Objective
Coronavirus disease 2019 (COVID‐19) continues to spread, and younger patients are also being critically affected. This study analyzed obesity as an independent risk factor for mortality in ...hospitalized patients younger than 50.
Methods
This study retrospectively analyzed data of patients with COVID‐19 who were hospitalized to a large academic hospital system in New York City between March 1, 2020, and May 17, 2020. Data included demographics, comorbidities, BMI, and smoking status. Obesity groups included the following: BMI of 30 to < 40 kg/m2 and BMI ≥ 40 kg/m2. Multivariable logistic regression models identified variables independently associated with mortality in patients younger and older than 50.
Results
Overall, 3,406 patients were included; 572 (17.0%) patients were younger than 50. In the younger age group, 60 (10.5%) patients died. In the older age group, 1,076 (38.0%) patients died. For the younger population, BMI ≥ 40 was independently associated with mortality (adjusted odds ratio 5.1; 95% CI: 2.3‐11.1). For the older population, BMI ≥ 40 was also independently associated with mortality to a lesser extent (adjusted odds ratio 1.6; 95% CI: 1.2‐2.3).
Conclusions
This study demonstrates that hospitalized patients younger than 50 with severe obesity are more likely to die of COVID‐19. This is particularly relevant in the Western world, where obesity rates are high.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic with millions infected and more than 1 million fatalities. Questions regarding the robustness, functionality, ...and longevity of the antibody response to the virus remain unanswered. Here, on the basis of a dataset of 30,082 individuals screened at Mount Sinai Health System in New York City, we report that the vast majority of infected individuals with mild-to-moderate COVID-19 experience robust immunoglobulin G antibody responses against the viral spike protein. We also show that titers are relatively stable for at least a period of about 5 months and that anti-spike binding titers significantly correlate with neutralization of authentic SARS-CoV-2. Our data suggest that more than 90% of seroconverters make detectable neutralizing antibody responses. These titers remain relatively stable for several months after infection.
The study objective was to determine whether targeted therapy to optimize cerebral oxygenation is associated with improved neurocognitive and perioperative outcomes.
In a prospective trial, ...intraoperative cerebral oximetry monitoring using bilateral forehead probes was performed in cardiac surgical patients who were randomly assigned to an intervention group in which episodes of cerebral oxygen desaturation (<60% for >60 consecutive seconds at either probe) triggered an intervention protocol or a control group in which the cerebral oximetry data were hidden from the clinical team, and no intervention protocol was applied. Cognitive testing was performed preoperatively and at postoperative months 3 and 6; domains studied were response speed, processing speed, attention, and memory. Perioperative outcomes studied were death, hospital length of stay, intensive care unit length of stay, postoperative day of extubation, time on mechanical ventilation, intensive care unit delirium, Sequential Organ Failure Assessment on intensive care unit admission, and intensive care unit blood transfusion.
Group mean memory change scores were significantly better in the intervention group at 6 months (0.60 standard error, 0.30 vs −0.17 standard error, 0.33, adjusted P = .008). However, presence, duration, and severity of cerebral desaturation were not associated with cognitive change scores. Perioperative outcomes did not differ between the intervention and control groups.
Targeted therapy to optimize cerebral oxygenation was associated with better memory outcome in a group of cardiac surgical patients. Some aspects of the protocol other than desaturation duration and severity contributed to the observed neuroprotective effect.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Cancer immunotherapy based on genetically redirecting T cells has been used successfully to treat B cell malignancies
. In this strategy, the T cell genome is modified by integration of viral vectors ...or transposons encoding chimaeric antigen receptors (CARs) that direct tumour cell killing. However, this approach is often limited by the extent of expansion and persistence of CAR T cells
. Here we report mechanistic insights from studies of a patient with chronic lymphocytic leukaemia treated with CAR T cells targeting the CD19 protein. Following infusion of CAR T cells, anti-tumour activity was evident in the peripheral blood, lymph nodes and bone marrow; this activity was accompanied by complete remission. Unexpectedly, at the peak of the response, 94% of CAR T cells originated from a single clone in which lentiviral vector-mediated insertion of the CAR transgene disrupted the methylcytosine dioxygenase TET2 gene. Further analysis revealed a hypomorphic mutation in this patient's second TET2 allele. TET2-disrupted CAR T cells exhibited an epigenetic profile consistent with altered T cell differentiation and, at the peak of expansion, displayed a central memory phenotype. Experimental knockdown of TET2 recapitulated the potency-enhancing effect of TET2 dysfunction in this patient's CAR T cells. These findings suggest that the progeny of a single CAR T cell induced leukaemia remission and that TET2 modification may be useful for improving immunotherapies.
