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1.
BMC Anesthesiol ; 22(1): 10, 2022 01 04.
Article in English | MEDLINE | ID: covidwho-1607079

ABSTRACT

BACKGROUND: ICU operational conditions may contribute to cognitive overload and negatively impact on clinical decision making. We aimed to develop a quantitative model to investigate the association between the operational conditions and the quantity of medication orders as a measurable indicator of the multidisciplinary care team's cognitive capacity. METHODS: The temporal data of patients at one medical ICU (MICU) of Mayo Clinic in Rochester, MN between February 2016 to March 2018 was used. This dataset includes a total of 4822 unique patients admitted to the MICU and a total of 6240 MICU admissions. Guided by the Systems Engineering Initiative for Patient Safety model, quantifiable measures attainable from electronic medical records were identified and a conceptual framework of distributed cognition in ICU was developed. Univariate piecewise Poisson regression models were built to investigate the relationship between system-level workload indicators, including patient census and patient characteristics (severity of illness, new admission, and mortality risk) and the quantity of medication orders, as the output of the care team's decision making. RESULTS: Comparing the coefficients of different line segments obtained from the regression models using a generalized F-test, we identified that, when the ICU was more than 50% occupied (patient census > 18), the number of medication orders per patient per hour was significantly reduced (average = 0.74; standard deviation (SD) = 0.56 vs. average = 0.65; SD = 0.48; p < 0.001). The reduction was more pronounced (average = 0.81; SD = 0.59 vs. average = 0.63; SD = 0.47; p < 0.001), and the breakpoint shifted to a lower patient census (16 patients) when at a higher presence of severely-ill patients requiring invasive mechanical ventilation during their stay, which might be encountered in an ICU treating patients with COVID-19. CONCLUSIONS: Our model suggests that ICU operational factors, such as admission rates and patient severity of illness may impact the critical care team's cognitive function and result in changes in the production of medication orders. The results of this analysis heighten the importance of increasing situational awareness of the care team to detect and react to changing circumstances in the ICU that may contribute to cognitive overload.


Subject(s)
Cognition , Intensive Care Units , Patient Care Team , Aged , COVID-19/therapy , Decision Making, Organizational , Female , Humans , Male , Middle Aged , Patient Safety , SARS-CoV-2 , Workload
2.
Mayo Clin Proc ; 96(1): 183-202, 2021 01.
Article in English | MEDLINE | ID: covidwho-1065440

ABSTRACT

A growing number of studies on coronavirus disease 2019 (COVID-19) are becoming available, but a synthesis of available data focusing on the critically ill population has not been conducted. We performed a scoping review to synthesize clinical characteristics, treatment, and clinical outcomes among critically ill patients with COVID-19. Between January 1, 2020, and May 15, 2020, we identified high-quality clinical studies describing critically ill patients with a sample size of greater than 20 patients by performing daily searches of the World Health Organization and LitCovid databases on COVID-19. Two reviewers independently reviewed all abstracts (2785 unique articles), full text (218 articles), and abstracted data (92 studies). The 92 studies included 61 from Asia, 16 from Europe, 10 from North and South America, and 5 multinational studies. Notable similarities among critically ill populations across all regions included a higher proportion of older males infected and with severe illness, high frequency of comorbidities (hypertension, diabetes, and cardiovascular disease), abnormal chest imaging findings, and death secondary to respiratory failure. Differences in regions included newly identified complications (eg, pulmonary embolism) and epidemiological risk factors (eg, obesity), less chest computed tomography performed, and increased use of invasive mechanical ventilation (70% to 100% vs 15% to 47% of intensive care unit patients) in Europe and the United States compared with Asia. Future research directions should include proof-of-mechanism studies to better understand organ injuries and large-scale collaborative clinical studies to evaluate the efficacy and safety of antivirals, antibiotics, interleukin 6 receptor blockers, and interferon. The current established predictive models require further verification in other regions outside China.


Subject(s)
COVID-19/therapy , Critical Care/methods , Critical Illness/therapy , Humans , SARS-CoV-2
3.
Mayo Clin Proc ; 95(11): 2382-2394, 2020 11.
Article in English | MEDLINE | ID: covidwho-912419

ABSTRACT

OBJECTIVE: To assess the efficacy and safety of lenzilumab in patients with severe coronavirus disease 2019 (COVID-19) pneumonia. METHODS: Hospitalized patients with COVID-19 pneumonia and risk factors for poor outcomes were treated with lenzilumab 600 mg intravenously for three doses through an emergency single-use investigational new drug application. Patient characteristics, clinical and laboratory outcomes, and adverse events were recorded. We also identified a cohort of patients matched to the lenzilumab patients for age, sex, and disease severity. Study dates were March 13, 2020, to June 18, 2020. All patients were followed through hospital discharge or death. RESULTS: Twelve patients were treated with lenzilumab; 27 patients comprised the matched control cohort (untreated). Clinical improvement, defined as improvement of at least 2 points on the 8-point ordinal clinical endpoints scale, was observed in 11 of 12 (91.7%) patients treated with lenzilumab and 22 of 27 (81.5%) untreated patients. The time to clinical improvement was significantly shorter for the lenzilumab-treated group compared with the untreated cohort with a median of 5 days versus 11 days (P=.006). Similarly, the proportion of patients with acute respiratory distress syndrome (oxygen saturation/fraction of inspired oxygen<315 mm Hg) was significantly reduced over time when treated with lenzilumab compared with untreated (P<.001). Significant improvement in inflammatory markers (C-reactive protein and interleukin 6) and markers of disease severity (absolute lymphocyte count) were observed in patients who received lenzilumab, but not in untreated patients. Cytokine analysis showed a reduction in inflammatory myeloid cells 2 days after lenzilumab treatment. There were no treatment-emergent adverse events attributable to lenzilumab. CONCLUSION: In high-risk COVID-19 patients with severe pneumonia, granulocyte-macrophage colony-stimulating factor neutralization with lenzilumab was safe and associated with faster improvement in clinical outcomes, including oxygenation, and greater reductions in inflammatory markers compared with a matched control cohort of patients hospitalized with severe COVID-19 pneumonia. A randomized, placebo-controlled clinical trial to validate these findings is ongoing (NCT04351152).


Subject(s)
Antibodies, Monoclonal, Humanized/administration & dosage , COVID-19/drug therapy , Granulocyte-Macrophage Colony-Stimulating Factor/antagonists & inhibitors , SARS-CoV-2 , Aged , COVID-19/epidemiology , COVID-19/metabolism , Dose-Response Relationship, Drug , Female , Granulocyte-Macrophage Colony-Stimulating Factor/metabolism , Humans , Infusions, Intravenous , Male , Middle Aged , Pandemics , Treatment Outcome
4.
Elife ; 92020 07 07.
Article in English | MEDLINE | ID: covidwho-635065

ABSTRACT

Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVIDpos; n = 2,317) versus COVID-19-negative (COVIDneg; n = 74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVIDpos over COVIDneg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVIDpos patients during the week prior to PCR testing, in addition to anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.


Subject(s)
Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Adult , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Chills/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Coronavirus Infections/virology , Diarrhea/virology , Dysgeusia/virology , Female , Fever/virology , Humans , Male , Middle Aged , Myalgia/virology , Olfaction Disorders/virology , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Pneumonia, Viral/virology , Polymerase Chain Reaction , SARS-CoV-2
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