Table 2.
Time-varying cox regression model results for clinical predictors of bipolar disorder conversion
| Variable | Baseline HR (1–2 years) | 95% CI | Time interaction HR | 95% CI | E-value (baseline) | P-value | |
|---|---|---|---|---|---|---|---|
| Time-invariant predictors | Age (per year) | 1.009 | (1.007–1.011) | — | — | 1.10 | <0.001 |
| Low income | 0.805 | (0.745–0.869) | — | — | 1.79 | <0.001 | |
| Foreign born | 1.049 | (0.905–1.217) | — | — | 1.28 | 0.524 | |
| Psychotic features | 3.183 | (2.929–3.458) | — | — | 5.82 | <0.001 | |
| Personality disorder | 1.206 | (1.118–1.301) | — | — | 1.70 | <0.001 | |
| Time-varying predictors | Somatic comorbidities | 1.259 | (1.082–1.464) | 0.990 | (0.923–1.062) | 1.83 | 0.003 |
| Substance use disorders | 0.947 | (0.796–1.127) | 1.180 | (1.077–1.294) | 1.30 | 0.539 | |
| Anxiety disorders | 0.407 | (0.344–0.481) | 1.306 | (1.196–1.427) | 4.35 | <0.001 | |
| Primary care visits | 0.985 | (0.983–0.988) | 1.008 | (1.007–1.008) | 1.14 | <0.001 | |
| Mental health visits | 1.013 | (1.009–1.018) | 1.002 | (1.000–1.004) | 1.13 | <0.001 | |
| MH hospitalizations | 1.141 | (1.118–1.165) | 0.937 | (0.924–0.950) | 1.54 | <0.001 | |
| Emergency visits | 1.004 | (0.995–1.014) | 1.000 | (0.995–1.005) | 1.07 | 0.376 |
Abbreviations: HR, hazard ratio; CI, confidence interval; MH, mental health.
Note: Baseline hazard ratios represent Period 1 (1–2 years). Time interaction indicates change in hazard ratio per subsequent period. Time periods: Period 1 (1–2 years), Period 2 (2–5 years), Period 3 (+5 years). Note: The ≥1 year follow-up inclusion criterion precludes events before year 1, and maximum follow-up of ~9 years (given the 2010–2019 study period) limits extended observations. E-values represent the minimum strength of association that an unmeasured confounder would need to have with both the predictor and outcome to fully explain away the observed effect. Variables used for stratification in the original Cox model (sex, urban residence, and suicide attempts) are not included in the time-varying model.