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KISLJ, NUK, SBMB, UL, UM, UPUK
Background A single subanesthetic (intravenous) IV dose of ketamine might have rapid but transient antidepressant effects in patients with treatment-resistant depression (TRD). Here we tested the ...tolerability, safety, and efficacy of repeated-dose open-label IV ketamine (six infusions over 12 days) in 10 medication-free symptomatic patients with TRD who had previously shown a meaningful antidepressant response to a single dose. Methods On day 1, patients received a 40-min IV infusion of ketamine (.5 mg/kg) in an inpatient setting with continuous vital-sign monitoring. Psychotomimetic effects and adverse events were recorded repeatedly. The primary efficacy measure was change from baseline in the Montgomery-Åsberg Depression Rating Scale (MADRS) score. If patients showed a ≥50% reduction in MADRS scores on day 2, they received five additional infusions on an outpatient basis (days 3, 5, 8, 10, and 12). Follow-up visits were conducted twice-weekly for ≥4 weeks or until relapse. Results Ketamine elicited minimal positive psychotic symptoms. Three patients experienced significant but transient dissociative symptoms. Side effects during and after each ketamine infusion were generally mild. The response criterion was met by nine patients after the first infusion as well as after the sixth infusion. The mean (SD) reduction in MADRS scores after the sixth infusion was 85% (12%). Postketamine, eight of nine patients relapsed, on average, 19 days after the sixth infusion (range 6 days–45 days). One patient remained antidepressant-free with minimal depressive symptoms for >3 months. Conclusions These pilot findings suggest feasibility of repeated-dose IV ketamine for the acute treatment of TRD.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
6.
AKI in Hospitalized Patients with COVID-19 Chan, Lili; Chaudhary, Kumardeep; Saha, Aparna ...
Journal of the American Society of Nephrology,
01/2021, Volume:
32, Issue:
1
Journal Article
Peer reviewed
Open access
Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associated with worse outcomes. However, AKI among hospitalized patients with COVID-19 in the ...United States is not well described.
This retrospective, observational study involved a review of data from electronic health records of patients aged ≥18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality.
Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patients with AKI required dialysis. The proportions with stages 1, 2, or 3 AKI were 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up.
AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.
Elephantids are the world’s most iconic megafaunal family, yet there is no comprehensive genomic assessment of their relationships. We report a total of 14 genomes, including 2 from the American ...mastodon, which is an extinct elephantid relative, and 12 spanning all three extant and three extinct elephantid species including an ∼120,000-y-old straight-tusked elephant, a Columbian mammoth, and woolly mammoths. Earlier genetic studies modeled elephantid evolution via simple bifurcating trees, but here we show that interspecies hybridization has been a recurrent feature of elephantid evolution. We found that the genetic makeup of the straight-tusked elephant, previously placed as a sister group to African forest elephants based on lower coverage data, in fact comprises three major components. Most of the straight-tusked elephant’s ancestry derives from a lineage related to the ancestor of African elephants while its remaining ancestry consists of a large contribution from a lineage related to forest elephants and another related to mammoths. Columbian and woolly mammoths also showed evidence of interbreeding, likely following a latitudinal cline across North America. While hybridization events have shaped elephantid history in profound ways, isolation also appears to have played an important role. Our data reveal nearly complete isolation between the ancestors of the African forest and savanna elephants for ∼500,000 y, providing compelling justification for the conservation of forest and savanna elephants as separate species.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia remains a significant challenge for ...improving the outcomes and decreasing the cost of healthcare delivery in the United States. Patient readmission rates are relatively high for conditions like heart failure (HF) despite the implementation of high-quality healthcare delivery operation guidelines created by regulatory authorities. Multiple predictive models are currently available to evaluate potential 30-day readmission rates of patients. Most of these models are hypothesis driven and repetitively assess the predictive abilities of the same set of biomarkers as predictive features. In this manuscript, we discuss our attempt to develop a data-driven, electronic-medical record-wide (EMR-wide) feature selection approach and subsequent machine learning to predict readmission