suspicion-of-infection

Detect suspected infection events by linking antibiotic administrations to culture timing.

40|17|Updated Oct 27, 2025
One-click install
npx skills add https://github.com/hannesill/m4 --skill suspicion-of-infection
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: suspicion-of-infection
Source: https://github.com/hannesill/m4/tree/main/src/m4/skills/clinical/suspicion-of-infection
Command: npx skills add https://github.com/hannesill/m4 --skill suspicion-of-infection

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This concept identifies when clinicians suspected infection based on antibiotic administration and culture timing, enabling cohort construction for Sepsis-3 and infection research.

Core Features & Use Cases

  • Detect suspected infection events by linking antibiotic administrations to culture collections within defined windows (72 hours before antibiotic and 24 hours after).
  • Support Sepsis-3 cohorts, antibiotic stewardship studies, time-to-treatment analyses, and infection onset timing research.
  • Provide dataset-agnostic guidance for implementing the infection-suspicion logic across MIMIC-IV, eICU, and similar ICU datasets.

Quick Start

Run the suspicion_of_infection workflow on your dataset to identify suspected infection events by matching antibiotic administrations with cultures within the defined windows.

Frequently Asked Questions about suspicion-of-infection

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify suspected infection events in MIMIC-IV for Sepsis-3 cohort construction?

Identify suspected infection events in MIMIC-IV by linking antibiotic administration records to culture collection timings. This Skill matches antibiotics to cultures within a 72-hour pre-antibiotic and 24-hour post-antibiotic window to support Sepsis-3 cohort construction.

What is the time window for linking antibiotics to cultures when detecting suspected infections?

The time window for detecting suspected infections links antibiotic administrations to cultures collected up to 72 hours before and 24 hours after the antibiotic was given. This defined window ensures accurate temporal matching for infection onset research.

Can I use this suspicion of infection logic with eICU datasets or is it limited to MIMIC-IV?

You can use this suspicion of infection logic with eICU datasets as well as MIMIC-IV. It provides dataset-agnostic guidance for implementing the antibiotic and culture matching rules across similar ICU datasets.

How do I handle non-positive cultures and one-row-per-antibiotic matching in clinical data derivation?

Handle non-positive cultures and one-row-per-antibiotic matching during clinical data derivation by enforcing specific culture-before and culture-after rules. The process ensures each antibiotic entry is matched correctly without duplicating records for non-positive culture results.

Does this approach support antibiotic stewardship studies and time-to-treatment analyses in ICU datasets?

This approach supports antibiotic stewardship studies and time-to-treatment analyses in ICU datasets by accurately timestamping suspected infection events. Linking antibiotic administrations to culture collections provides the temporal data needed for these clinical research workflows.

Why use antibiotic administration timing instead of diagnosis codes to identify suspected infections in clinical research?

Use antibiotic administration timing instead of diagnosis codes to identify suspected infections because medication and culture data reflect real-time clinical decision-making. This Sepsis-3 aligned method captures actual suspected infection events rather than relying on retrospective billing codes.