuBois): 1.79 m²
Calvert Formula: Dose = Target AUC × (GFR + 25)
                 = 5 × (80 + 25)
                 = 525 mg
Maximum dose check: 525 mg ≤ 800 mg ✓
Recommended dose: 525 mg

Pattern 2: Obesity Screening

Scenario: BMI assessment for weight management clinic.

# BMI with full assessment
assessment = calc.assess_bmi(
    weight_kg=95,
    height_cm=165,
    age=52,
    sex="female",
    waist_cm=98
)
print(f"BMI: {assessment.bmi:.1f} (Obese Class II)")
print(f"Waist-to-height ratio: {assessment.whtr:.2f} (High risk)")
print(f"Comorbidity risk: {assessment.health_risk}")
print(f"Recommended: {assessment.recommendations}")

Pattern 3: Pediatric Growth Assessment

Scenario: Calculate child's BSA for medication dosing.

# Pediatric dosing
child = calc.pediatric_assessment(
    weight_kg=20,
    height_cm=110,
    age_years=6,
    sex="male"
)
print(f"BSA: {child.bsa:.2f} m² (Haycock formula)")
print(f"BMI percentile: {child.bmi_percentile}th")
print(f"Doxorubicin dose: {child.bsa * 60:.0f} mg")

Pattern 4: Rapid Clinical Assessment

Scenario: Quick BMI/BSA for admission vital signs.

# Quick calculation
python scripts/main.py --weight 80 --height 180 --quick
Output:
BMI: 24.7 kg/m² (Normal)
BSA: 2.00 m² (DuBois)
Ideal weight: 65-80 kg

Complete Workflow Example

Comprehensive patient assessment:

from scripts.calculator import BMIBSACalculator
from scripts.reports import ClinicalReport
Initialize
calc = BMIBSACalculator()
report = ClinicalReport()
Patient data
patient = {
    "weight_kg": 75,
    "height_cm": 170,
    "age": 55,
    "sex": "female",
    "waist_cm": 88
}
Calculate all metrics
bmi = calc.calculate_bmi(**patient)
bsa = calc.calculate_bsa(**patient, formula="dubois")
assessment = calc.comprehensive_assessment(**patient)
Generate report
report_data = {
    "bmi": bmi,
    "bsa": bsa,
    "assessment": assessment,
    "recommendations": assessment.recommendations
}
report.generate(report_data, output="patient_assessment.pdf")

Quality Checklist

Input Validation:

Calculation Accuracy:

Clinical Interpretation:

Documentation:

Common Pitfalls

Calculation Errors:

Clinical Misuse:

Dosing Errors:

References

Available in references/ directory:

Scripts

Located in scripts/ directory:

Limitations

Parameters

| Parameter | Type | Default | Required | Description | |-----------|------|---------|----------|-------------| | --weight, -w | float | - | Yes | Weight in kilograms | | --height, -H | float | - | Yes | Height in centimeters | | --dose, -d | float | - | No | Standard drug dose per m² in mg (optional) | | --format, -f | string | text | No | Output format (text, json) | | --output, -o | string | - | No | Output file path (optional) |

Usage

Basic Usage

# Calculate BMI and BSA
python scripts/main.py --weight 70 --height 175
Calculate with drug dosing
python scripts/main.py --weight 70 --height 175 --dose 100
Output as JSON
python scripts/main.py --weight 70 --height 175 --format json --output results.json

Risk Assessment

| Risk Indicator | Assessment | Level | |----------------|------------|-------| | Code Execution | Python script executed locally | Low | | Network Access | No external API calls | Low | | File System Access | Optional file output only | Low | | Data Exposure | No sensitive data stored | Low | | Clinical Risk | Results used for medical decisions | Medium |

Security Checklist

Prerequisites

# Python 3.7+
No additional packages required (uses standard library)

Evaluation Criteria

Success Metrics

Test Cases

Lifecycle Status

⚕️ Clinical Note: BMI and BSA are screening and calculation tools, not substitutes for clinical judgment. Always correlate with physical examination, patient history, and other assessments. Double-check all chemotherapy calculations independently.

Basic Usage

# Calculate BMI and BSA
python scripts/main.py --weight 70 --height 175
Calculate with drug dosing
python scripts/main.py --weight 70 --height 175 --dose 100
Output as JSON
python scripts/main.py --weight 70 --height 175 --format json --output results.json

# Python 3.7+
No additional packages required (uses standard library)