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Background: As more reports emerge that many COVID-19 survivors suffer protracted and lingering symptoms, how to define and better characterize these patients with post-acute COVID-19 is a research challenge. To understand the overall symptom burden in patients with post-acute COVID-19, we explored whether identifiable symptom clusters exist in a cohort of patients with post-acute COVID-19 and then examined whether these clusters are associated with quality of life impairments. Methods: In a prospective observational study of COVID-19 patients at a Covid-19 Recovery (CORE) clinic between June and December 2020 (eligible patients had either a positive COVID-19 PCR or IgG antibody test), we administered a modified revised Edmonton Symptom Assessment survey which assessed whether patients had 13 symptoms over the week prior to presentation to the clinic on a scale of 0 (no symptoms) to 10 (most severe symptoms). We performed exploratory factor analysis to search for clustering of symptoms into factors and examined the relationship between these clusters and quality of life measures. Results: Across 127 adult patients treated at CORE (mean (standard deviation (SD) age 51.8 (14.0);73.2% were women. We found four symptom factors: emotional factor (including depression and anxiety), activity limiting factor (fatigue, sleepiness and shortness of breath), gastrointestinal symptom factor (nausea, appetite and taste changes) and pain factor (pain, neuropathy). The Cronbach's α for the individual factors ranged from 0.64-0.84. The emotional factor was associated with an increased odds of reporting worse emotional (Odds Ratio (95% Confidence Interval (95% CI) 1.9 (1.2-3.3) and worse cognitive health status (OR 4.9 (2.5-9.5);the activity limiting factor was associated with increase odds of worse physical health status (OR 4.5 (2.1-9.7);the gastrointestinal symptom factor was associated with increase odds of worse cognitive health status (OR 2.1 (1.1-4.2). Conclusions: We found four symptom factors in adult patients with post-acute COVID-19. There was strong internal correlation between the factors and the factors were associated with quality of life measures. Routine assessment of post-acute COVID-19 patient's emotional, gastrointestinal, pain and activity limiting symptoms is important as they may be associated with impaired health related quality of life.
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Rationale: Recent reports suggest that many patients diagnosed with COVID-19 will experience protracted symptoms. As part of a COVID-19 Recovery Engagement program, we aimed to 1) elucidate the type and trajectory of protracted symptoms after COVID-19 diagnosis and 2) compare symptom prevalence and severity at 1, 3 and 6 months after COVID-19 diagnosis. Methods: This is a prospective observational study of adults diagnosed with COVID-19 at Montefiore Medical Center from March 2020 to December 2020. We identified patients with a positive SARS-CoV-2 result who were recently treated in outpatient, Emergency Department, or hospital settings within the medical center. Patients were contacted for consent via telephone at 1, 3, and 6 months after diagnosis and asked to complete 1) a modified revised Edmonton Symptom Assessment (mrESAS), which assessed 13 symptoms on a scale of 0-10 and 2) three additional questions that asked patients to compare their physical, emotional and cognitive health status to their pre-COVID health state. We used chart review to gather additional data for each of the patients, including demographics, past medical history, and course of COVID-19 illness.Results: We enrolled 141 patients (mean (standard deviation (SD) age 49.5(16.9)], with 29 in the 1-month cohort, 22 in 3-month cohort, and 90 in 6-month cohort;46/141 (32.6%) were hospitalized. In patients in the 1-month cohort, there was a high (≥ 25% of patients) prevalence of 7/13 symptoms: pain (31%), fatigue (31%), sleepiness (30.3%), nausea (30.3%), change in taste (31%), breathlessness (27.6%) and anxiety (37.9%). In general, prevalence of symptoms was lower in patients at 3- month and 6-months after discharge. We found a higher prevalence of nausea and change of taste symptoms in the 1-month group compared with the 3- and 6-month group (10% at 1-month reported nausea vs 1.8% in 3- and 6-month cohorts, p= 0.026;31% at 1-month reported change in taste vs. 10.7 in the 3- and 6-month groups, p=0.006 for change of taste). Furthermore, in the 6-month cohort, 24.4%, 25.6% and 30% reported being worse than pre-COVID in their physical, emotional and cognitive health status, respectively. Conclusion: Patients at 1-month post-COVID experience more nausea and taste change than patients called at later time points after diagnosis. Even at 6 months after COVID diagnosis, over one-fourth of all patients still consider themselves to have worse health status than before their illness. COVID-19 survivors have a significant risk of residual symptoms for months after diagnosis.
