qtc_fredericia_calculator.py•5.91 kB
"""
QTc Fredericia Calculator
"""
from typing import Dict, Any
from medcalc import (
BaseCalculator,
CalculatorInfo,
Parameter,
ParameterType,
ValidationResult,
CalculationResult,
register_calculator
)
from medcalc.utils import round_number
@register_calculator("qtc_fredericia")
class QTcFredericiaCalculator(BaseCalculator):
"""QTc Fredericia校正计算器实现"""
def get_info(self) -> CalculatorInfo:
return CalculatorInfo(
id=56,
name="QTc Fredericia Calculator",
category="cardiology",
description="Calculate corrected QT interval using Fredericia formula",
parameters=[
Parameter(
name="qt_interval",
type=ParameterType.NUMERIC,
required=True,
unit="msec",
min_value=200,
max_value=800,
description="QT interval in milliseconds"
),
Parameter(
name="heart_rate",
type=ParameterType.NUMERIC,
required=True,
unit="bpm",
min_value=30,
max_value=250,
description="Heart rate in beats per minute"
)
]
)
def validate_parameters(self, parameters: Dict[str, Any]) -> ValidationResult:
"""验证参数"""
errors = []
# 获取参数定义
param_defs = {p.name: p for p in self.get_info().parameters}
# 检查必需参数
for param_name, param_def in param_defs.items():
if param_def.required and param_name not in parameters:
errors.append(f"Missing required parameter: {param_name}")
if errors:
return ValidationResult(is_valid=False, errors=errors)
# 验证数值范围
for param_name, param_def in param_defs.items():
if param_name in parameters:
value = parameters[param_name]
# 验证数值类型和范围
if param_def.type == ParameterType.NUMERIC:
try:
value = float(value)
# 验证范围
if param_def.min_value is not None and value < param_def.min_value:
errors.append(f"{param_name} must be >= {param_def.min_value}, got {value}")
if param_def.max_value is not None and value > param_def.max_value:
errors.append(f"{param_name} must be <= {param_def.max_value}, got {value}")
except (ValueError, TypeError):
errors.append(f"Invalid {param_name}: must be a number")
return ValidationResult(
is_valid=len(errors) == 0,
errors=errors
)
def calculate(self, parameters: Dict[str, Any]) -> CalculationResult:
"""计算QTc Fredericia校正"""
# 获取参数值
param_defs = {p.name: p for p in self.get_info().parameters}
qt_interval = self.get_param_value(parameters, "qt_interval", param_defs["qt_interval"])
heart_rate = self.get_param_value(parameters, "heart_rate", param_defs["heart_rate"])
# 计算RR间期（秒）
rr_interval = 60 / heart_rate
# 使用Fredericia公式计算QTc
# QTc = QT / (RR)^(1/3)
qtc_fredericia = qt_interval / (rr_interval ** (1/3))
# 四舍五入到整数
qtc_fredericia = round_number(qtc_fredericia, 0)
rr_interval_rounded = round_number(rr_interval, 3)
# 生成解释
explanation = "QTc Fredericia calculation:\n\n"
explanation += f"• QT interval: {qt_interval} msec\n"
explanation += f"• Heart rate: {heart_rate} bpm\n"
explanation += f"• RR interval: 60/{heart_rate} = {rr_interval_rounded} seconds\n\n"
explanation += f"Fredericia formula: QTc = QT / (RR)^(1/3)\n"
explanation += f"QTc = {qt_interval} / ({rr_interval_rounded})^(1/3) = {qtc_fredericia} msec"
# 添加QTc解释
if qtc_fredericia < 350:
interpretation = "Short QTc"
clinical_significance = "May indicate short QT syndrome or other conditions"
elif qtc_fredericia <= 440:
interpretation = "Normal QTc"
clinical_significance = "Normal corrected QT interval"
elif qtc_fredericia <= 500:
interpretation = "Prolonged QTc"
clinical_significance = "Borderline prolonged - monitor for arrhythmia risk"
else:
interpretation = "Significantly prolonged QTc"
clinical_significance = "High risk for torsades de pointes and sudden cardiac death"
explanation += f"\n\nInterpretation: {interpretation}"
explanation += f"\nClinical significance: {clinical_significance}"
# 添加与其他公式的比较说明
explanation += "\n\nNote: Fredericia formula (QTc = QT/RR^(1/3)) is considered more accurate than Bazett formula at extreme heart rates"
return CalculationResult(
value=qtc_fredericia,
unit="msec",
explanation=explanation,
metadata={
"qt_interval": qt_interval,
"heart_rate": heart_rate,
"rr_interval": rr_interval_rounded,
"interpretation": interpretation,
"clinical_significance": clinical_significance,
"formula": "Fredericia",
"normal_range": "350-440 msec"
}
)