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Please summerize the given abstract to a title | instruction | 0 | 77,419 | 13 | 231,847 |
Ferritin and Hemoglobin as Predictors of Fatal Outcome in COVID-19: Two Sides of the Same Coin. | output | 1 | 77,419 | 13 | 231,848 |
INTRODUCTION Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have multisystemic involvement with hyperinflammation being a cardinal feature and deranged iron metabolism having a possible role. In this premise, we studied the prognostic value of two markers of iron metabolism ferritin and hemoglobin. METHODOLOGY A retrospective-cohort study was carried out in a tertiary hospital in northern India involving 210 hospitalized COVID-19 patients aged 15-and above. Analysis was done for clinical profile, comorbidities and basic laboratory indices including ferritin-hemoglobin ratio (FHR) with primary end-point being in-hospital all-cause mortality. RESULTS Median serum ferritin levels (640.00ng/mL vs 220.00ng/mL) were significantly higher among non-survivors as against survivors while median hemoglobin levels were significantly lower (12.12g/dL vs 13.73g/dL). Serum ferritin levels >400ng/mL (Sn 80%, Sp 70%) predicted mortality with high sensitivity and specificity. Notably, serum ferritin levels >400ng/mL (HR 11.075 [1.481-82.801]) and anemia, defined as a hemoglobin of <12g/dL for females and < 13g/dL for males and were significantly associated with the risk of mortality in a univariable Cox-proportional hazards regression. The median FHR was significantly higher among non-survivors compared to survivors (56.98 vs 17.17). FHR>31 (Sn 85% Sp 71.6%) was highly sensitive and specific for predicting mortality. The multivariable analysis indicated that FHR >31 remained an independent risk factor for mortality (HR 12.293 [3.147-48.028]). CONCLUSION Ferritin-hemoglobin ratio (FHR), which encompasses into a single index, the effects of both elevated levels of ferritin and the severity of anemia, seems to perform particularly well as a prognostic marker and emerged as an independent risk factor for mortality in COVID-19 patients. Hyperferritinemia and anemia, both, are inexorably interlinked in addition to having a role, directly or indirectly in the disease pathophysiology. Ferritin and hemoglobin, hence should be seen as two sides of the same coin rather than as two discrete entities. | input | 2 | 77,419 | 13 | 231,849 |
Please summerize the given abstract to a title | instruction | 0 | 77,421 | 13 | 231,853 |
Better outcome with D-dimer guided anticoagulant in hospitalised patients with moderate and severe COVID-19 illness | output | 1 | 77,421 | 13 | 231,854 |
Background: Venous thromboembolism (VTE) prophylaxis is recommended for all hospitalized COVID-19 patients in the absence of contraindications. Although D-dimer is a recognized biomarker for disease severity, there are insufficient data to recommend using this parameter to guide therapeutic decisions. Purpose: The aim of the study is to investigate whether D-dimer guided anticoagulant therapy (ACT) is associated with a better evolution in moderate and severe COVID 19 illness. Methods: We retrospectively analysed 120 consecutive patients (71 men, mean age 62.8±14 years old), hospitalised for moderate or severe COVID-19 illness. All patients were clinically examined, thoracic CT was performed, hematologic parameters were measured. Presence of VTE in patients with risk factors was excluded with doppler imaging and/or contrast thoracic CT. Patients with D-dimer ≤0.5 mg/L received prophylactic ACT (enoxaparin 40 mg daily), patients with D-dimer between 0.5 mg/L and 1 mg/L received 40 mg bid and those with D dimer ≥1mg/L were treated with full dose ACT (enoxaparin 1mg/kg bid). During hospitalization D-dimer was measured and the ACT was adapted accordingly. In all patients COVID-19 disease was managed according to current guidelines. After discharge patients were followed up 30±7 days. Prophylactic ACT was continued in patients with high thrombotic risk. Results: 76 patients (63.3%) had moderate, and 44 patients (36.6%) had severe disease. Comorbidities were present in 71.5% patients (61.5% with cardiovascular disease, 16.6% with diabetes mellitus, 16.6% with obesity, 6.6% with renal failure, 4.1% with neoplastic disease). Average D-dimer was 1.3±0.8 mg/L. D-dimer elevation>0.5 mg/L was seen in 79 patients (65.8%). D-dimer was higher in patients with severe vs moderate illness 1.5±0.9 mg/L vs 1.01±0.9 mg/l (p<0.05) and in patients with comorbidities vs patients with no comorbidities (1.2±0.8 mg/L vs 0.7±0.6 mg/L, p<0.05). During hospitalization and subsequent follow up no VTE was recorded. 