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Rationale: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic led to elevated inhospital morbidity and mortality. We aim to understand the frequency, timing, and outcomes associated with organ failure as defined by Sequential Organ Failure Assessment (SOFA) score for adult inpatients before and during the SARS-CoV-2 pandemic. Methods: A retrospective cohort of 17,722 unique patients age ≥18 years and their 20,675 admissions to 3 hospitals within the Montefiore Health System from 1 February 2020 through 31 May 2020 was constructed from the electronic health record. The cohort was stratified into two groups based on admission date with the cutoff being on or after 17 March 2020, when the confirmed index case of SARS-CoV-2 was admitted. Sequential Organ Failure Assessment (SOFA) scores were computed every 2 hours for each patient starting at admission using an automated SOFA calculator to produce a SOFA score composed of cardiovascular, coagulation, liver, renal, and respiratory components. The neurologic component was not computed due to sparsity of Glasgow Coma Scale data captured electronically. Results: A total of 1,789,930 SOFA scores were computed for the 20,675 admissions. Testing for SARS-CoV-2 occurred more during the pandemic (87.6% vs. 1.7%), with 48.4% of pandemic admissions testing positive. There was a significant increase in ICU admissions, usage of invasive mechanical ventilation, ICU and hospital length of stay, and mortality during the pandemic as compared to before (Table 1). Renal failure was the most common organ failure on presentation for both periods, but the most common organ failure during hospitalization was respiratory, which increased 53% during the pandemic. The burden of organ failure was higher during the pandemic, with a significant increase in multiorgan failure as indicated by the number of patients with maximum SOFA scores ≥ 6 as compared to before the pandemic. Conclusions: Before and during the SARS-CoV-2 pandemic, respiratory and renal systems were the most common organ systems to fail. There was a marked increase in the burden of multiorgan failure during the pandemic leading to increased ICU admissions, invasive mechanical ventilation, hospital length of stay, and mortality.
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Introduction: Many COVID-19 survivors suffer protracted symptoms after COVID-19. This study aimed to describe and compare the symptom burden and clinical management in adult patients seen at a COVID-19 Recovery Engagement Clinic (CORE) between hospitalized and non-hospitalized COVID-19 patients. Methods: A prospective observational study of COVID-19 adult patients referred to the CORE clinic, from June-December, 2020 was performed. Eligible patients had either a positive COVID-19 PCR or IgG antibody test. All patients were administered a modified revised Edmonton Physical Symptom Assessment (mrESAS), where patients were asked to quantify their level of 13 symptoms over the week prior to presentation to the clinic using a numerical rating scale between 0 (none) and 10 (the highest level imaginable). The ten most common symptoms were then tallied to generate a total symptom score that could range from 0-100. All patient qualified their physical, emotional and cognitive function post-COVID (as the same, worse or better) compared to before acute COVID illness. Chart review was used to collect additional information on patient's history, demographics, and to summarize relevant clinical management. Results: Of the 127 adults who presented to CORE clinic (mean age 52, SD 14.0), 43 (34.4%) had been hospitalized for COVID-related acute illness. Adults who were hospitalized were older than those who were not hospitalized (mean age (standard deviation (SD) 58.6 (11.7) in hospitalized versus 48.9 (12.7) in non-hospitalized, p<0.001). Figure 1 summarizes the prevalence of symptoms on presentation to the clinic (median (IQR) time in days from PCR first positive 139.5 (124, 162)1). The four most common symptoms were: fatigue (n=110 (88.0%);anxiety (n=95 (76.0%);shortness of breath (n=96 (76.8%);pain (n=92 (73.6%). Of the cohort, 84.7%, 73.4%, and 59.7% reported being worse in their physical, emotional, and cognitive health respectively compared to before COVID-19 acute illness. There were few clinically or statistically significant differences in the prevalence or severity of symptoms by hospitalization status (median (interquartile range) of total symptom score 39 (28-56) in hospitalized versus 32 (20-47) in hospitalized patients, p-value=0.09. Conclusions: COVID-19 patients experience lingering symptoms for weeks after testing positive, most commonly being fatigue, anxiety, shortness of breath, and pain. We found no significant difference in symptom presentation between hospitalized and non-hospitalized patients. Further symptom assessment in post-acute care of COVID-19 patients is necessary, specifically with a larger sample size to compare hospitalization status.
