Monitoring Module

Track CPAP/BiPAP therapy adherence and treatment effectiveness

Overview

The Monitoring module tracks patient adherence to PAP (Positive Airway Pressure) therapy and measures treatment effectiveness through residual apnea indices. It combines technical device data with clinical outcomes to ensure successful therapy adaptation.

Model: Monitoreo
Location: apps/exams/models.py:8-64

Monitoring data is automatically linked to the patient’s active admission to ensure proper data isolation between treatment cycles.

---

Core Data Fields

Adherence Metrics

uso_diario · DecimalField · required

Daily Usage Percentage - Percentage of days the patient used their device

• Format: Decimal (5 digits, 2 decimal places)
• Range: 0.00 - 100.00
• Form Label: “Porcentaje(%) Uso Diario”
• Clinical Significance: Primary adherence indicator

dias_uso_horas_4 · DecimalField · required

Days with >4 Hours Usage - Percentage of days with at least 4 hours of device use

• Format: Decimal (5 digits, 2 decimal places)
• Range: 0.00 - 100.00
• Form Label: “Porcentaje(%) días uso > 4 horas”
• Clinical Standard: Medicare and insurance typically require ≥4 hours/night for 70% of nights

horas_uso_diario · DecimalField · required

Average Daily Usage Hours - Mean hours of device use per night

• Format: Decimal (5 digits, 2 decimal places)
• Unit: Hours
• Form Label: “Horas de uso diario”
• Target: ≥4 hours minimum, 6-8 hours optimal

Treatment Effectiveness

hipopnea_basal · DecimalField · required

Baseline AHI - Original apnea-hypopnea index from basal polysomnography

• Format: Decimal (5 digits, 2 decimal places)
• Form Label: “Indice de apneas BASAL”
• Source: Automatically copied from PolisomnografiaBasal.iah
• Help Text: “Copiado de la PSG Basal al momento del registro”
• UI Behavior: Read-only field (pre-filled from basal study)

hipopnea_residual · DecimalField · required

Residual AHI - Current apnea-hypopnea index while using PAP therapy

• Format: Decimal (5 digits, 2 decimal places)
• Form Label: “Indice de apneas RESIDUAL”
• Clinical Significance: Measures how well treatment controls apnea events
• Target: < 5 events/hour indicates effective therapy

porcentaje_correccion · DecimalField · required

Correction Percentage - Percentage improvement in apnea index

• Format: Decimal (5 digits, 2 decimal places)
• Calculation: ((Basal - Residual) / Basal) × 100
• Form Label: “Porcentaje de corrección”
• Help Text: “Calculado automáticamente: ((Basal - Residual) / Basal) * 100”
• UI Behavior: Auto-calculated, read-only field
• Interpretation: Higher is better (>80% is excellent)

---

Device Settings

Ventilatory Mode

modo_ventilatorio · CharField · required

Type of positive airway pressure therapy being monitored

Available Choices:

• CPAP - Continuous Positive Airway Pressure (single pressure level)
• BPAP - Bilevel Positive Airway Pressure (two pressure levels)
• BPAP ST - BiPAP with Spontaneous/Timed backup rate

Form Label: “Modo Ventilatorio”

Pressure Settings

presion_ipap · DecimalField · required

Inspiratory Positive Airway Pressure - Pressure delivered during inhalation

• Format: Decimal (5 digits, 2 decimal places)
• Unit: cmH₂O
• Form Label: “Presion IPAP”
• Range: Typically 4-20 cmH₂O
• Note: For CPAP mode, this is the single continuous pressure

presion_epap · DecimalField

Expiratory Positive Airway Pressure - Pressure maintained during exhalation

• Format: Decimal (5 digits, 2 decimal places)
• Unit: cmH₂O
• Form Label: “Presion EPAP”
• Range: Typically 4-15 cmH₂O
• Optional: Only applicable for BiPAP modes (not used for CPAP)

frecuencia_respiratoria · IntegerField

Respiratory Rate - Backup breaths per minute for BiPAP ST mode

• Unit: Respirations per minute (rpm)
• Form Label: “Frecuencia Respiratoria”
• Help Text: “Respiraciones por minuto (rpm)”
• Optional: Only applicable for BiPAP ST mode
• Typical Range: 8-20 rpm

---

Mask Interface

mascara_cpap · CharField · required

Type of mask interface the patient is using

Available Choices:

• PILLOW NASAL - Nasal pillow (minimalist, inserted into nostrils)
• NASAL - Nasal mask (covers nose only)
• ORONASAL - Full face mask (covers nose and mouth)

Form Label: “Máscara de CPAP” Display Labels:

• PILLOW NASAL → “Pillow nasal”
• NASAL → “Nasal”
• ORONASAL → “Oronasal”

tamano_mascara · CharField · required

Size of the mask fitted to the patient

Available Choices:

• SMALL - Small
• MEDIUM - Medium
• LARGE - Large

Form Label: “Tamaño de Máscara”

Mask type and size tracking is crucial for troubleshooting adherence issues. Ill-fitting masks are a common cause of poor compliance.