10 patients (0.83%) initially on prophylactic doses were switched to full dose ACT. Haemorrhagic complications were recorded in 5 patients (4.1%) and were minor. 4 patients (3.3%) with moderate illness at admission and comorbidities, were transferred to intensive care unit (ICU) and subsequently died (two patients with severe respiratory failure, one patient with respiratory failure and myocarditis and one patient with coma after resuscitated cardiac arrest). 116 patients (96.7%) were discharged after a median hospitalization of 12±3 days and there were no complications recorded during the short term follow up. Conclusions: D-dimer guided therapy is associated with a lower incidence of TVP complications and mortality in moderate and severe hospitalized patients (0% vs 10% and 3.3% vs 20.3% respectively in literature data base) with nonsignificant haemorrhagic complications. This small observational study needs to be validated by further research. | input | 2 | 77,421 | 13 | 231,855 |
Please summerize the given abstract to a title | instruction | 0 | 77,492 | 13 | 232,066 |
Smoking and comorbidities are associated with COVID-19 severity and mortality in 565 patients treated in Turkey: a retrospective observational study | output | 1 | 77,492 | 13 | 232,067 |
OBJECTIVE: We aimed to explore the prevalence of smoking rates and comorbidities and evaluate the relationship between them and disease severity and mortality in inpatients with COVID-19. METHODS: COVID-19 patients were divided into the following groups: clinic group, intensive care unit (ICU) group, survivors, and non-survivors. Non-COVID-19 patients were included as a control group. The groups were compared. RESULTS: There was no difference between patients with and without COVID-19 in terms of smoking, asthma, diabetes, dementia, coronary artery disease (CAD), hypertension, chronic renal failure and arrhythmia (p>0.05). Older age (Odds ratio (OR), 1.061; 95% confidence interval (CI): 1.041-1.082; p< 0.0001), chronic obstructive pulmonary disease (COPD) (OR, 2.775; 95% CI: 1.128-6.829; p=0.026) and CAD (OR, 2.696; 95% CI: 1.216-5.974; p=0.015) were significantly associated with ICU admission. Current smoking (OR, 5.101; 95% CI: 2.382-10.927; p<0.0001) and former smoking (OR, 3.789; 95% CI: 1.845-7.780; p<0.0001) were risk factors for ICU admission. Older age (OR; 1.082; 95% CI: 1.056-1.109; p<0.0001), COPD (OR, 3.213; 95% CI: 1.224-8.431; p=0.018), CAD (OR, 6.252; 95% CI: 2.171-18.004; p=0.001) and congestive heart failure (CHF) (OR, 5.917; 95% CI 1.069-32.258; p=0.042), were significantly associated with mortality. Current smoking (OR, 13.014; 95% CI: 5.058-33.480; p<0.0001) and former smoking (OR, 6.507; 95% CI 2.731-15.501; p<0.0001) were also risk factors for mortality. CONCLUSION: Smoking, older age, COPD, and CAD were risk factors for ICU admission and mortality in patients with COVID-19. CHF was not a risk factor for ICU admission; however, it was a risk factor for mortality. | input | 2 | 77,492 | 13 | 232,068 |
Please summerize the given abstract to a title | instruction | 0 | 77,513 | 13 | 232,129 |
Intubation among emergency department and hospitalized patients with COVID-19: A retrospective analysis of 18,467 patients | output | 1 | 77,513 | 13 | 232,130 |
INTRODUCTION: As of December 18, 2020, there have been nearly 17 million cases of COVID-19 in the United States. Early studies reported intubation rates between 12.2-29.2% with varying criteria between sites and as the pandemic has progressed. With the rapid spread of infection and increased use of ventilators, triage of patients based on factors such as their past medical history can help guide resource allocation. This retrospective study examined a large multi-center cohort of patients with COVID-19 infection to identify risk factors associated with intubation. METHODS: Adult patients with an emergency department or inpatient encounter from December 1, 2019 to June 30, 2020 with COVID-19 were included in the Cerner COVID-19 dataset, which was extracted from 62 hospital systems throughout the United States. Only patients with at least two previous visits in the past 5 years were included. ICD-10 diagnosis codes, demographic data, and discharge status were collected and classified based on intubation status. Logistic regression model identified independently associated risk factors for intubation. RESULTS:18,467 patients with confirmed SARS-CoV-2 infection were identified, with 5,525 seen only in the ED and 12,942 hospitalized. The mean age was 54.3 ± 20.5 years, the mean body mass index (BMI) was 30.42 ± 11.72, 8,397 (45.6%) patients were male, and 938 (7.2%) were intubated. 