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Rationale: COVID-19 hospitalizations continue to surge rapidly throughout the world. Given the high morbidity and mortality and prolonged duration of illness experienced by patients with respiratory failure due to COVID-19, shortages of ventilators are expected. In New York State, the Crisis Standards of Care guidelines were codified by the New York State Taskforce on Life and the Law in the 2015 Ventilator Triage Guidelines (NYS guidelines). These guidelines outline clinical criteria for triage, including exclusion criteria and stratification of patients using the Sequential Organ Failure Assessment (SOFA) score. We aimed to estimate the excess mortality that would be associated with implementation of triage processes using this protocol. Methods: We included all 5,028 patients who were admitted with COVID-19 in three acute care hospitals at a single academic medical center in the Bronx from March 1, 2020 to May 27, 2020 during the peak of the pandemic surge in New York City. Importance sampling was used to estimate the likelihood of patient trajectories under the NYS guidelines and estimate survival rates. Pessimistic and optimistic estimations were derived to account for potential unobserved confounders. Overall estimated survival was then calculated over a range of hypothetical ventilator shortages (e.g. if it has not been possible to acquire the additional ventilators that were procured in the Spring) from 85-100% availability of the total ventilator capacity of these facilities. Results: The average age of the sample was 64.2 (SD 16.2) and 47% were female. The observed survival rate was 74.16%. A total of 721 patients (14%) required mechanical ventilation during admission. If there has been a ventilator shortfall with ventilator capacity at 85% and the NYS guidelines were enacted in this setting, the estimated survival would be between 70.3% (pessimistic estimation) and 71.5% (optimistic estimation) (Figure 1). Conclusions: A shortfall of ventilators at 85% ventilator capacity requiring implementation of the NYS guidelines triage protocol would have resulted in 2.7-3.9% excess mortality in hospitalized patients with COVID-19 during the pandemic surge, or 134-194 additional deaths. This study is limited by the exclusion of COVID-19 negative patients, who would be in the triage pool in an actual triage situation. Future directions include using this data set to compare NYS guideline performance to other triage strategies including first-come first-served and random allocation to better understand the utility of SOFA score-based triage strategies.
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RATIONALE: Preliminary studies have shown varied outcomes when comparing Acute Respiratory Distress Syndrome (ARDS) caused by Coronavirus Disease 2019 (COVID-19) versus “Classic” ARDS. The aim of this study was to compare patient characteristics and outcome of ARDS before and during COVID-19 pandemic. METHODS: We conducted a single center retrospective cohort study at 3 hospitals sites of Montefiore Medical Center comparing a pre-COVID respiratory failure cohort from 2017 to 2018 and a COVID respiratory failure cohort from March 2020 to May 2020. ARDS was identified by having PaO2/FiO2 ratio <= 300 and independent x-ray review consistent of bilateral infiltrates according to 2012 Berlin definition. We used Mann-Whitney-U test for non-parametric comparison of continuous variables and chi-square test for categorical variables. P < 0.05 is considered statistically significant. RESULTS: We included 1328 ARDS pre-COVID patients from 2017-2018 and 536 COVID-19 patients. The age or race was not different between the 2 ARDS cohorts (Table 1). There were more males in the COVID-19 ARDS (56.2% pre-COVID vs 61.4% COVID-19;p = 0.039). The median PaO2/FiO2 ratio for pre-COVID ARDS was higher than COVID (184 (IQR 117, 242) vs 116 (IQR 80.3, 178), p < 0.0005) with less severe ARDS in pre-COVID (18.3% vs 38.2%;p < 0.0005). In-hospital mortality almost doubled in COVID-19 ARDS (68.8%) compare with pre-COVID ARDS (37.2%, p <0.0005). The hospital length of stay was significantly longer in pre-COVID ARDS;ICU length of stay and duration of mechanical ventilation did not differ between the two ARDS groups (Table 1). CONCLUSIONS: COVID-19 ARDS presented more severely than pre-COVID ARDS based on PaO2/FiO2 ratio. The increase in in-hospital mortality in COVID-19 ARDS is likely related to the severity of respiratory failure. We need to adjust for the confounders between ARDS types and patient outcomes.
