# Expected Output: Wellness Trend Analysis This document shows the expected agent output when running the trend analysis prompt against the Alex Rivera reference patient pod. --- # Wellness Trend Analysis Report **Patient:** Alex Rivera, 52M **Analysis Period:** 2026-01-20 to 2026-02-18 (30 days) **Data Sources:** Apple Watch Series 9 (HealthKit), Omron Evolv (Bluetooth BP monitor) **Clinical Context:** Essential Hypertension (on Lisinopril 20 mg), Type 2 Diabetes (on Metformin 1000 mg), Hyperlipidemia (on Atorvastatin 40 mg) --- ## 1. Data Stream Summaries ### Heart Rate (Resting) `[Device: Apple Watch Series 9]` | Statistic | Value | |-----------|-------| | Mean | 68.2 bpm | | Std Dev | 5.8 bpm | | Min | 58 bpm (2026-01-27) | | Max | 82 bpm (2026-02-07) | | Range | 24 bpm | | Samples/day | 120-168 (avg ~144) | **Trend:** Stable. First-half average (68.0 bpm) and second-half average (68.4 bpm) are essentially identical. No upward or downward drift. **Weekly pattern:** Resting HR tends to be lower on weekends/rest days (58-64 bpm) and higher midweek (72-82 bpm), likely reflecting higher physical and psychological stress during the workweek. **Outlier:** 82 bpm on 2026-02-07 (Friday) is the highest reading. This coincides with the lowest sleep quality that week (5.9 hours, Poor quality), suggesting sleep deprivation drove the elevated HR. **Confidence: HIGH** -- Continuous device monitoring with 120-168 samples/day. Consistent device wear indicated by daily data without gaps. ### Blood Pressure `[Device: Omron Evolv]` | Statistic | Systolic | Diastolic | |-----------|----------|-----------| | Mean | 129.3 mmHg | 80.0 mmHg | | Std Dev | 5.3 mmHg | 3.7 mmHg | | Min | 120 mmHg | 74 mmHg | | Max | 138 mmHg | 86 mmHg | | Range | 18 mmHg | 12 mmHg | **Trend:** Stable with oscillating pattern. First-half systolic average (129.5) vs second-half (129.1) shows no meaningful change. BP oscillates between 120-130 on good days and 132-138 on higher days without a clear directional trend. **Pattern:** Higher BP readings (>134 mmHg systolic) appear to cluster on days following poor sleep or low activity. The two highest readings (138 on 2026-01-24, 137 on 2026-02-07) both follow days with below-average activity. **Clinical context:** Alex takes Lisinopril 20 mg for hypertension. His systolic BP ranges consistently above the 120 mmHg optimal threshold but below the 140 mmHg Stage 2 hypertension cutoff. This represents "controlled but not optimized" hypertension. **Confidence: MEDIUM** -- Single daily measurement from a validated home BP device. While the device is medical-grade (Omron Evolv), one reading per day captures only morning BP. Intra-day variability is not measured. ### Activity `[Device: Apple Watch Series 9]` | Metric | Mean | Min | Max | |--------|------|-----|-----| | Steps/day | 7,207 | 4,089 | 11,987 | | Active energy | 306 kcal | 198 kcal | 498 kcal | | Exercise min | 20.1 min | 0 min | 45 min | | Stand hours | 9.4 hrs | 6 hrs | 12 hrs | **Trend:** Stable with strong weekly cyclicality. **Weekly pattern (strongly visible):** - **Gym days** (typically Mon, Wed, or Thu): 8,000-12,000 steps, 30-45 exercise minutes - **Non-gym weekdays**: 5,000-8,000 steps, 10-20 exercise minutes - **Weekends**: 4,000-5,200 steps, 0-5 exercise minutes **Notable observations:** - Zero-exercise days: 6 out of 30 days (20%) had 0 exercise minutes, all on weekends or Fridays - Weekend activity drop is significant: 60% reduction in steps vs peak gym days - The pattern is consistent over the 30-day window with no decline or improvement trend **Confidence: HIGH** -- Continuous accelerometer and heart rate monitoring throughout the day. Steps and active energy are highly accurate from wrist-worn devices