1,829 (14.1%) patients died in the hospital and 4,185 (22.7%) had a non-routine discharge, which encompasses home health care, short-term hospital, other facility including intermediate care and skilled nursing home. Using multivariate logistic regression, patients who were intubated were more likely to present with stroke, pneumonia, acute kidney injury, septic shock, respiratory failure, cardiac arrest, and encephalopathy. From patient demographics and past medical history, male sex (p=0.011), age > 35 (p=0.035 for 35-49 years old;p<0.001 for >50 years old), BMI > 30 (p=0.013 for BMI 30-40;p=0.004 for BMI >40), and previous respiratory failure (p=0.014) were independently associated with intubation. CONCLUSIONS: Among patients with COVID-19, male sex, increased age, BMI > 30, and previous respiratory failure were independently associated with the risk for intubation. Intubated patients were also more likely to present with stroke, pneumonia, acute kidney injury, septic shock, respiratory failure, cardiac arrest, and encephalopathy. Clinicians should be aware of these independent risk factors for intubation to facilitate resource allocation and minimize the possibility of unanticipated crash intubations. | input | 2 | 77,513 | 13 | 232,131 |
Please summerize the given abstract to a title | instruction | 0 | 77,611 | 13 | 232,423 |
Prediction Models for the Clinical Severity of Patients With COVID-19 in Korea: Retrospective Multicenter Cohort Study | output | 1 | 77,611 | 13 | 232,424 |
BACKGROUND: Limited information is available about the present characteristics and dynamic clinical changes that occur in patients with COVID-19 during the early phase of the illness. OBJECTIVE: This study aimed to develop and validate machine learning models based on clinical features to assess the risk of severe disease and triage for COVID-19 patients upon hospital admission. METHODS: This retrospective multicenter cohort study included patients with COVID-19 who were released from quarantine until April 30, 2020, in Korea. A total of 5628 patients were included in the training and testing cohorts to train and validate the models that predict clinical severity and the duration of hospitalization, and the clinical severity score was defined at four levels: mild, moderate, severe, and critical. RESULTS: Out of a total of 5601 patients, 4455 (79.5%), 330 (5.9%), 512 (9.1%), and 301 (5.4%) were included in the mild, moderate, severe, and critical levels, respectively. As risk factors for predicting critical patients, we selected older age, shortness of breath, a high white blood cell count, low hemoglobin levels, a low lymphocyte count, and a low platelet count. We developed 3 prediction models to classify clinical severity levels. For example, the prediction model with 6 variables yielded a predictive power of >0.93 for the area under the receiver operating characteristic curve. We developed a web-based nomogram, using these models. CONCLUSIONS: Our prediction models, along with the web-based nomogram, are expected to be useful for the assessment of the onset of severe and critical illness among patients with COVID-19 and triage patients upon hospital admission. | input | 2 | 77,611 | 13 | 232,425 |
Please summerize the given abstract to a title | instruction | 0 | 77,622 | 13 | 232,456 |
The decrease of CD4 T cell is associated with mortality in critical inpatients with COVID-19 | output | 1 | 77,622 | 13 | 232,457 |
Background: The 2019 novel coronavirus (SARS-CoV-2) has caused an outbreak in the world. The critically ill patients had a high mortality. However, the possible risk factors of critical patients with coronavirus disease 2019 (COVID-19) are not fully known. We aim to investigate the risk factors in critical patients with COVID-19 and to address their role in predicting disease progression.Methods In this single-centered, retrospective, observational study, we enrolled 91 critically ill adult patients with COVID-19 in Renmin Hospital of Wuhan University between Jan 20, 2020 and Feb 28, 2020. Data were collected using a standard method including clinical records and laboratory findings.Results 39 patients (42.9%) were dead and 52 patients (57.1%) were cured and discharged before Mar 22, 2020. CD4 T cell count, CD8 T cell count and glomerular filtration rate were significantly lower in non-survivors than in survivors. However, the non-survivors presented a higher proportion of D-dimer, Cardiac troponin and immunoglobulin G than in survivors. Intravenous immunoglobulin was more common in survivors than in non-survivors. On multivariate analysis, D-dimer (༞1 µg/mL, OR = 9.53, 95% CI, 2.53–35.88), CD4 + T count (༜200/µl, OR = 9.68, 95%CI, 2.76-40.00 ) and cardiac troponin (༞0.04 ng/mL, OR = 5.73, 95% CI, 1.86–17.66) were independent risk factors for mortality.Conclusion The decrease of CD4 T cell is associated with higher risk mortality in critical inpatients with COVID-19. Intravenous immunoglobulin was more common in survivors than in non-survivors. | input | 2 | 77,622 | 13 | 232,458 |