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Introduction: Daily spontaneous awakening trials (SAT) have been associated with decreased ventilator and ICU days We evaluated the compliance with SATs in COVID positive patients using electronic health record data and whether increasing SAT performance was associated with mortality, length of stay (LOS) and ventilator-free-days (VFDs). Methods: We retrospectively analyzed mechanically ventilated (MV) COVID positive patients admitted to the ICU from March 10, 2020 to May 21, 2020. Using an EHR-based performance measure for SAT, we excluded patients whom daily SAT was contra-indicated by admission primary ICD-10 codes: status epilepticus, increased intra-cranial pressure, alcoholic withdrawal. Eligibility for SAT for each day on MV was defined as absence of acidosis with pH < 7.30, or receipt of neuromuscular blocking agents on that day. SAT was defined as done when the patient had documented RASS >=0 or had a time period in which no continuous sedating medication were administered. A performance measure for SAT was defined as the percentage of eligible MV days in which SAT was done. Multivariate linear regression was used, adjusting for age, gender, race, and APACHE score and transforming length of stay to satisfy normality assumption. Results: 626 COVID positive patients including 552 on MV were admitted to the ICU during the target time period. Of these, 487 (88%) had at least one ICU day where they met eligibility for SAT. The in-hospital mortality of this cohort was 60.4% (n= 294, Table 1). SAT was performed on 66.7% (IQR 42.9%,100%) of eligible MV days with 5.1% of patients having no SATs done and 34.3% of patients receiving SAT on all eligible days, meaning they reached 100% SAT performance. Multivariate analyses demonstrated that while 100% SAT performance was not significantly associated with mortality (OR 1.06 95% CI (0.71,1.62)), it was associated with shorter hospital LOS and ICU LOS (Hospital LOS coefficient-0.37, 95% CI (-0.51,-0.24) and ICU LOS coefficient-0.74, 95% CI (-0.87,-0.61)) and greater number of ventilator-free days (coefficient 5.36, 95% CI (2.01,8.71)). Conclusion: Improving compliance with SAT on intubated COVID patients may decrease ICU length of stay which has implications for post-COVID recovery as well as resource optimization. We were limited by incomplete documentation during overwhelming COVID surge and likely underpowered to detect significant associations for the primary outcome of in-hospital mortality.
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Rationale: Prone positioning is a well-established recruitment maneuver to improve oxygenation and decrease mortality in intubated patients with severe acute respiratory distress syndrome (ARDS). There is evolving literature in utilizing proning among non-intubated and hypoxemic patients with novel coronavirus 2019 (COVID-19). However, there is paucity of evidence proving a sustained improvement in patient-centered outcomes. We aimed to determine the association between prone positioning in non-intubated patients with COVID-19 and incidence of invasive mechanical ventilation (IMV) or in-hospital mortality. Methods: We conducted a nested matched case-control analysis of adult COVID-19 patients admitted to three hospital sites in Bronx, NY between March 1, 2020 and April 1, 2020. Patients with do-not-intubate orders were excluded. Cases were defined by IMV or in-hospital mortality. Each case was matched with two controls based on age, gender, admission date within two weeks, and hospital length of stay greater than index time of matched case via risk-set sampling. Index time was defined as time after hospital admission when the case was intubated or died, whichever came first. The presence of non-intubated proning was identified from provider documentation. Results: We included 600 patients, 41 (6.8%) underwent non-intubated proning. Cases had lower SpO2/FiO2 (S/F) ratios prior to IMV or in-hospital mortality compared to controls (case median, 97 [interquartile range, 90-290] versus control median, 404 [interquartile range, 296-452]). While most providers (58.5%) documented immediate improvement in oxygenation status after initiating non-intubated proning, there was no difference in worst S/F ratios before and after non-intubated proning in both case and control (case median S/F ratio difference, 3 [interquartile range,-3-8] versus control median S/F ratio difference, 0 [interquartile range,-3-50]). In the univariate analysis, patients who underwent non-intubated proning were 2.57 times more likely to require IMV or experience in-hospital mortality (hazard ratio, 2.57;95% confidence interval, 1.17-5.64;P =.02). Following adjustment for patient level differences, we found no association between non-intubated proning and IMV or inhospital mortality (adjusted hazard ratio, 0.92;95% confidence interval, 0.34-2.45;P =.86). Conclusions: Although many providers documented an immediate improvement in oxygenation after non-intubated proning, sustained improvement was not identified. Non-intubated proning did not reduce the need for IMV or in-hospital mortality after adjustment for severity of illness and oxygenation status. While non-intubated proning may temporarily improve hypoxemia, it may lead to harmful delays in intubation and respiratory complications. Physicians should rigorously monitor respiratory parameters when attempting non-intubated proning.