during daily wear. ### Sleep `[Device: Apple Watch Series 9]` | Statistic | Value | |-----------|-------| | Mean duration | 7.10 hours | | Std Dev | 0.83 hours | | Min | 5.5 hours (2026-01-24) | | Max | 8.5 hours (2026-01-26) | | Quality: Excellent | 4 nights (13%) | | Quality: Good | 13 nights (43%) | | Quality: Fair | 10 nights (33%) | | Quality: Poor | 3 nights (10%) | **Trend:** Stable average, but with notable periodic dips. **Pattern:** Poor sleep nights (5.5-5.9 hours) occur on a roughly weekly cycle, clustering on Thursdays and Fridays: - 2026-01-24 (Friday): 5.5 hours, Poor - 2026-01-31 (Saturday): 5.8 hours, Poor - 2026-02-07 (Friday): 5.9 hours, Poor These are followed by compensatory long-sleep weekends (8.0-8.5 hours). This suggests end-of-week fatigue accumulation with weekend recovery. **Confidence: MEDIUM** -- Apple Watch sleep tracking is based on accelerometer and heart rate analysis. It captures time in bed and movement-based sleep stages but is less accurate than clinical polysomnography for quality assessment. Duration measurements are generally reliable. --- ## 2. Confidence Assessment Summary | Data Stream | Provenance | Samples/Day | Confidence | Basis | |-------------|-----------|-------------|------------|-------| | Resting Heart Rate | DeviceGenerated | 120-168 | **High** | Continuous passive monitoring, no user intervention needed | | Blood Pressure | DeviceGenerated | 1 | **Medium** | Validated device, but single daily reading; requires user action | | Activity (steps) | DeviceGenerated | Continuous | **High** | Passive accelerometer; no user action needed | | Activity (exercise min) | DeviceGenerated | Continuous | **High** | Auto-detected from HR + motion | | Sleep (duration) | DeviceGenerated | 1 | **Medium** | Wrist-based detection; less accurate than clinical measurement | | Sleep (quality) | DeviceGenerated | 1 | **Medium** | Algorithmically derived; quality labels are device-specific | | Supplements | SelfReported | N/A | **Low** | No adherence tracking; assumes patient takes as reported | --- ## 3. Cross-Stream Correlations ### Correlation 1: Poor Sleep and Elevated Heart Rate **Finding:** On the three worst sleep nights (5.5, 5.8, 5.9 hours), the following day's resting heart rate was elevated: | Poor Sleep Night | Hours | Next-Day Resting HR | 30-Day HR Average | |-----------------|-------|--------------------|--------------------| | 2026-01-24 | 5.5 | 62 bpm (2026-01-25) | 68.2 bpm | | 2026-01-31 | 5.8 | 69 bpm (2026-02-01) | 68.2 bpm | | 2026-02-07 | 5.9 | 68 bpm (2026-02-08) | 68.2 bpm | **Note:** The correlation is inconsistent. The 2026-01-25 reading is actually *lower* than average. The expected pattern (poor sleep leads to elevated HR) is not reliably demonstrated in this 30-day window. This may be due to confounding factors like weekend rest and reduced stress. **Confidence: LOW** -- Only 3 poor sleep events in the 30-day window is insufficient for statistical significance. The expected correlation is not consistently observed in this data. ### Correlation 2: Weekend Activity Drop and Blood Pressure **Finding:** Weekend days consistently show lower activity and slightly variable BP: | Day Type | Avg Steps | Avg Systolic BP | |----------|-----------|----------------| | Gym days (weekday) | ~9,800 | ~130 mmHg | | Non-gym weekdays | ~6,900 | ~130 mmHg | | Weekends | ~4,600 | ~129 mmHg | **Analysis:** Despite a 50% reduction in activity on weekends, blood pressure does not show a corresponding meaningful change. This suggests the BP is primarily pharmacologically controlled (Lisinopril) rather than activity-dependent in the short term. **Confidence: MEDIUM** -- Activity data is high-confidence, BP data is medium-confidence. The