Please summerize the given abstract to a title | instruction | 0 | 77,648 | 13 | 232,534 |
Elevated fasting blood glucose within the first week of hospitalization was associated with progression to severe illness of COVID-19 in patients with preexisting diabetes: A multicenter observational study | output | 1 | 77,648 | 13 | 232,535 |
Highlights Fasting blood glucose < 10 mmol/L was proposed as a target of glycemic control during the first week of hospitalization in patients with preexisting diabetes. Poor HbA1c levels prior to coronavirus disease 2019 (COVID-19) might not be associated with severity among patients with preexisting diabetes. Mean blood glucose seemed not to be associated with poor prognosis of COVID-19. | input | 2 | 77,648 | 13 | 232,536 |
Please summerize the given abstract to a title | instruction | 0 | 77,704 | 13 | 232,702 |
Survival Analysis of COVID-19 Patients in Russia Using Machine Learning | output | 1 | 77,704 | 13 | 232,703 |
The current pandemic can likely have several waves and will require a major effort to save lives and provide optimal treatment. The efficient clinical resource planning and efficient treatment require identification of risk groups and specific clinical features of the patients. In this study we develop analyze mortality for COVID19 patients in Russia. We identify comorbidities and risk factors for different groups of patients including cardiovascular diseases and therapy. In the study we used a Russian national COVID registry, that provides sophisticated information about all the COVID-19 patients in Russia. To analyze Features importance for the mortality we have calculated Shapley values for the "mortality" class and ANN hidden layer coefficients for patient lifetime. We calculated the distribution of days spent in hospital before death to show how many days a patient occupies a bed depending on the age and the severity of the disease to allow optimal resource planning and enable age-based risk assessment. Predictors of the days spent in hospital were calculated using Pearson correlation coefficient. Decisions trees were developed to classify the patients into the groups and reveal the lethality factors. | input | 2 | 77,704 | 13 | 232,704 |
Please summerize the given abstract to a title | instruction | 0 | 77,726 | 13 | 232,768 |
A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine | output | 1 | 77,726 | 13 | 232,769 |
BACKGROUND: We performed a phenome-wide association study to identify pre-existing conditions related to Coronavirus disease 2019 (COVID-19) prognosis across the medical phenome and how they vary by race. METHODS: The study is comprised of 53,853 patients who were tested/diagnosed for COVID-19 between 10 March and 2 September 2020 at a large academic medical center. RESULTS: Pre-existing conditions strongly associated with hospitalization were renal failure, pulmonary heart disease, and respiratory failure. Hematopoietic conditions were associated with intensive care unit (ICU) admission/mortality and mental disorders were associated with mortality in non-Hispanic Whites. Circulatory system and genitourinary conditions were associated with ICU admission/mortality in non-Hispanic Blacks. CONCLUSIONS: Understanding pre-existing clinical diagnoses related to COVID-19 outcomes informs the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery. | input | 2 | 77,726 | 13 | 232,770 |
Please summerize the given abstract to a title | instruction | 0 | 77,808 | 13 | 233,014 |
Secondary bacterial co-infection and mortality risk in intubated patients with critically ill COVID19 | output | 1 | 77,808 | 13 | 233,015 |
Background:Secondary bacterial co-infections are not common in patients with COVID19.However ,the rate of bacterial pneumonia is high in critically ill patients with COVID19 and there is increased risk of joining bacterial infection by increasing of severity of COVID19 and achieving maximal rate in intubated patients.And there is increased rate of overuse of broad-spectrum antibiotics in patients admitted to the intensive care unit(ICU) department.Objective:The aim of our investigation was to evaluate the rate of secondary bacterial co-infection in critically ill patients with COVID19 and its impact to the mortality rate in such patients.Method and measurements:Of 129 COVID-19 patients admitted in our ICU from 21 