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Padua Prediction Score Calculator (Barbar 2010)
x402
Padua Prediction Score Calculator (Barbar 2010) is a paid API for AI agents from api.magentlab.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-15).
Calculates the Padua Prediction Score for VTE risk stratification in hospitalized medical patients based on 11 clinical risk factors
Price / call$0.005
Success—
StatusUnknown
How this service works
Barbar 2010 Padua Prediction Score for hospitalized medical patients: cancer 3, previous VTE 3, reduced mobility 3, thrombophilia 3, recent trauma/surgery 2, age >=70 1, heart/respiratory failure 1, acute MI/stroke 1, infection/rheumatologic 1, obesity (BMI>=30) 1, hormonal treatment 1. Max 20. <4 low; >=4 high. Not a diagnosis. Not Caprini, IMPROVE, or Khorana.
Output
Returns the numeric Padua Prediction Score (integer 0–20) and a risk classification: low risk (score <4) or high risk (score ≥4), based on the Barbar 2010 Padua model. Not a clinical diagnosis; intended to assist decision-making for VTE prophylaxis in hospitalized medical patients.
Example use cases
VTE prophylaxis decision for oncology inpatient
“I need the Padua score for a 68-year-old patient admitted with active cancer and reduced mobility — they've been bedridden for 5 days, have a known thrombophilic condition, no prior VTE, no recent surgery, no heart failure, no stroke, no acute infection, BMI is 28, and not on hormonal treatment. Are they high or low risk?”
Post-surgical medical ward admission triage
“Can you calculate the Padua VTE risk score for a 72-year-old patient who had surgery 3 weeks ago, has been on bed rest for 4 days, BMI is 32 so they're obese, no active cancer, no prior blood clots, no thrombophilia, no heart or respiratory failure, no MI or stroke, no infection, and no hormonal treatment?”
Routine VTE screening for elderly medical inpatient
“Run the Padua Prediction Score for a 71-year-old patient who has congestive heart failure but no cancer, no prior VTE, is mobile, no thrombophilia, no recent trauma, no stroke, no active infection, not obese, and not on hormones — I want to know if they're in the high-risk group.”
Technical details
Endpoint
GEThttps://api.magentlab.com/api/calc/paduaWhen to prefer
Use this endpoint when you need the validated Barbar 2010 Padua Prediction Score specifically — not Caprini (surgical patients), IMPROVE, or Khorana (cancer outpatients). This is the standard model for VTE risk stratification in non-surgical hospitalized medical patients. Choose this when a clinical workflow requires a discrete low/high risk classification to guide pharmacological prophylaxis decisions.
Side effects
- Missing required boolean parameters returns a validation error
- Age outside 18–120 range may be rejected or produce unexpected results
- Incorrect data types (e.g. string instead of boolean) cause schema validation failure
- Network or payment (x402) authentication failures result in HTTP 402 or 5xx errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"path": "/api/calc/padua",
"count": 2,
"items": [
{
"score": 0,
"formula": "padua",
"citation": {
"id": "barbar-2010",
"doi": "10.1111/j.1538-7836.2010.04044.x",
"title": "A risk assessment model for the identification of hospitalized medical patients at risk for venous thromboembolism: the Padua Prediction Score",
"source": "J Thromb Haemost. 2010;8(11):2450-2457",
"authors": "Barbar S, Noventa F, Rossetto V, et al."
},
"age_years": 50,
"max_score": 20,
"components": [
{
"factor": "active_cancer",
"points": 0,
"present": false
},
{
"factor": "previous_vte",
"points": 0,
"present": false
},
{
"factor": "reduced_mobility",
"points": 0,
"present": false
},
{
"factor": "thrombophilic_condition",
"points": 0,
"present": false
},
{
"factor": "recent_trauma_or_surgery",
"points": 0,
"present": false
},
{
"value": 50,
"factor": "age_ge_70",
"points": 0,
"present": false
},
{
"factor": "heart_or_respiratory_failure",
"points": 0,
"present": false
},
{
"factor": "acute_mi_or_ischemic_stroke",
"points": 0,
"present": false
},
{
"factor": "acute_infection_or_rheumatologic_disorder",
"points": 0,
"present": false
},
{
"factor": "obesity",
"points": 0,
"present": false
},
{
"factor": "ongoing_hormonal_treatment",
"points": 0,
"present": false
}
],
"disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
"padua_risk": "low",
"formula_expression": "Padua = active_cancer (3) + previous_vte (3) + reduced_mobility (3) + thrombophilic_condition (3) + recent_trauma_or_surgery (2) + age>=70 (1) + heart_or_respiratory_failure (1) + acute_mi_or_ischemic_stroke (1) + acute_infection_or_rheumatologic_disorder (1) + obesity (1) + ongoing_hormonal_treatment (1); max 20; <4 low, >=4 high"
},
{
"score": 0,
"formula": "padua",
"citation": {
"id": "barbar-2010",
"doi": "10.1111/j.1538-7836.2010.04044.x",
"title": "A risk assessment model for the identification of hospitalized medical patients at risk for venous thromboembolism: the Padua Prediction Score",
"source": "J Thromb Haemost. 2010;8(11):2450-2457",
"authors": "Barbar S, Noventa F, Rossetto V, et al."
},
"age_years": 50,
"max_score": 20,
"components": [
{
"factor": "active_cancer",
"points": 0,
"present": false
},
{
"factor": "previous_vte",
"points": 0,
"present": false
},
{
"factor": "reduced_mobility",
"points": 0,
"present": false
},
{
"factor": "thrombophilic_condition",
"points": 0,
"present": false
},
{
"factor": "recent_trauma_or_surgery",
"points": 0,
"present": false
},
{
"value": 50,
"factor": "age_ge_70",
"points": 0,
"present": false
},
{
"factor": "heart_or_respiratory_failure",
"points": 0,
"present": false
},
{
"factor": "acute_mi_or_ischemic_stroke",
"points": 0,
"present": false
},
{
"factor": "acute_infection_or_rheumatologic_disorder",
"points": 0,
"present": false
},
{
"factor": "obesity",
"points": 0,
"present": false
},
{
"factor": "ongoing_hormonal_treatment",
"points": 0,
"present": false
}
],
"disclaimer": "Not a medical device. Deterministic published-formula or published-code output for autonomous agents. A licensed clinician remains responsible for patient care and billing submissions.",
"padua_risk": "low",
"formula_expression": "Padua = active_cancer (3) + previous_vte (3) + reduced_mobility (3) + thrombophilic_condition (3) + recent_trauma_or_surgery (2) + age>=70 (1) + heart_or_respiratory_failure (1) + acute_mi_or_ischemic_stroke (1) + acute_infection_or_rheumatologic_disorder (1) + obesity (1) + ongoing_hormonal_treatment (1); max 20; <4 low, >=4 high"
}
]
}
}Tags
x402
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