Clinical Lab Results Interpreter

Lab data arrives as a testResults array, each entry carrying a testType, value, and date, plus a patientHistory object whose conditions, medications, and allergies later put abnormal readings into clinical context.

Each entry in testResults is evaluated separately because the table runs in loop mode over that array, writing flag, condition, and recommendation back onto every result. Potassium below 3.5 or above 6.0 is 'critical' ('Hypokalemia', 'Hyperkalemia') with urgent electrolyte and cardiac-monitoring guidance, glucose below 70 is critical 'Hypoglycemia' while above 200 is 'abnormal' 'Hyperglycemia', hemoglobin outside 8.5 to 18.0 flags 'Anemia' or 'Polycythemia', and creatinine above 1.5 flags 'Elevated Creatinine' with a prompt to reassess kidney function and dosing.

The thresholds sit at recognized reference-range boundaries: 70 is the standard hypoglycemia line and 3.5 the lower limit of normal potassium, and reserving the 'critical' flag for potassium and low glucose reflects the arrhythmia and neuroglycopenia risks that develop within hours. Automated flagging of this kind supports the critical-results reporting that laboratory accreditation and Joint Commission patient-safety goals require, though the exact cutoffs here are template simplifications of a lab's own critical-value list.

Condition, medication, and result combine in each row: 'diabetes' in patientHistory.conditions plus a glucose-lowering drug ('metformin', 'insulin', 'glipizide') and a glucose above 250 yields 'high-risk' with follow-up inside 48 hours; 'heart_failure' pairs 'furosemide' or 'spironolactone' with a potassium reading above 3.0 to trigger electrolyte replacement and a diuretic review; 'kidney_disease' with creatinine above 2.0 calls for a nephrology consult; and 'warfarin' with an INR above 3.5 holds the next dose and watches for bleeding. There is no default row, so riskAssessment.level only appears when a recognized pattern fires.

Drug-lab interaction checks like these are standard clinical pharmacology: diuretics disturb potassium in both directions, furosemide wasting it and spironolactone retaining it, so heart failure patients on them get the tightest electrolyte scrutiny, and holding warfarin for a supratherapeutic INR above 3.5 matches routine anticoagulation-clinic protocol. The 250 and 2.0 cutoffs are stricter follow-up triggers than the generic flags upstream, which is the point: known chronic disease lowers the bar for action.

Escalation runs on the derived flags: some(testResults, #.flag == 'critical') maps straight to 'urgent', riskAssessment.level == 'high-risk' to 'high', any 'abnormal' flag to 'moderate', and the empty final row to 'routine'. Row order encodes precedence, so a critical lab value outranks the patient-context assessment no matter what it concluded.

Collapsing everything into a single four-tier urgencyLevel mirrors how critical-value escalation works in practice, where a panic value always takes priority over chronic-disease context, and it gives downstream consumers one field to route on. Four tiers rather than a numeric score is a sensible business choice that keeps the follow-up table trivially auditable.

Timeframes attach last: 'urgent' cases require 'Immediate provider notification required' within '24 hours', 'high' recommends notification within '72 hours', 'moderate' folds into routine review inside '1 week', and 'routine' waits for the 'Next scheduled visit'. Both outputs land under followUp, giving the caller an action and a deadline in one place.

Putting explicit windows on follow-up reflects how clinics operationalize results-management policies, where notification and review times are documented and auditable rather than left to individual judgment. The specific 24-hour and 72-hour windows are program-level choices, tightened or relaxed per organization rather than set by regulation.