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Introduction: ARDS is often unrecognized. We aimed to developed and validate a deep learning algorithm using EHR structured data to identify patients at risk for ARDS or in-hospital mortality in pre-COVID and COVID-19 inpatient population. Method: The initial cohort consisted of adult ICU patients on mechanical ventilation (MV) from 2017 to 2018 at 3 hospitals at Montefiore Medical Center. Independently trained physician reviewed all chest x-rays in patients with PaO2/FiO2 ratio ≤ 300 to determine ARDS as per Berlin criteria. We used 66 discrete EHR variables to generate 135 features based on variable types. We longitudinally sampled hourly and missing data were forwardly imputed. We trained a preliminary Long Short-Term Memory network to determine the probability of ARDS or in-hospital mortality in the 2017-2018 cohort. Using active learning process, we applied this preliminary model to additional MV patients admitted between 2016-2017 and 2018-2019 to expand the sample size with additional ARDS and non-ARDS patients. The expanded pre-COVID cohort (2016-2019) was split into training and validation cohort (80 and 20%). A new and final LSTM model were trained on the pre-COVID training cohort. Validations were performed on the pre-COVID validation cohort and a population of mechanically ventilated and non-ventilated COVID-19 patients between March-April 2020. Result: The pre-COVID cohort included 3905 MV patients in the ICU from final 2016-2019. 1646 (42.4%) had ARDS and 1033 (26.5%) died during hospitalization. COVID-19 cohort included 5672 patients and 907 (16%) died. 803 (14.2%) were mechanically ventilated including 583 ARDS patients(10.3% of COVID cohort and 72.6% of MV COVID patients) and 418 (52.1%) who died (Table 1). The model ROC was 0.78 for pre-COVID validation cohort. At model cutoff 0.90, the sensitivity was 86% and specificity was 57% (Table 1) In the COVID-19 cohort, the ROC was 0.83 (sensitivity of 70% and specificity of 84%). On the COVID-19 +MV sub-cohort, the model ROC was 0.70 and accurately diagnosed 91.6% of ARDS or death. The model was able to identify ARDS or death close to the time of intubation and ARDS label time in both pre-COVID and COVID-19 cohort (Table 1). Conclusion: Our LSTM algorithm accurately and timely identified the probability ARDS or in-hospital in mechanically ventilated patients. When we applied the model to a larger cohort of hospitalized patients with COVID-19 which had a higher prevalence of ARDS, the sensitivity, and positive predictive value remains high but specificity is much lower among MV patients.
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RATIONALE: COVID-19 activity continues to cause a high disease burden, and hospitals are vulnerable to ventilator scarcity. Crisis standards of care aim to maximize lives saved and to minimize clinician distress from bedside rationing. 26 states have allocation guidelines. 15 use the Sequential Organ Failure Assessment (SOFA) score. SOFA predicts mortality in hospitalized patients and provides objective data to reduce the risk of introducing bias. We use data from the COVID-19 surge in New York City (NYC) to model performance of a protocol based on SOFA scores and NY State guidelines. Although these guidelines were not implemented, we estimate the hypothetical outcomes had they been required. METHODS: This is a chart review of a random sample (205) of all intubated patients (1002) in three NYC hospitals between 25 March 2020 and 29 April 2020. Patients with and without COVID-19 were included. SOFA scores were calculated upon intubation, 48-, and 120-hours post-intubation. We calculated mortality and proportion of patients categorized into four groups: blue (ventilator not offered or removed), red (highest priority), yellow (intermediate priority), and green (weaned or ventilation not indicated) at each interval. RESULTS: 65 (32%) patients survived to discharge (Figure). 117 patients (57%) were categorized blue at least once;28 (24%) of those ultimately survived hospitalization. Patients ever in blue category had higher mortality (76%) compared with those never categorized blue (58%;p<0.01). Of expired patients, 89 (63%) were ever categorized as blue. CONCLUSIONS: Since over half of all patients met exclusion criteria at one or more time points, clinical judgment may still be needed to decide which patients would be excluded first. This re-introduces bias and moral distress;issues effective triage protocols should address. More specific scoring systems, such as 4C mortality score, may improve performance. Alternative strategies including first-come, first-served, randomization, clinician judgement, and triage committees lack empirical data and have ethical shortcomings. Our findings differ from a recent retrospective cohort study, which found few patients outside of the pandemic met New York State guideline blue category criteria among more than 40,000 ICU admissions. Our sample more closely reflects the acuity of pandemic conditions when this allocation guideline would be activated. The data from this preliminary study suggest that the SOFA score offers limited utility in triage, raising the question of whether sufficient ethical justification exists to impose a life-ending decision on a subset of patients to offer potential benefit to a modest number of others.