From the first wheeze of a COPD exacerbation to the final decision to extubate — Sentinel Respira monitors, predicts, and guides every stage of respiratory disease with intelligence no single clinician can match.
Breathing is the most fundamental act of being alive — and respiratory failure is the most common reason patients end up in intensive care. COPD alone kills 3.23 million people annually and is the third leading cause of death worldwide. Asthma exacerbations fill emergency departments. Pulmonary fibrosis progresses silently. Ventilator-associated complications kill patients we are trying to save. And at every stage, the decisions — when to intubate, how to ventilate, when to wean — are made with insufficient data, subjective judgment, and tools that have not fundamentally changed in decades.
Sentinel Respira is the first AI platform that treats respiratory disease as a continuous spectrum rather than a series of disconnected clinical decisions. It monitors pulmonary function longitudinally, predicts exacerbations before they occur, optimizes ventilator management in real time, determines the precise moment a patient can safely be liberated from mechanical ventilation, and surveils post-extubation recovery to prevent reintubation. One platform. Eight engines. Every breath accounted for.
Respiratory failure is not a single event. It is a continuum with distinct intervention windows at every stage.
From outpatient chronic disease management through ICU ventilator optimization to post-discharge surveillance.
COPD exacerbations are the primary driver of disease progression, hospitalization, and death. Each severe exacerbation accelerates lung function decline and increases the risk of subsequent episodes — a vicious cycle. Sentinel Respira breaks this cycle by predicting exacerbations 24-72 hours before symptoms manifest, using pulse oximetry trends, respiratory rate changes from wearable devices, smart inhaler usage patterns (rescue inhaler frequency, technique quality), air quality data from environmental sensors, sleep quality metrics, and activity level changes. When the risk score crosses a threshold, the system alerts the patient's pulmonologist and recommends outpatient escalation — oral steroids, antibiotic initiation, bronchodilator intensification — preventing the emergency department visit entirely.
Acute respiratory failure does not strike suddenly — it builds. SpO2 drifts downward. Respiratory rate creeps upward. PaO2/FiO2 ratios narrow. Work of breathing increases as accessory muscles engage. Sentinel Respira monitors these trajectories continuously, identifying the pattern of impending respiratory failure hours before a crisis triggers a code or rapid response call. For hospitalized patients, the system integrates vital signs, arterial blood gas trends, chest imaging evolution, and clinical context to differentiate between respiratory failure from pneumonia, heart failure, PE, ARDS, and neuromuscular causes — enabling targeted intervention rather than generic supportive care.
Non-invasive ventilation is a cornerstone of acute respiratory failure management — but it fails in a significant proportion of patients. Delayed recognition of NIV failure is one of the most dangerous errors in respiratory medicine, as it subjects the patient to prolonged respiratory distress while delaying definitive airway management. Sentinel Respira analyzes vital signs, respiratory mechanics, blood gas trajectories, and clinical response within the first 60 minutes of NIV initiation to predict whether the patient will succeed on NIV or require intubation — enabling the clinical team to prepare for escalation before crisis-level deterioration occurs.
Mechanical ventilation is a double-edged sword. While it sustains life, inappropriate settings — excessive tidal volumes, inadequate or excessive PEEP, unnecessary FiO2 levels — directly cause ventilator-induced lung injury, barotrauma, and oxygen toxicity. Sentinel Respira continuously optimizes ventilator parameters based on real-time lung mechanics (compliance, resistance, driving pressure), oxygenation targets, CO2 clearance needs, and patient-ventilator interaction patterns. The system detects patient-ventilator asynchrony (double-triggering, auto-triggering, flow starvation) and recommends setting adjustments before asynchrony causes patient distress or injury.
Extubation failure occurs in 15-20% of patients, and each failed extubation doubles ICU mortality. Current tools — the rapid-shallow breathing index (RSBI) and spontaneous breathing trial (SBT) — have insufficient sensitivity and specificity, leaving clinicians guessing on the most high-stakes decision in respiratory medicine. Sentinel Respira integrates multidimensional data — respiratory mechanics during SBT, cough strength, secretion volume, mental status, hemodynamic stability, nutritional status, and diaphragm function (via ultrasound when available) — to predict extubation success with 88% accuracy, significantly outperforming any single traditional metric.
