Six worked queries. Adapt and run.

-- Cohort: first MDD + paired PHQ-9
WITH mdd AS (
  SELECT person_id, MIN(condition_start_date) AS dx
  FROM omop.condition_occurrence
  WHERE condition_concept_id IN (4252191, 4262111) -- F32, F33
    AND person_age >= 18
  GROUP BY person_id
), phq AS (
  SELECT person_id, observation_date,
         CAST(value_as_string AS int) AS phq9
  FROM omop.observation
  WHERE observation_concept_id = 3022875  -- PHQ-9 total
), paired AS (
  SELECT m.person_id,
         AVG(CASE WHEN ABS(p.observation_date - m.dx) <= 30 THEN phq9 END) AS phq_0,
         AVG(CASE WHEN ABS(p.observation_date - (m.dx + 84)) <= 14 THEN phq9 END) AS phq_12
  FROM mdd m JOIN phq p USING (person_id)
  GROUP BY m.person_id
), nm AS (
  -- CH extension: 8-axis daily telemetry, baseline window
  SELECT person_id, AVG(score) AS nm_avg
  FROM ch.axis_daily a JOIN mdd m USING (person_id)
  WHERE axis = 'NM' AND date BETWEEN m.dx - 30 AND m.dx
  GROUP BY person_id
)
SELECT ch_bracket(nm_avg) AS nm_bracket,
       AVG(phq_0 - phq_12)        AS phq_drop,
       k_anon(person_id, 11)  AS n
FROM paired JOIN nm USING (person_id)
WHERE phq_0 IS NOT NULL AND phq_12 IS NOT NULL
GROUP BY nm_bracket;

WITH cohort AS (
  SELECT person_id, MIN(condition_start_date) AS dx
  FROM omop.condition_occurrence
  WHERE condition_concept_id = 201826 -- T2DM
    AND person_age >= 18
  GROUP BY person_id
), a1c AS (
  SELECT c.person_id,
    AVG(CASE WHEN measurement_date BETWEEN c.dx - 30 AND c.dx + 30
            THEN value_as_number END) AS a1c_0,
    AVG(CASE WHEN measurement_date BETWEEN c.dx + 150 AND c.dx + 210
            THEN value_as_number END) AS a1c_6
  FROM cohort c JOIN omop.measurement m USING (person_id)
  WHERE measurement_concept_id = 3004410 -- A1c
  GROUP BY c.person_id
), pv AS (
  SELECT person_id, AVG(score) AS pv_avg, COUNT(*) AS n_days
  FROM ch.axis_daily a JOIN cohort c USING (person_id)
  WHERE a.axis = 'PV'
    AND a.date BETWEEN c.dx AND c.dx + 180
  GROUP BY person_id
), bmi AS (
  SELECT person_id, AVG(value_as_number) AS bmi_0
  FROM omop.measurement m JOIN cohort c USING (person_id)
  WHERE measurement_concept_id = 3038553
    AND measurement_date BETWEEN c.dx - 90 AND c.dx
  GROUP BY person_id
)
SELECT quartile(pv_avg) AS pv_q,
       AVG(a1c_0 - a1c_6)         AS a1c_drop,
       AVG(bmi_0)                 AS mean_bmi,
       k_anon(person_id, 11)  AS n
FROM a1c JOIN pv USING (person_id) JOIN bmi USING (person_id)
WHERE a1c_0 IS NOT NULL AND a1c_6 IS NOT NULL AND n_days >= 30
GROUP BY pv_q;

library(tidyverse); library(survival); library(lubridate)

# Pull from enclave views (k≥20 enforced server-side)
exposure <- tbl(con, "epa_pm25_daily") %>%
  filter(pm25 >= 35) %>%
  collect()

person_zcta <- tbl(con, "ch.person_zcta3") %>% collect()

axis_er <- tbl(con, "ch.axis_daily") %>%
  filter(axis == "ER") %>%
  collect()

resp_visits <- tbl(con, "omop.condition_occurrence") %>%
  filter(condition_concept_id %in% c(4112352, 261061)) %>% # asthma exac, COPD exac
  collect()

# Lag-aligned event-study, 0..14 day window post-exposure
joined <- join_lagged(exposure, axis_er, resp_visits, lag = 0:14)
summarise_by_lag(joined, k = 20) %>% plot_event_study()

-- Construct survival object: response = ≥50% PHQ-9 drop
WITH rx AS (
  SELECT person_id, MIN(drug_exposure_start_date) AS rx_start
  FROM omop.drug_exposure d
  JOIN omop.concept_ancestor a ON d.drug_concept_id = a.descendant_concept_id
  WHERE a.ancestor_concept_id = 21601798  -- ATC N06AB
  GROUP BY person_id
), phq AS (...),
sc AS (
  SELECT person_id, AVG(score) AS sc_avg
  FROM ch.axis_daily a JOIN rx USING (person_id)
  WHERE axis = 'SC' AND date BETWEEN rx_start - 30 AND rx_start
  GROUP BY person_id
)
-- Survival analysis run in R via survival::coxph
SELECT person_id, t_to_response, response, ch_bracket(sc_avg) AS sc_bracket
FROM built_cohort;

-- Compute per-axis baseline + 6mo, output the lift envelope
WITH rx AS (
  SELECT person_id, MIN(drug_exposure_start_date) AS rx0
  FROM omop.drug_exposure d
  JOIN omop.concept_ancestor a ON d.drug_concept_id = a.descendant_concept_id
  WHERE a.ancestor_concept_id IN (42873638, 793143, 1551860) -- sema, tirz, lira
  GROUP BY person_id
), bands AS (
  SELECT r.person_id, a.axis,
         AVG(CASE WHEN a.date BETWEEN r.rx0 - 30 AND r.rx0 THEN a.score END) AS base,
         AVG(CASE WHEN a.date BETWEEN r.rx0 + 150 AND r.rx0 + 210 THEN a.score END) AS mo6
  FROM ch.axis_daily a JOIN rx r USING (person_id)
  GROUP BY r.person_id, a.axis
)
SELECT axis, AVG(mo6 - base) AS mean_lift,
       stddev(mo6 - base) AS sd_lift,
       k_anon(person_id, 11) AS n
FROM bands
WHERE base IS NOT NULL AND mo6 IS NOT NULL
GROUP BY axis
ORDER BY mean_lift DESC;

-- Network density: count of distinct supportive ties in baseline household + school graph
WITH ties AS (
  SELECT person_id,
         COUNT(DISTINCT alter_id) FILTER (WHERE tie_type IN ('household', 'school')
                                       AND support_score >= 3) AS support_n
  FROM ch.rs_graph_edge_baseline
  GROUP BY person_id
), response AS (
  SELECT person_id,
         (vanderbilt_0 - vanderbilt_8w) / vanderbilt_0::float AS rel_drop
  FROM built_cohort
)
SELECT ntile(3) OVER (ORDER BY support_n) AS rs_tier,
       AVG(rel_drop) AS mean_response,
       k_anon(person_id, 11) AS n
FROM ties JOIN response USING (person_id)
GROUP BY rs_tier;