# Padua Prediction Score Calculator (Barbar 2010) > 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 ## Facts - Endpoint: GET https://api.magentlab.com/api/calc/padua - Price: $0.005/call - Payment: x402 - Status: unknown - Last checked: 2026-09-15 - Activations on Zero: 0 - Tags: x402 - Canonical page: https://www.zero.xyz/c/padua-prediction-score-calculator-barbar-2010-ae437abb - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_aRAAckYcuLM1wRRRJWg2A Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently. ## How to call it through Zero Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`): ```sh zero fetch --capability padua-prediction-score-calculator-barbar-2010-ae437abb ``` Example prompt: Calculate the Padua Prediction Score for a 74-year-old hospitalized patient who has active cancer and reduced mobility (bedridden for 4 days), no previous VTE, no thrombophilia, no recent surgery, no heart or respiratory failure, no recent MI or stroke, no acute infection or rheumatologic disorder, not obese, and not on hormonal treatment. ## When to prefer this 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. ## Known failure modes - 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 ## 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. ## Request schema (JSON Schema) ```json { "type": "object", "$schema": "https://json-schema.org/draft/2020-12/schema", "required": [ "input" ], "properties": { "input": { "type": "object", "required": [ "type", "method" ], "properties": { "type": { "type": "string", "const": "http" }, "method": { "enum": [ "GET", "HEAD", "DELETE" ], "type": "string" }, "headers": { "type": "object", "additionalProperties": { "type": "string" } }, "queryParams": { "type": "object", "required": [ "age", "active_cancer", "previous_vte", "reduced_mobility", "thrombophilic_condition", "recent_trauma_or_surgery", "heart_or_respiratory_failure", "acute_mi_or_ischemic_stroke", "acute_infection_or_rheumatologic_disorder", "obesity", "ongoing_hormonal_treatment" ], "properties": { "age": { "type": "integer", "description": "Age in years (18-120). Scores 1 when age ≥70; 69 does not score." }, "obesity": { "type": "boolean", "description": "Obesity as assigned by the caller (BMI ≥30). true or false. magent does not take height or weight. 1 point if true." }, "previous_vte": { "type": "boolean", "description": "Previous VTE as assigned by the caller (exclude superficial vein thrombosis). true or false. 3 points if true." }, "active_cancer": { "type": "boolean", "description": "Active cancer as assigned by the caller (local or distant metastases and/or chemotherapy or radiotherapy in the previous 6 months). true or false. 3 points if true." }, "reduced_mobility": { "type": "boolean", "description": "Reduced mobility as assigned by the caller (bedrest with bathroom privileges ≥3 days). true or false. 3 points if true." }, "thrombophilic_condition": { "type": "boolean", "description": "Known thrombophilic condition as assigned by the caller. true or false. 3 points if true." }, "recent_trauma_or_surgery": { "type": "boolean", "description": "Recent trauma and/or surgery as assigned by the caller (≤1 month). true or false. 2 points if true." }, "ongoing_hormonal_treatment": { "type": "boolean", "description": "Ongoing hormonal treatment. true or false. 1 point if true." }, "acute_mi_or_ischemic_stroke": { "ty … (truncated) ``` ## Response schema (JSON Schema) ```json { "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 … (truncated) ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/padua-prediction-score-calculator-barbar-2010-ae437abb/health.json - [Zero catalog index](https://www.zero.xyz/llms.txt) - [Other services from api.magentlab.com](https://www.zero.xyz/host/api.magentlab.com/llms.txt)