Rhabdomyolysis in Severe COVID-19: Male Sex, High Body Mass Index, and Prone Positioning Confer High Risk.

BACKGROUND: Bedside experience and studies of critically ill patients with coronavirus disease 2019 (COVID-19) indicate COVID-19 to be a devastating multisystem disease. We aim to describe the incidence, associated variables, and outcomes of rhabdomyolysis in critically ill COVID-19 patients. MATERIALS AND METHODS: Data for all critically ill adult patients (≥18 years old) admitted to the ICU at a large academic medical center with confirmed COVID-19 between March 13, 2020 and April 18, 2020 were prospectively collected. Patients with serum creatine kinase (CK) concentrations greater than 1000 U/L were diagnosed with rhabdomyolysis. Patients were further stratified as having moderate (serum CK concentration 1000-4999 U/L) or severe (serum CK concentration ≥5000 U/L) rhabdomyolysis. Univariate and multivariate analyses were performed to identify outcomes and variables associated with the development of rhabdomyolysis. RESULTS: Of 235 critically ill COVID-19 patients, 114 (48.5%) met diagnostic criteria for rhabdomyolysis. Patients with rhabdomyolysis more often required mechanical ventilation (P < 0.001), prone positioning (P < 0.001), pharmacological paralysis (P < 0.001), renal replacement therapy (P = 0.010), and extracorporeal membrane oxygenation (ECMO) (P = 0.025). They also had longer median ICU length of stay (LOS) (P < 0.001) and hospital LOS (P < 0.001). No difference in mortality was observed. Male sex, patients with morbid obesity, SOFA score, and prone positioning were independently associated with rhabdomyolysis. CONCLUSIONS: Nearly half of critically ill COVID-19 patients in our cohort met diagnostic criteria for rhabdomyolysis. Male sex, morbid obesity, SOFA score, and prone position were independently associated with rhabdomyolysis.

Adding to the story, did penetrating trauma really increase? changes in trauma patterns during the COVID-19 pandemic: A multi-institutional, multi-region investigation.

BACKGROUND: Results from single-region studies suggest that stay at home orders (SAHOs) had unforeseen consequences on the volume and patterns of traumatic injury during the initial months of the Coronavirus disease 2019 (COVID-19). The aim of this study was to describe, using a multi-regional approach, the effects of COVID-19 SAHOs on trauma volume and patterns of traumatic injury in the US. METHODS: A retrospective cohort study was performed at four verified Level I trauma centers spanning three geographical regions across the United States (US). The study period spanned from April 1, 2020 - July 31, 2020 including a month-matched 2019 cohort. Patients were categorized into pre-COVID-19 (PCOV19) and first COVID-19 surge (FCOV19S) cohorts. Patient demographic, injury, and outcome data were collected via Trauma Registry queries. Univariate and multivariate analyses were performed. RESULTS: A total 5,616 patients presented to participating study centers during the PCOV19 (2,916) and FCOV19S (2,700) study periods.  Blunt injury volume decreased (p = 0.006) due to a significant reduction in the number of motor vehicle collisions (MVCs) (p = 0.003). Penetrating trauma experienced a significant increase, 8% (246/2916) in 2019 to 11% (285/2,700) in 2020 (p = 0.007), which was associated with study site (p = 0.002), not SAHOs. Finally, study site was significantly associated with changes in nearly all injury mechanisms, whereas SAHOs accounted for observed decreases in calculated weekly averages of blunt injuries (p < 0.02) and MVCs (p = 0.003). CONCLUSION: Results of this study suggest that COVID-19 and initial SAHOs had variable consequences on patterns of traumatic injury, and that region-specific shifts in traumatic injury ensued during initial SAHOs. These results suggest that other factors, potentially socioeconomic or cultural, confound trauma volumes and types arising from SAHOs. Future analyses must consider how regional changes may be obscured with pooled cohorts, and focus on characterizing community-level changes to aid municipal preparation for future similar events.

The variation of opioid prescription after injury and its association with long-term chronic pain: A multicenter cohort study.

