Nursing intensity trajectory patterns and clinical outcomes in intensive care units: a latent class analysis.
Distinct nursing intensity patterns in ICU patients correlate with mortality and length of stay, but further research is needed to apply these findings clinically.
Where it sits
this study against the rest of the lypressin corpusSummary and findings
The study analyzed nursing intensity trajectory patterns in 7,334 ICU patients over the first 7 days of stay. Four distinct patterns were identified, each associated with different mortality rates and ICU lengths of stay. Rapid Improvement class had the lowest mortality and shortest stay, while Late Escalation had the highest mortality and longest stay.
Abstract
<h4>Background</h4>Temporal patterns of nursing intensity during ICU stay may identify clinically meaningful patient subgroups, yet existing studies rely primarily on static measurements at single time points.<h4>Objectives</h4>To identify distinct nursing intensity trajectory patterns during the first 7 ICU days and examine their associations with hospital mortality and ICU length of stay, independent of baseline illness severity.<h4>Design</h4>Retrospective cohort study using latent class trajectory modeling. This study was not prospectively registered as it involved retrospective analysis of an existing database.<h4>Setting</h4>Medical and surgical intensive care units at Beth Israel Deaconess Medical Center (2008-2019).<h4>Participants</h4>7,334 adult ICU patients (≥18 years) with ICU length of stay ≥7 days.<h4>Methods</h4>Nursing intensity was measured daily using a composite score incorporating three dimensions: sedation management (RASS scores), monitoring frequency (nursing charting counts), and care complexity (organ support requirements). Latent class trajectory modeling identified distinct patterns over ICU Days 1-7. Multivariable logistic regression examined associations with hospital mortality, adjusting for age, sex, and SOFA score.<h4>Results</h4>Four distinct trajectory classes were identified (entropy = 0.948): Class 1 'Rapid Improvement' (n = 702, 9.6%) showed steeply declining NI from 56.2 to 29.8, with the lowest mortality (9.6%) and shortest ICU stay (median 8.7 days). Class 2 'Late Escalation' (n = 360, 4.9%) showed rising NI from 38.5 to 61.7, with the highest mortality (39.3%) and longest stay (median 16.6 days). Class 3 'Moderate Stable' (n = 1,798, 24.5%) and Class 4 'Persistent High' (n = 4,474, 61.0%) showed intermediate outcomes. After adjusting for age, sex, and SOFA, Rapid Improvement was associated with 74% lower mortality odds (OR = 0.26, 95% CI: 0.18-0.36, p < 0.001) and Late Escalation with 86% higher odds (OR = 1.86, 95% CI: 1.45-2.39, p < 0.001) compared to Persistent High. Sensitivity analysis excluding medical intervention variables confirmed trajectory robustness (Adjusted Rand Index = 0.565). Bootstrap validation (500 resamples) confirmed class stability.<h4>Conclusions</h4>Four distinct nursing intensity trajectory patterns were identified, each characterized by different clinical outcome profiles. Declining NI trajectories characterized patients with lower mortality and shorter ICU stays, while escalating trajectories were observed in patients with worse outcomes, independent of baseline illness severity. These observational findings are hypothesis-generating and require prospective validation before informing clinical practice.
Background
This study addresses the clinical question of how nursing intensity patterns during ICU stays correlate with patient outcomes. Prior research has focused on static measurements, which may not capture dynamic changes in patient care needs. Identifying trajectory patterns could help stratify patients by risk and tailor interventions accordingly.
Methods
A retrospective cohort study was conducted using data from 7,334 adult ICU patients at Beth Israel Deaconess Medical Center from 2008 to 2019. Nursing intensity was measured daily through a composite score of sedation management, monitoring frequency, and care complexity. Latent class trajectory modeling identified patterns over the first 7 ICU days. Associations with hospital mortality were analyzed using multivariable logistic regression, adjusting for age, sex, and SOFA score.
Results
Four distinct nursing intensity trajectory classes were identified, with Class 1 'Rapid Improvement' showing the lowest mortality (9.6%) and shortest ICU stay (median 8.7 days). Class 2 'Late Escalation' had the highest mortality (39.3%) and longest stay (median 16.6 days). Adjusted analyses showed Rapid Improvement was associated with significantly lower mortality odds (OR = 0.26, 95% CI: 0.18-0.36, p < 0.001), while Late Escalation was associated with higher odds (OR = 1.86, 95% CI: 1.45-2.39, p < 0.001).
Interpretation
The findings suggest that dynamic nursing intensity patterns are associated with significant differences in patient outcomes, independent of baseline illness severity. The effect sizes are statistically significant, but the observational nature of the study limits clinical applicability without further validation. The study adds to the literature by highlighting the potential of trajectory analysis in ICU settings, though prospective studies are needed to confirm these patterns.
Key findings
- Four trajectory classes identified (entropy = 0.948).
- Class 1 'Rapid Improvement' had 9.6% mortality and median ICU stay of 8.7 days.
- Class 2 'Late Escalation' had 39.3% mortality and median ICU stay of 16.6 days.
- Rapid Improvement associated with 74% lower mortality odds (OR = 0.26, 95% CI: 0.18-0.36, p < 0.001).
- Late Escalation associated with 86% higher mortality odds (OR = 1.86, 95% CI: 1.45-2.39, p < 0.001).
Limitations
- Retrospective cohort design
- Single-center study
- Observational, not causal
- Requires prospective validation
- Potential unmeasured confounders