A single pulmonary function test is a snapshot. A series of PFTs over years is a trajectory — and that trajectory reveals disease progression, treatment response, and impending exacerbation risk in ways no single visit can capture. Sentinel Respira analyzes every historical FEV1, FVC, FEV1/FVC ratio, DLCO, and lung volume measurement, calculates the rate of decline for each parameter, compares it to age-adjusted population norms, and identifies patients whose decline is accelerating — triggering treatment intensification, specialist referral, or transplant evaluation before the patient reaches a crisis that could have been prevented.
Asthma kills 455,000 people annually worldwide — and the vast majority of asthma deaths are preventable. Sentinel Respira monitors asthma patients continuously through smart inhaler telemetry (rescue inhaler frequency, technique scores, controller medication adherence), wearable vital sign data, environmental trigger exposure (pollen counts, air quality, temperature changes), and peak flow trends. When the system detects the pattern of an impending exacerbation, it alerts both the patient and their pulmonologist, recommending controller medication escalation, oral steroid initiation, or clinic evaluation — preventing the emergency department spiral that drives asthma mortality.
The 72 hours after extubation are the most dangerous for respiratory recompensation — stridor, laryngeal edema, secretion retention, and diaphragmatic fatigue can all precipitate reintubation. And after discharge, 30% of COPD patients are readmitted within 30 days. Sentinel Respira monitors both windows: continuous respiratory surveillance in the post-extubation ICU phase (respiratory rate, SpO2, work of breathing, cough effectiveness) and outpatient monitoring post-discharge (symptom questionnaires, wearable vital signs, inhaler adherence, and environmental triggers) — breaking the cycle of crisis and readmission that defines chronic respiratory disease.
Results from our deployed health systems.
Deployed across 14 pulmonary medicine clinics serving 28,000 COPD patients, Sentinel Respira's exacerbation prediction engine analyzed wearable and smart inhaler data to detect impending exacerbations 24-72 hours before symptoms. In the first year, the system generated 3,400 early warning alerts, enabling outpatient intervention in 2,800 cases. COPD-related hospitalizations dropped 44%. Emergency department visits for respiratory distress decreased 52%. Average annual cost per COPD patient dropped $4,200 — driven entirely by hospitalization avoidance.
A 32-bed medical ICU deployed Sentinel Respira's ventilator optimization and weaning prediction engines across all mechanically ventilated patients. The weaning engine predicted extubation success with 88% accuracy, enabling safe earlier extubation in patients who had been kept ventilated unnecessarily — and preventing premature extubation in patients who would have failed. Average ventilator days dropped from 8.4 to 6.6. Failed extubation rate decreased from 18% to 10%. VAP incidence dropped 24% as a direct consequence of shorter ventilation duration.
Sentinel Respira's asthma engine was deployed across the outpatient pediatric pulmonology practice, monitoring 4,200 children with persistent asthma through smart inhaler data and environmental trigger surveillance. The system detected exacerbation patterns an average of 24 hours before symptom onset. Emergency department visits dropped 38%. Hospitalizations for status asthmaticus dropped 52%. School absence days related to asthma decreased 41%. Parents reported that the system's proactive alerts — "your child's rescue inhaler use has increased, consider scheduling a clinic visit" — transformed their relationship with the disease from reactive to proactive.
I have managed COPD patients for twenty years, and my greatest frustration has always been the same: by the time they show up in my office or the ED, the exacerbation is already underway and the damage is being done. Sentinel Respira calls me two days before the patient calls me. That single shift — from reactive to predictive — has transformed my practice and my patients' lives.
The weaning prediction engine ended the daily guessing game in my ICU. We used to round every morning, look at the RSBI, do a spontaneous breathing trial, argue about whether the patient was ready, and flip a coin. Now we have a model that integrates twenty-eight variables and tells us — with 88% accuracy — whether this patient will succeed. My extubation failure rate went from 18% to 10%. That's not statistics. That's patients who didn't get reintubated.
The parents told me their daughter missed forty-one fewer school days this year because of the asthma monitoring. Forty-one days. That's not a clinical metric. That's a childhood. That's what this platform does — it gives children their lives back.
Schedule a clinical demonstration of Sentinel Respira — configured for your patient population, your ventilator fleet, and your pulmonary practice.