---

Advanced Monitoring

etco2_promedio · DecimalField

End-Tidal CO₂ Average - Average carbon dioxide levels at the end of exhalation

• Format: Decimal (5 digits, 2 decimal places)
• Unit: mmHg
• Form Label: “EtCO2 Promedio”
• Optional: Advanced monitoring for hypoventilation concerns
• Normal Range: 35-45 mmHg
• Clinical Use: Monitors for CO₂ retention in complex cases

---

Relationships

ingreso · ForeignKey

Links to the patient’s active admission record

Related Name: monitoreos
On Delete: CASCADE

registrado_por · ForeignKey

User who registered this monitoring record

Related Name: monitoreos_registrados
On Delete: SET_NULL

created_at · DateTimeField

Timestamp when this monitoring record was created

Auto-generated: Automatically set on record creation

---

Registration Workflow

Dual-Form Interface

View: register_monitoreo (apps/exams/views.py:62-117)

The monitoring registration page handles two forms simultaneously:

1. Technical Monitoring Form (MonitoreoForm) - Device data and adherence metrics
2. Follow-up Notes Form (SeguimientoAdaptacionForm) - Clinical observations

def register_monitoreo(request, patient_id):
    patient = get_object_or_404(Patient, id=patient_id)
    ingreso_actual = patient.ingresos.filter(estado='ACTIVO').first()
    
    # Auto-populate basal IAH from last polysomnography
    psg = PolisomnografiaBasal.objects.filter(
        ingreso=ingreso_actual
    ).last()
    valor_basal = psg.iah if psg else 0
    
    form = MonitoreoForm(initial={'hipopnea_basal': valor_basal})
    seguimiento_form = SeguimientoAdaptacionForm()
    active_tab = 'tecnico'
    
    if request.method == 'POST':
        # Technical monitoring form submitted
        if 'btn_monitoreo' in request.POST:
            form = MonitoreoForm(request.POST)
            if form.is_valid():
                monitoreo = form.save(commit=False)
                monitoreo.ingreso = ingreso_actual
                monitoreo.registrado_por = request.user
                monitoreo.save()
                return redirect('patient_clinical', patient_id=patient.id)
            active_tab = 'tecnico'
        
        # Follow-up notes form submitted
        elif 'btn_contacto' in request.POST:
            seguimiento_form = SeguimientoAdaptacionForm(request.POST)
            if seguimiento_form.is_valid():
                seguimiento = seguimiento_form.save(commit=False)
                seguimiento.ingreso = ingreso_actual
                seguimiento.registrado_por = request.user
                seguimiento.save()
                return redirect('patient_clinical', patient_id=patient.id)
            active_tab = 'contacto'

Key Workflow Features

Automatic Basal IAH Retrieval:

• System automatically fetches the last basal polysomnography IAH
• Pre-fills hipopnea_basal field (read-only in UI)
• Located at apps/exams/views.py:77-79

Tab State Preservation:

• active_tab variable maintains which form was submitted
• Ensures users stay on the correct tab if validation fails
• Technical form errors keep “tecnico” tab active
• Follow-up form errors keep “contacto” tab active

Button-Based Form Detection:

• btn_monitoreo button submits technical monitoring data
• btn_contacto button submits follow-up notes
• Prevents form submission conflicts on same page

---

Clinical Interpretation

Adherence Guidelines

Excellent Adherence

70% or more nights with 4+ hours use, averaging 6-8 hours per night. Meets insurance compliance requirements.

Poor Adherence

Less than 50% of nights with 4+ hours use, averaging under 3 hours per night. Requires intervention and troubleshooting.

Treatment Effectiveness Thresholds

Residual AHI	Interpretation	Action Required
< 5	Excellent control	Continue current therapy
5-10	Adequate control	Monitor closely, minor adjustments if symptoms persist
10-15	Suboptimal control	Pressure adjustment or mask refit needed
> 15	Poor control	Urgent evaluation - check mask leak, pressure settings, compliance

Correction Percentage

# Formula (automatically calculated)
porcentaje_correccion = ((hipopnea_basal - hipopnea_residual) / hipopnea_basal) * 100

Example:

• Basal AHI: 32 (severe sleep apnea)
• Residual AHI: 3 (excellent control)
• Correction: ((32 - 3) / 32) × 100 = 90.6%

A correction percentage of ≥80% indicates highly effective therapy. Lower percentages suggest the need for pressure adjustments, mask refitting, or evaluation for persistent central apnea.

---

Common Issues and Troubleshooting

Low Adherence Despite Good Residual AHI

Possible Causes:

• Mask discomfort or air leak
• Claustrophobia
• Aerophagia (air swallowing)
• Bed partner concerns

Actions:

• Check mask fit and size (see mascara_cpap and tamano_mascara fields)
• Consider different mask type
• Add humidification
• Psychology consultation for anxiety (see Psychology Module)

Good Adherence but High Residual AHI

Possible Causes:

• Insufficient pressure (IPAP/EPAP too low)
• Significant mask leak
• Positional apnea
• Central sleep apnea component

Actions:

• Increase CPAP/BiPAP pressures
• Refit mask or change size
• Consider switching CPAP → BiPAP or BiPAP → BiPAP ST
• Pulmonology referral (see Pulmonology Module)

Elevated EtCO2

Clinical Significance:

• EtCO2 > 45 mmHg suggests hypoventilation
• Common in obesity hypoventilation syndrome (OHS)
• May require BiPAP ST with backup rate

Actions:

• Increase pressure support (IPAP - EPAP difference)
• Add backup respiratory rate
• Consider volumetric modes
• Evaluate for supplemental oxygen

---

Data Retrieval

View: patient_clinical (apps/exams/views.py:28)

# Get all monitoring records for active admission
monitoreos = Monitoreo.objects.filter(
    ingreso=ingreso_actual
).order_by('-id')

Monitoring records are filtered by the patient’s active admission and ordered by ID (most recent first) to show the latest adherence data at the top.

---

Related Modules

Polysomnography

Basal IAH automatically pulled from basal study

Medical Equipment

Device and mask specifications tracked here

Psychology

Mental health support for adherence issues