comparison is limited by having only 8 weekend days in the 30-day window. ### Correlation 3: Weekly Sleep-Activity Cycle **Finding:** A clear weekly cycle emerges when viewing sleep and activity together: ``` Mon-Wed: High activity (gym) -> Fair/Good sleep -> Moderate HR Thu-Fri: Declining activity -> Poor sleep -> Higher HR Sat-Sun: Low activity -> Long sleep -> Lower HR ``` This cycle is consistent across all 4 weeks in the data, suggesting an established lifestyle pattern rather than a random fluctuation. **Confidence: HIGH** -- Pattern repeats consistently across 4 weekly cycles with data from multiple independent streams. --- ## 4. Clinical Context Integration ### Hypertension Management Alex's home BP (mean 129/80 mmHg) on Lisinopril 20 mg indicates controlled but not optimized hypertension. The variability (systolic range 120-138) suggests room for improvement. No upward trend was detected, which is reassuring. The lack of correlation between activity and BP in this short window suggests the medication is the primary control factor. ### Diabetes and Activity Alex's exercise pattern (gym 3x/week, 20 min/day average) is below the ADA recommendation of 150 min/week of moderate activity. His 30-day total is approximately 603 exercise minutes, averaging ~140 min/week. Increasing weekend activity could help improve glycemic control (HbA1c currently 7.2%, target <7.0%). ### Medication Effects on Vitals - **Lisinopril**: Expected to lower BP and slightly lower HR. The observed resting HR of 68 bpm is consistent with mild bradycardic effect. - **Metformin**: No expected effect on vitals measured here. - **Atorvastatin**: No expected effect on vitals measured here. --- ## 5. Trend Observations Written to Pod ### Observation 1: Blood Pressure Trend ```turtle @prefix cascade: . @prefix health: . @prefix prov: . @prefix xsd: . a cascade:AIObservation ; cascade:observationType "WellnessTrendObservation" ; cascade:trendType "vitalSign" ; cascade:metric "bloodPressure" ; cascade:direction "stable" ; cascade:severity "informational" ; cascade:confidence "medium" ; cascade:dataProvenance cascade:AIGenerated ; cascade:schemaVersion "1.3" ; cascade:summary "30-day home blood pressure is stable (mean 129/80 mmHg, range 120-138/74-86). Controlled but consistently above optimal threshold of 120/80. No upward or downward trend detected. Pattern: higher readings follow low-activity or poor-sleep days." ; cascade:dataPoints 30 ; cascade:period "2026-01-20 to 2026-02-18" ; cascade:clinicalRelevance "Hypertension managed with Lisinopril 20 mg. Consider discussing optimization strategies at next visit." ; prov:wasGeneratedBy [ a prov:Activity ; prov:label "AI Wellness Trend Analysis" ; prov:startedAtTime "2026-02-20T00:00:00Z"^^xsd:dateTime ; prov:wasAssociatedWith [ a prov:SoftwareAgent ; prov:label "Cascade Trend Analysis Agent" ] ] . ``` ### Observation 2: Activity Pattern ```turtle a cascade:AIObservation ; cascade:observationType "WellnessTrendObservation" ; cascade:trendType "activity" ; cascade:metric "exerciseMinutes" ; cascade:direction "stable" ; cascade:severity "informational" ; cascade:confidence "high" ; cascade:dataProvenance cascade:AIGenerated ; cascade:schemaVersion "1.3" ; cascade:summary "30-day exercise averages ~140 min/week (target 150 min/week per ADA guidelines for diabetes management). Strong weekday/weekend cyclicality: gym sessions 3x/week produce 30-45 min exercise, but 6 of 30 days had zero exercise minutes. Weekend activity drops to 4,000-5,200 steps vs 8,000-12,000 on gym days." ; cascade:dataPoints 30 ; cascade:period "2026-01-20 to 2026-02-18" ; cascade:clinicalRelevance "Patient with Type 2 Diabetes (HbA1c 7.2%, target <7.0%). Increasing weekend activity and adding 