BACKGROUND: Opioid overprescription in trauma contributes to the opioid epidemic through diversion of unused pills. Through our study, we sought to do the following: (1) understand the variation in opioid prescription after injury and its relationship to patient and/or clinical variables, and (2) study the relationship between opioid prescribing and long-term pain and analgesic use. METHOD: Trauma patients with an injury severity score ≥9 admitted to 3 level 1 trauma centers were screened for chronic pain and analgesic use 6 to 12 months postinjury. First, multivariable linear regression models were constructed with "oral morphine equivalents" and "number of opioid pills prescribed" at discharge as dependent variables. The coefficients of determination were calculated to determine how much of the variation in opioid prescription was explained by patient and clinical variables. Second, a multivariable logistic regression analysis was created to study the association between opioid prescription at discharge and chronic pain/analgesic use at 6 to 12 months. Analyses were adjusted for patient demographics, socioeconomics, comorbidities, injury parameters, and hospital course. RESULTS: Of the 2,702 patients included (mean [standard deviation] age: 61.0 [21.5]; 55% males), 74% were prescribed opioids at discharge (mean number of pills [standard deviation]: 24.0 [26.5]; mean oral morphine equivalent [standard deviation]: 204.8 [348.1]). The adjusted coefficients of determination for oral morphine equivalents and number of pills was 0.12 and 0.21, respectively, suggesting that the measured patient and clinical factors explain <21% of the variation in opioid prescribing in trauma. Patients prescribed opioids were more likely to have chronic pain (odds ratio [95%] confidence interval: 1.34 [1.05-1.71]) and use analgesics daily (odds ratio [95%] confidence interval: 1.86 [1.25-2.77]) 6 to 12 months postinjury. CONCLUSION: The variation in opioid prescription after traumatic injury is more affected by system and provider level rather than clinical or patient-related factors, and opioid prescribing correlates independently with long-term chronic pain and continued analgesic use postinjury. Efforts to decrease opioid use should prioritize standardizing prescription practices after traumatic injury.

Multisystem outcomes and predictors of mortality in critically ill patients with COVID-19: Demographics and disease acuity matter more than comorbidities or treatment modalities.

BACKGROUND: We sought to describe characteristics, multisystem outcomes, and predictors of mortality of the critically ill COVID-19 patients in the largest hospital in Massachusetts. METHODS: This is a prospective cohort study. All patients admitted to the intensive care unit (ICU) with reverse-transcriptase-polymerase chain reaction-confirmed severe acute respiratory syndrome coronavirus 2 infection between March 14, 2020, and April 28, 2020, were included; hospital and multisystem outcomes were evaluated. Data were collected from electronic records. Acute respiratory distress syndrome (ARDS) was defined as PaO2/FiO2 ratio of ≤300 during admission and bilateral radiographic pulmonary opacities. Multivariable logistic regression analyses adjusting for available confounders were performed to identify predictors of mortality. RESULTS: A total of 235 patients were included. The median (interquartile range [IQR]) Sequential Organ Failure Assessment score was 5 (3-8), and the median (IQR) PaO2/FiO2 was 208 (146-300) with 86.4% of patients meeting criteria for ARDS. The median (IQR) follow-up was 92 (86-99) days, and the median ICU length of stay was 16 (8-25) days; 62.1% of patients were proned, 49.8% required neuromuscular blockade, and 3.4% required extracorporeal membrane oxygenation. The most common complications were shock (88.9%), acute kidney injury (AKI) (69.8%), secondary bacterial pneumonia (70.6%), and pressure ulcers (51.1%). As of July 8, 2020, 175 patients (74.5%) were discharged alive (61.7% to skilled nursing or rehabilitation facility), 58 (24.7%) died in the hospital, and only 2 patients were still hospitalized, but out of the ICU. Age (odds ratio [OR], 1.08; 95% confidence interval [CI], 1.04-1.12), higher median Sequential Organ Failure Assessment score at ICU admission (OR, 1.24; 95% CI, 1.06-1.43), elevated creatine kinase of ≥1,000 U/L at hospital admission (OR, 6.64; 95% CI, 1.51-29.17), and severe ARDS (OR, 5.24; 95% CI, 1.18-23.29) independently predicted hospital mortality.Comorbidities, steroids, and hydroxychloroquine treatment did not predict mortality. CONCLUSION: We present here the outcomes of critically ill patients with COVID-19. Age, acuity of disease, and severe ARDS predicted mortality rather than comorbidities. LEVEL OF EVIDENCE: Prognostic, level III.