Introduction

Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome.

Methods

Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality.

Results

We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters.

Conclusions

Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.

Care during mass casualty events (MCE) has improved during the last 15 years. Military and civilian collaboration has led to partnerships which augment the response to MCE. Much has been written about strategies to deliver care during an MCE, but there is little about how to transition back to normal operations after an event. A panel discussion entitled The Day(s) After: Lessons Learned from Trauma Team Management in the Aftermath of an Unexpected Mass Casualty Event at the 76th Annual American Association for the Surgery of Trauma meeting on September 13, 2017 brought together a cadre of military and civilian surgeons with experience in MCEs. The events described were the First Battle of Mogadishu (1993), the Second Battle of Fallujah (2004), the Bagram Detention Center Rocket Attack (2014), the Boston Marathon Bombing (2013), the Asiana Flight 214 Plane Crash (2013), the Baltimore Riots (2015), and the Orlando Pulse Night Club Shooting (2016). This article focuses on the lessons learned from military and civilian surgeons in the days after MCEs.

Background

The Mangled Extremity Severity Score (MESS) was developed 25 years ago in an attempt to use the extent of skeletal and soft tissue injury, limb ischemia, shock, and age to predict the need for amputation after extremity injury. Subsequently, there have been mixed reviews as to the use of this score. We hypothesized that the MESS, when applied to a data set collected prospectively in modern times, would not correlate with the need for amputation.

Methods

We applied the MESS to patient data collected in the American Association for the Surgery of Trauma PROspective Vascular Injury Treatment registry. This registry contains prospectively collected demographic, diagnostic, treatment, and outcome data.

Results

Between 2013 and 2015, 230 patients with lower extremity arterial injuries were entered into the PROspective Vascular Injury Treatment registry. Most were male with a mean age of 34 years (range, 4-92 years) and a blunt mechanism of injury at a rate of 47.4%. A MESS of 8 or greater was associated with a longer stay in the hospital (median, 22.5 (15, 29) vs 12 (6, 21); p = 0.006) and intensive care unit (median, 6 (2, 13) vs 3 (1, 6); p = 0.03). Of the patients' limbs, 81.3% were ultimately salvaged (median MESS, 4 (3, 5)), and 18.7% required primary or secondary amputation (median MESS, 6 (4, 8); p < 0.001). However, after controlling for confounding variables including mechanism of injury, degree of arterial injury, injury severity score, arterial location, and concomitant injuries, the MESS between salvaged and amputated limbs was no longer significantly different. Importantly, a MESS of 8 predicted in-hospital amputation in only 43.2% of patients.

Conclusion

Therapeutic advances in the treatment of vascular, orthopedic, neurologic, and soft tissue injuries have reduced the diagnostic accuracy of the MESS in predicting the need for amputation. There remains a significant need to examine additional predictors of amputation following severe extremity injury.

Level of evidence

Prospective, prognostic study, level III.

Background

The large-scale social distancing efforts to reduce SARS-CoV-2 transmission have dramatically changed human behaviors associated with traumatic injuries. Trauma centers have reported decreases in trauma volume, paralleled by changes in injury mechanisms. We aimed to quantify changes in trauma epidemiology at an urban Level I trauma center in a county that instituted one of the earliest shelter-in-place orders to inform trauma care during future pandemic responses.

Methods

A single-center interrupted time-series analysis was performed to identify associations of shelter-in-place with trauma volume, injury mechanisms, and patient demographics in San Francisco, California. To control for short-term trends in trauma epidemiology, weekly level data were analyzed 6 months before shelter-in-place. To control for long-term trends, monthly level data were analyzed 5 years before shelter-in-place.

Results

Trauma volume decreased by 50% in the week following shelter-in-place (p < 0.01), followed by a linear increase each successive week (p < 0.01). Despite this, trauma volume for each month (March-June 2020) remained lower compared with corresponding months for all previous 5 years (2015-2019). Pediatric trauma volume showed similar trends with initial decreases (p = 0.02) followed by steady increases (p = 0.05). Reductions in trauma volumes were due entirely to changes in nonviolent injury mechanisms, while violence-related injury mechanisms remained unchanged (p < 0.01).

Conclusion

Although the shelter-in-place order was associated with an overall decline in trauma volume, violence-related injuries persisted. Delineating and addressing underlying factors driving persistent violence-related injuries during shelter-in-place orders should be a focus of public health efforts in preparation for future pandemic responses.

Level of evidence

Epidemiological study, level III.

