ABSTRACT
Objectives: Clinical productivity is an important operational and educational metric for emergency medicine (EM) residents. It is unclear whether working consecutive days and circadian disruption impact resident productivity. The objective of this study was to determine whether there is a correlation between consecutive shifts and productivity. Methods: This was a single-site retrospective observational study using data from academic year 2021-2022 (July 1, 2021-June 23, 2022). Productivity was defined as primary resident encounters with patients per hour (PPH). Postgraduate year (PGY)-1 and PGY-2 productivity data and schedules were abstracted from the electronic medical record and scheduling software. Descriptive statistics, including arithmetic mean, standard deviation, and confidence interval (CI), were determined for each shift number and stratified by PGY level. Subgroup analysis of night shifts was performed. Analysis of variance and linear regression analysis were performed. Results: A total of 2950 shifts were identified, including 1328 PGY-1 shifts and 1622 PGY-2 shifts, which involved a total of 32,379 patient encounters. PGY-1 residents saw a mean of 0.88-0.96 PPH on sequential shifts 1-7, respectively (y-intercept 0.923, slope 0.001, 95% CI -0.008 to 0.009, p = 0.86). PGY-2 residents saw a mean of 1.61-1.75 PPH on Shifts 1-7, respectively (y-intercept 1.628, slope 0.004, 95% CI -0.007 to 0.015, p = 0.50). A subgroup analysis of 598 overnight shifts (11 p.m.-7 a.m.) was performed, in which residents saw a mean of 1.29-1.56 PPH on Sequential Shifts 1-7 (y-intercept 1.286, slope 0.011, 95% CI -0.011 to 0.033, p = 0.34). Conclusions: EM resident productivity remained relatively constant across consecutive shifts, including night shifts. These findings may have educational and operational implications. Further research is required to understand patient- and provider-oriented consequences of consecutive shift scheduling.
ABSTRACT
Sepsis is a heterogeneous syndrome and phenotypes have been proposed using clinical data. Less is known about the contribution of protein biomarkers to clinical sepsis phenotypes and their importance for treatment effects in randomized trials of resuscitation. The objective is to use both clinical and biomarker data in the Protocol-Based Care for Early Septic Shock (ProCESS) randomized trial to determine sepsis phenotypes and to test for heterogeneity of treatment effect by phenotype comparing usual care to protocolized early, goal-directed therapy(EGDT). In this secondary analysis of a subset of patients with biomarker sampling in the ProCESS trial (n = 543), we identified sepsis phenotypes prior to randomization using latent class analysis of 20 clinical and biomarker variables. Logistic regression was used to test for interaction between phenotype and treatment arm for 60-day inpatient mortality. Among 543 patients with severe sepsis or septic shock in the ProCESS trial, a 2-class model best fit the data (p = 0.01). Phenotype 1 (n = 66, 12%) had increased IL-6, ICAM, and total bilirubin and decreased platelets compared to phenotype 2 (n = 477, 88%, p < 0.01 for all). Phenotype 1 had greater 60-day inpatient mortality compared to Phenotype 2 (41% vs 16%; p < 0.01). Treatment with EGDT was associated with worse 60-day inpatient mortality compared to usual care (58% vs. 23%) in Phenotype 1 only (p-value for interaction = 0.05). The 60-day inpatient mortality was similar comparing EGDT to usual care in Phenotype 2 (16% vs. 17%). We identified 2 sepsis phenotypes using latent class analysis of clinical and protein biomarker data at randomization in the ProCESS trial. Phenotype 1 had increased inflammation, organ dysfunction and worse clinical outcomes compared to phenotype 2. Response to EGDT versus usual care differed by phenotype.
Subject(s)
Sepsis , Shock, Septic , Humans , Biomarkers , Clinical Protocols , Phenotype , Sepsis/diagnosis , Sepsis/therapy , Shock, Septic/diagnosis , Shock, Septic/therapyABSTRACT
BACKGROUND: This is a post hoc analysis of combined cohorts from two previous Phase II clinical trials to assess the effect of thiamine administration on kidney protection and mortality in patients with septic shock. METHODS: Patient-level data from the Thiamine in Septic Shock Trial (NCT01070810) and the Thiamine for Renal Protection in Septic Shock Trial (NCT03550794) were combined in this analysis. The primary outcome for the current study was survival without the receipt of renal replacement therapy (RRT). Analyses were performed on the overall cohort and the thiamine-deficient cohort (thiamine < 8 nmol/L). RESULTS: Totally, 158 patients were included. Overall, thiamine administration was associated with higher odds of being alive and RRT-free (adjusted odds ratio [aOR]: 2.05 [95% confidence interval (CI) 1.08-3.90]) and not needing RRT (aOR: 2.59 [95% CI 1.01-6.62]). In the thiamine-deficient group, thiamine administration was associated with higher odds of being alive and RRT-free (aOR: 8.17 [95% CI 1.79-37.22]) and surviving to hospital discharge (aOR: 6.84 [95% CI 1.54-30.36]). There was a significant effect modification by baseline thiamine deficiency for alive and RRT-free (interaction, p = 0.016) and surviving to hospital discharge (p = 0.019). CONCLUSION: In the combined analysis of two previous randomized trials, thiamine administration was associated with higher odds of being alive and RRT-free at hospital discharge in patients with septic shock. This signal was stronger in patients with thiamine deficiency.