1-2 additional exercise sessions per week could help reach the 150 min/week target and potentially improve glycemic control." ; prov:wasGeneratedBy [ a prov:Activity ; prov:label "AI Wellness Trend Analysis" ; prov:startedAtTime "2026-02-20T00:00:00Z"^^xsd:dateTime ; prov:wasAssociatedWith [ a prov:SoftwareAgent ; prov:label "Cascade Trend Analysis Agent" ] ] . ``` ### Observation 3: Sleep Pattern ```turtle a cascade:AIObservation ; cascade:observationType "WellnessTrendObservation" ; cascade:trendType "sleep" ; cascade:metric "sleepDuration" ; cascade:direction "stable" ; cascade:severity "informational" ; cascade:confidence "medium" ; cascade:dataProvenance cascade:AIGenerated ; cascade:schemaVersion "1.3" ; cascade:summary "30-day sleep averages 7.1 hours/night (adequate for age). However, 10% of nights (3/30) are classified as Poor quality with duration under 6 hours. Poor sleep nights cluster on Thursdays/Fridays, suggesting end-of-week fatigue accumulation. Compensatory long sleep occurs on weekends (8.0-8.5 hours)." ; cascade:dataPoints 30 ; cascade:period "2026-01-20 to 2026-02-18" ; cascade:clinicalRelevance "Sleep consistency may be more important than average duration. The weekly poor-sleep pattern could affect glucose regulation and blood pressure control. Consider sleep hygiene counseling for work-week consistency." ; prov:wasGeneratedBy [ a prov:Activity ; prov:label "AI Wellness Trend Analysis" ; prov:startedAtTime "2026-02-20T00:00:00Z"^^xsd:dateTime ; prov:wasAssociatedWith [ a prov:SoftwareAgent ; prov:label "Cascade Trend Analysis Agent" ] ] . ``` ### Observation 4: Weekly Lifestyle Cycle ```turtle a cascade:AIObservation ; cascade:observationType "WellnessTrendObservation" ; cascade:trendType "crossStream" ; cascade:metric "weeklyLifestyleCycle" ; cascade:direction "cyclical" ; cascade:severity "informational" ; cascade:confidence "high" ; cascade:dataProvenance cascade:AIGenerated ; cascade:schemaVersion "1.3" ; cascade:summary "A consistent weekly lifestyle cycle was detected across all 4 data streams over 4 weeks: Mon-Wed high activity and moderate sleep, Thu-Fri declining activity and poor sleep, Sat-Sun low activity and long recovery sleep. This cycle correlates with heart rate patterns (lower on weekends, higher midweek). The pattern is lifestyle-driven rather than indicating disease progression." ; cascade:dataPoints 120 ; cascade:period "2026-01-20 to 2026-02-18" ; cascade:clinicalRelevance "Established lifestyle pattern, not a disease indicator. However, the weekly stress-recovery cycle may contribute to suboptimal chronic disease management. More consistent daily routines could benefit both BP and glucose control." ; prov:wasGeneratedBy [ a prov:Activity ; prov:label "AI Wellness Trend Analysis" ; prov:startedAtTime "2026-02-20T00:00:00Z"^^xsd:dateTime ; prov:wasAssociatedWith [ a prov:SoftwareAgent ; prov:label "Cascade Trend Analysis Agent" ] ] . ``` --- ## Limitations - **30-day window**: Insufficient for detecting long-term trends (seasonal patterns, disease progression). Minimum 90 days recommended for reliable trend detection. - **Single BP reading/day**: Morning-only BP may not capture afternoon/evening hypertensive episodes. - **No continuous glucose monitor**: Activity and sleep trends cannot be directly correlated with glucose data. Only periodic HbA1c is available. - **Self-reported supplement adherence**: Confidence in supplement-related correlations is inherently limited. --- **Disclaimer:** This analysis was generated by an AI agent processing device-generated wellness data. Trends and observations are statistical in nature and do not constitute medical diagnoses. All findings should be reviewed with a licensed healthcare provider.