A modern TypeScript utility library for glucose, A1C, and diabetic health data. No bloat. No guesswork. Just sharp utilities built for real-world usage.
⚠️ This is a full v1 rewrite - rebuilt from the ground up with strict TypeScript types, runtime guards, and modular, test-driven architecture. No bloat. No guesswork. Just sharp utilities built for real-world usage.
Install from npm:
npm install diabetic-utils
# or
pnpm add diabetic-utils
# or
yarn add diabetic-utilsimport {
estimateGMI,
estimateA1CFromAverage,
mgDlToMmolL,
mmolLToMgDl,
calculateTimeInRange,
formatGlucose,
parseGlucoseString,
isValidGlucoseValue,
getGlucoseLabel,
} from 'diabetic-utils'
estimateGMI(100, 'mg/dL') // → 5.4
estimateGMI('5.5 mmol/L') // → ~12.1
estimateGMI({ value: 100, unit: 'mg/dL' }) // → 5.4
// You can also automatically label glucose values as low, normal, or high:
getGlucoseLabel(60, 'mg/dL') // 'low'
getGlucoseLabel(5.5, 'mmol/L') // 'normal'
getGlucoseLabel(200, 'mg/dL') // 'high'Here are some real-world TypeScript examples to get you started:
// Convert mg/dL to mmol/L
const mmol = mgDlToMmolL(100) // 5.5
// Convert mmol/L to mg/dL
const mgdl = mmolLToMgDl(7.2) // 130
// Estimate A1C from average glucose (mg/dL)
const a1c = estimateA1CFromAverage(120, 'mg/dL') // 5.9
// Estimate A1C from average glucose (mmol/L)
const a1c2 = estimateA1CFromAverage(6.7, 'mmol/L') // 6.7
// Calculate Time-in-Range (TIR)
const readings = [90, 110, 150, 200, 80]
const tir = calculateTimeInRange(readings, 70, 180) // e.g., 60
// Format a glucose value
const formatted = formatGlucose(5.5, 'mmol/L') // '5.5 mmol/L'
// Label glucose status
const status = getGlucoseLabel(65, 'mg/dL') // 'low'
// Parse a glucose string
const { value, unit } = parseGlucoseString('7.2 mmol/L')
// Validate a glucose value
const isValid = isValidGlucoseValue(value, unit) // true
// ...and more!- Zero-bloat, focused utilities
- 100% test coverage
- TypeScript-first, works in JS too
- Perfect for apps, research, and data science
- ✅ Fully tested core utilities with edge case coverage via Vitest
- ✅ Input guards and string parsing for robust DX - protect users from malformed data
- ✅ Strictly typed inputs and outputs using modern TypeScript best practices
- ✅ Predictable, composable function signatures designed for safe integrations
- ✅ Developer-first architecture: clear folder structure, import aliases, and helper separation
- ✅ Built with CGM apps, dashboards, and wearable integrations in mind
- ✅ Readable, ergonomic API that's easy to use in both clinical and wellness-focused tools
- ✅ Performance-focused - zero external runtime dependencies
- ⏱️ More time-in-range (TIR) utilities
- 🧠 Predictive A1C & glucose trends
- 🔁 Advanced glucose unit conversions
- 🏷️ Glucose formatting & status labeling (low, normal, high)
- 🧪 Lab value constants, ranges, and typed result models
- 🌐 Docs site: diabeticutils.com
- Docs: Complete
- Code: Modular, clean, scalable
- Coverage: 100%
- NPM: Live!
Built by @marklearst
Pushing pixels with purpose. Tools for humans.
- X (Twitter): @marklearst
- LinkedIn: Mark Learst
- GitHub: marklearst
- Portfolio: marklearst.com
- Website: diabeticutils.com (coming soon)
💬 Mention or DM me if you use diabetic-utils in your project—I'd love to feature your work!
⭐ Star the repo, share on socials, and help us build the best diabetes data toolkit together!
- This library follows semver for versioning.
- All calculations are based on peer-reviewed medical sources.
(See: NIH A1C, ADA conversion formulas) - Unit tests live in
/testand run automatically via CI. - API will stay stable for all
1.xreleases—any breaking change will be in2.0. - Planned next: [ ] Add more unit conversions, [ ] Support for Type 1-specific metrics.
- Got a formula you want to see? File an issue or PR!
This project is licensed under the MIT License.
© 2024–2025 Mark Learst