probabilities. We have assessed a large repertoire of variables from electronic medical records of heart failure patients in a single center. The cohort included 1,068 patients with 178 patients were readmitted within a 30-day interval (16.66% readmission rate). A total of 4,205 variables were extracted from EMR including diagnosis codes (n=1,763), medications (n=1,028), laboratory measurements (n=846), surgical procedures (n=564) and vital signs (n=4). We designed a multistep modeling strategy using the Naïve Bayes algorithm. In the first step, we created individual models to classify the cases (readmitted) and controls (non-readmitted). In the second step, features contributing to predictive risk from independent models were combined into a composite model using a correlation-based feature selection (CFS) method. All models were trained and tested using a 5-fold cross-validation method, with 70% of the cohort used for training and the remaining 30% for testing. Compared to existing predictive models for HF readmission rates (AUCs in the range of 0.6-0.7), results from our EMR-wide predictive model (AUC=0.78; Accuracy=83.19%) and phenome-wide feature selection strategies are encouraging and reveal the utility of such datadriven machine learning. Fine tuning of the model, replication using multi-center cohorts and prospective clinical trial to evaluate the clinical utility would help the adoption of the model as a clinical decision system for evaluating readmission status.
Objectives: Approximately 20–30% of patients with COVID-19 require hospitalization, and 5–12% may require critical care in an intensive care unit (ICU). A rapid surge in cases of severe COVID-19 will ...lead to a corresponding surge in demand for ICU care. Because of constraints on resources, frontline healthcare workers may be unable to provide the frequent monitoring and assessment required for all patients at high risk of clinical deterioration. We developed a machine learning-based risk prioritization tool that predicts ICU transfer within 24 h, seeking to facilitate efficient use of care providers’ efforts and help hospitals plan their flow of operations. Methods: A retrospective cohort was comprised of non-ICU COVID-19 admissions at a large acute care health system between 26 February and 18 April 2020. Time series data, including vital signs, nursing assessments, laboratory data, and electrocardiograms, were used as input variables for training a random forest (RF) model. The cohort was randomly split (70:30) into training and test sets. The RF model was trained using 10-fold cross-validation on the training set, and its predictive performance on the test set was then evaluated. Results: The cohort consisted of 1987 unique patients diagnosed with COVID-19 and admitted to non-ICU units of the hospital. The median time to ICU transfer was 2.45 days from the time of admission. Compared to actual admissions, the tool had 72.8% (95% CI: 63.2–81.1%) sensitivity, 76.3% (95% CI: 74.7–77.9%) specificity, 76.2% (95% CI: 74.6–77.7%) accuracy, and 79.9% (95% CI: 75.2–84.6%) area under the receiver operating characteristics curve. Conclusions: A ML-based prediction model can be used as a screening tool to identify patients at risk of imminent ICU transfer within 24 h. This tool could improve the management of hospital resources and patient-throughput planning, thus delivering more effective care to patients hospitalized with COVID-19.
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a new human disease with few effective treatments
. Convalescent plasma, donated by ...persons who have recovered from COVID-19, is the acellular component of blood that contains antibodies, including those that specifically recognize SARS-CoV-2. These antibodies, when transfused into patients infected with SARS-CoV-2, are thought to exert an antiviral effect, suppressing virus replication before patients have mounted their own humoral immune responses
. Virus-specific antibodies from recovered persons are often the first available therapy for an emerging infectious disease, a stopgap treatment while new antivirals and vaccines are being developed
. This retrospective, propensity score-matched case-control study assessed the effectiveness of convalescent plasma therapy in 39 patients with severe or life-threatening COVID-19 at The Mount Sinai Hospital in New York City. Oxygen requirements on day 14 after transfusion worsened in 17.9% of plasma recipients versus 28.2% of propensity score-matched controls who were hospitalized with COVID-19 (adjusted odds ratio (OR), 0.86; 95% confidence interval (CI), 0.75-0.98; chi-square test P value = 0.025). Survival also improved in plasma recipients (adjusted hazard ratio (HR), 0.34; 95% CI, 0.13-0.89; chi-square test P = 0.027). Convalescent plasma is potentially effective against COVID-19, but adequately powered, randomized controlled trials are needed.
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FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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