Background

Thrombosis and inflammation may contribute to morbidity and mortality among patients with coronavirus disease 2019 (Covid-19). We hypothesized that therapeutic-dose anticoagulation would improve outcomes in critically ill patients with Covid-19.

Methods

In an open-label, adaptive, multiplatform, randomized clinical trial, critically ill patients with severe Covid-19 were randomly assigned to a pragmatically defined regimen of either therapeutic-dose anticoagulation with heparin or pharmacologic thromboprophylaxis in accordance with local usual care. The primary outcome was organ support-free days, evaluated on an ordinal scale that combined in-hospital death (assigned a value of -1) and the number of days free of cardiovascular or respiratory organ support up to day 21 among patients who survived to hospital discharge.

Results

The trial was stopped when the prespecified criterion for futility was met for therapeutic-dose anticoagulation. Data on the primary outcome were available for 1098 patients (534 assigned to therapeutic-dose anticoagulation and 564 assigned to usual-care thromboprophylaxis). The median value for organ support-free days was 1 (interquartile range, -1 to 16) among the patients assigned to therapeutic-dose anticoagulation and was 4 (interquartile range, -1 to 16) among the patients assigned to usual-care thromboprophylaxis (adjusted proportional odds ratio, 0.83; 95% credible interval, 0.67 to 1.03; posterior probability of futility [defined as an odds ratio <1.2], 99.9%). The percentage of patients who survived to hospital discharge was similar in the two groups (62.7% and 64.5%, respectively; adjusted odds ratio, 0.84; 95% credible interval, 0.64 to 1.11). Major bleeding occurred in 3.8% of the patients assigned to therapeutic-dose anticoagulation and in 2.3% of those assigned to usual-care pharmacologic thromboprophylaxis.

Conclusions

In critically ill patients with Covid-19, an initial strategy of therapeutic-dose anticoagulation with heparin did not result in a greater probability of survival to hospital discharge or a greater number of days free of cardiovascular or respiratory organ support than did usual-care pharmacologic thromboprophylaxis. (REMAP-CAP, ACTIV-4a, and ATTACC ClinicalTrials.gov numbers, NCT02735707, NCT04505774, NCT04359277, and NCT04372589.).

Background

Thrombosis and inflammation may contribute to the risk of death and complications among patients with coronavirus disease 2019 (Covid-19). We hypothesized that therapeutic-dose anticoagulation may improve outcomes in noncritically ill patients who are hospitalized with Covid-19.

Methods

In this open-label, adaptive, multiplatform, controlled trial, we randomly assigned patients who were hospitalized with Covid-19 and who were not critically ill (which was defined as an absence of critical care-level organ support at enrollment) to receive pragmatically defined regimens of either therapeutic-dose anticoagulation with heparin or usual-care pharmacologic thromboprophylaxis. The primary outcome was organ support-free days, evaluated on an ordinal scale that combined in-hospital death (assigned a value of -1) and the number of days free of cardiovascular or respiratory organ support up to day 21 among patients who survived to hospital discharge. This outcome was evaluated with the use of a Bayesian statistical model for all patients and according to the baseline d-dimer level.

Results

The trial was stopped when prespecified criteria for the superiority of therapeutic-dose anticoagulation were met. Among 2219 patients in the final analysis, the probability that therapeutic-dose anticoagulation increased organ support-free days as compared with usual-care thromboprophylaxis was 98.6% (adjusted odds ratio, 1.27; 95% credible interval, 1.03 to 1.58). The adjusted absolute between-group difference in survival until hospital discharge without organ support favoring therapeutic-dose anticoagulation was 4.0 percentage points (95% credible interval, 0.5 to 7.2). The final probability of the superiority of therapeutic-dose anticoagulation over usual-care thromboprophylaxis was 97.3% in the high d-dimer cohort, 92.9% in the low d-dimer cohort, and 97.3% in the unknown d-dimer cohort. Major bleeding occurred in 1.9% of the patients receiving therapeutic-dose anticoagulation and in 0.9% of those receiving thromboprophylaxis.

Conclusions

In noncritically ill patients with Covid-19, an initial strategy of therapeutic-dose anticoagulation with heparin increased the probability of survival to hospital discharge with reduced use of cardiovascular or respiratory organ support as compared with usual-care thromboprophylaxis. (ATTACC, ACTIV-4a, and REMAP-CAP ClinicalTrials.gov numbers, NCT04372589, NCT04505774, NCT04359277, and NCT02735707.).