Clarion Sentinel continuously monitors every patient in your facility — detecting life-threatening conditions hours before traditional methods, enabling intervention before the crisis.
Every year, 400,000 hospitalized patients die from conditions that were detectable — but not detected in time. Sepsis. Cardiac arrest. Respiratory failure. Acute kidney injury. The data was in the chart. The signals were in the vitals. The pattern was visible — to a machine learning model trained to look for it. But no human can continuously monitor 200 data points across 400 patients simultaneously. Sentinel can.
Clarion Sentinel is a suite of ten purpose-built AI detection engines, each trained on millions of de-identified patient encounters, each validated against peer-reviewed clinical evidence, and each designed to give clinicians the one thing that saves lives above all else: time.
Each engine operates independently but shares a unified patient context — so a sepsis alert enriches the AKI model, and a cardiac rhythm change informs the deterioration engine.
Sepsis kills 270,000 Americans annually and accounts for one-third of all in-hospital deaths. Survival drops 7.6% for every hour treatment is delayed after onset. Sentinel's sepsis engine continuously monitors vital sign trajectories, lab trends, medication responses, nursing flowsheet entries, and micro-changes in heart rate variability to detect the earliest inflammatory cascade — hours before traditional SIRS criteria or qSOFA scores trigger.
The model was trained on 18 million de-identified sepsis and non-sepsis encounters, validated externally across 42 hospitals, and published in three peer-reviewed journals. It achieves a specificity that virtually eliminates false-alarm fatigue — the primary reason existing sepsis alerts fail.
In-hospital cardiac arrest occurs in 8.27 per 1,000 hospitalizations, with only 25% survival to discharge. Most arrests are preceded by subtle physiological deterioration — changes in heart rate variability, respiratory patterns, blood pressure trajectories, and lab values — that are individually unremarkable but collectively predictive. Sentinel's cardiac engine synthesizes these signals continuously, generating a risk score that enables rapid response activation before pulseless arrest occurs.
Acute kidney injury affects 20% of hospitalized patients and is independently associated with 3.5× higher mortality. By the time serum creatinine rises enough to meet KDIGO criteria, significant renal damage has already occurred. Sentinel's AKI engine analyzes urine output patterns, hemodynamic trends, nephrotoxic medication exposure, fluid balance, and baseline renal function to predict AKI 48 hours before lab confirmation — enabling nephroprotective interventions while the injury is still reversible.
In stroke care, every minute of delay costs 1.9 million neurons. Sentinel's stroke engine analyzes CT and CTA imaging in under 90 seconds, identifies large vessel occlusions with 96.2% accuracy, and simultaneously triages the case to the neurointerventional team — cutting door-to-needle time by an average of 26 minutes. The system also monitors post-stroke patients for hemorrhagic transformation and neurological deterioration.
Pulmonary embolism is the third leading cause of cardiovascular death and is missed in up to 33% of cases on initial presentation. Sentinel's PE engine analyzes CT pulmonary angiography in real time, detects clot burden with 94.8% accuracy, quantifies right ventricular strain markers, and immediately escalates saddle and massive PE to the on-call team — even when the radiologist hasn't opened the study yet.
Sentinel's imaging engine analyzes chest CT, mammography, colonoscopy video, and dermoscopic images to detect malignancy at its earliest stage. The system operates as a second reader — flagging suspicious findings for radiologist review, prioritizing worklist queues by urgency, and tracking incidental findings that might otherwise be lost to follow-up. For lung cancer screening on low-dose CT, the engine achieves 94.3% sensitivity with a false-positive rate 40% lower than unaided interpretation.
50% of diabetic patients are not receiving recommended annual retinal exams, and diabetic retinopathy is the leading cause of blindness in working-age adults. Sentinel's retinal engine enables point-of-care screening during a routine primary care visit — analyzing fundus photographs in under 60 seconds to detect referable diabetic retinopathy, diabetic macular edema, and glaucoma risk. The system is FDA-cleared for autonomous diagnostic decisions, meaning it provides a clinical-grade result without requiring an ophthalmologist to read the scan.
Undetected atrial fibrillation is responsible for 15-20% of all ischemic strokes. Sentinel's arrhythmia engine provides continuous ECG analysis for every monitored patient, classifying 16 distinct rhythm types with 99.2% accuracy — including paroxysmal AFib episodes lasting fewer than 30 seconds that conventional monitoring misses. The system also detects subtle ST-segment changes suggestive of acute coronary syndrome, QT prolongation from medication effects, and emerging conduction abnormalities.
Unplanned intubations carry twice the mortality risk of planned airway management. Sentinel's respiratory engine monitors SpO2 trends, respiratory rate variability, end-tidal CO2, work of breathing indicators, and ABG trajectories to predict respiratory failure 5.1 hours before clinical decompensation. For ventilated patients, the system continuously assesses readiness for extubation — analyzing spontaneous breathing trial parameters, cuff leak data, and physiological reserve — to recommend optimal weaning windows and reduce ventilator days.
Adverse drug events injure 1.3 million Americans annually and are the fourth leading cause of death in the US. Traditional drug interaction checkers are binary — they flag known interactions without considering the patient's specific physiology, renal clearance, hepatic metabolism, genomic profile, or the cumulative risk of polypharmacy. Sentinel's medication engine analyzes the patient's entire medication profile against their individual pharmacokinetic and pharmacodynamic parameters — including organ function, weight, age, genetic polymorphisms, and concurrent disease states — to identify adverse event risk before it manifests clinically.
Each engine operates independently but shares context through Clarion's unified patient data layer — so signals compound across systems.
Every Sentinel engine meets the highest standard of clinical evidence — not just internal testing, but independent, external, peer-reviewed validation.
Schedule a clinical demonstration of Sentinel configured for your patient population, your acuity level, and your care protocols.