April 2020 to 15 August 2020,93 have been mechanically ventilated.BALF was performed in 68 patients during ICU stay and all were suspected of bacterial pneumonia.Bacterial cultures of BALF positively defined in case of grew with significant amount of bacteria(ie,>-104 colony-forming units/ml).All pneumonia cases in intubated patients was assessed as Ventilator-associated pneumonia(VAP) and was defined as eraly-onset and late onset as pneumonia diagnosed before and after 5 days of mechanical ventilation, respectively.Results:In 51% (n=35) of 78 patients was obtained bacterial cultires and just in 5(7.4%) of 68 patients was evaluated the early-onset VAP and in remaining 63 patients (92%) of patients was detected late-onset VAP.VAP in patients commonly was associated with ARDS compared to non-VAP patients(OR 3.57[0.89-7.92]CI 95%;p=0.001) and although late-onset VAP in patients significantly often was associated with kidney failure (OR 2.95[075-6.32]CI 95%;p=0.003) and septic shock 3.68[1.05-8.21] CI95%;p=0.001).In all early-onset pneumonia patients ,bacterial pathogens were most commonly gram positive bacteria(100%) and 80%(4/5) were susceptible to cefotaxime, cefepime, piperacillin-tazobactam, and meropenem.Conversely, in late-onset VAP, most bacterial pathogens were gram-negative bacteria(29/30) and muti-drug resistant (MDR)pathogens(14/30).Among MDR gram-negative bacteria causing late-onset VAP, most commonly was obtained Acinotebacter baumannii(9/30),followed Pseudomonas aeruginosa(6/30),folowed Klebsiella pneumoniae (5/30) and Escherichia coli(5/30) and Aspergillus fumigates(5/30).And just 13% of patients with late-onset VAP were susceptible to piperacillin-tazobactam,17% were susceptible to cefepime and 34% were susceptible to meropenem.Late-onset VAP was associated with high mortality rate among intubated compared to early-onset VAP and non-VAP patients ( OR 4.87[1,54-10.32] CI95%;p=0.001;OR 6.33[1.58-14.25] CI 95%;p=0.0008).Conclusions:Secondary bacterial co-infection is common in intubated critically ill patients with COVID19 and most commonly presentation of bacterial infection is late-onset VAP causing by multi-drug resitant pathogens which are associated commonly with ARDS, kidney failure and septic shock.In patients with late-onset VAP MDR pathogens may predict high mortality rate. | input | 2 | 77,808 | 13 | 233,016 |
Please summerize the given abstract to a title | instruction | 0 | 77,833 | 13 | 233,089 |
Active pulmonary tuberculosis and coronavirus disease 2019: A systematic review and meta-analysis | output | 1 | 77,833 | 13 | 233,090 |
OBJECTIVE: The proportion of COVID-19 patients having active pulmonary tuberculosis, and its impact on COVID-19 related patient outcomes, is not clear. We conducted this systematic review to evaluate the proportion of patients with active pulmonary tuberculosis among COVID-19 patients, and to assess if comorbid pulmonary tuberculosis worsens clinical outcomes in these patients. METHODS: We queried the PubMed and Embase databases for studies providing data on (a) proportion of COVID-19 patients with active pulmonary tuberculosis or (b) severe disease, hospitalization, or mortality among COVID-19 patients with and without active pulmonary tuberculosis. We calculated the proportion of tuberculosis patients, and the relative risk (RR) for each reported outcome of interest. We used random-effects models to summarize our data. RESULTS: We retrieved 3,375 citations, and included 43 studies, in our review. The pooled estimate for proportion of active pulmonary tuberculosis was 1.07% (95% CI 0.81%-1.36%). COVID-19 patients with tuberculosis had a higher risk of mortality (summary RR 1.93, 95% CI 1.56–2.39, from 17 studies) and for severe COVID-19 disease (summary RR 1.46, 95% CI 1.05–2.02, from 20 studies), but not for hospitalization (summary RR 1.86, 95% CI 0.91–3.81, from four studies), as compared to COVID-19 patients without tuberculosis. CONCLUSION: Active pulmonary tuberculosis is relatively common among COVID-19 patients and increases the risk of severe COVID-19 and COVID-19-related mortality. | input | 2 | 77,833 | 13 | 233,091 |
Please summerize the given abstract to a title | instruction | 0 | 77,858 | 13 | 233,164 |
Reply to: Comment on Predicting In‐Hospital Mortality in COVID‐19 Older Patients with Specifically Developed Scores | output | 1 | 77,858 | 13 | 233,165 |
This letter comments on the letter by Alain Putot | input | 2 | 77,858 | 13 | 233,166 |
Please summerize the given abstract to a title | instruction | 0 | 77,930 | 13 | 233,380 |
Development of a Predictive Score for COVID-19 Diagnosis based on Demographics and Symptoms in Patients Attended at a Dedicated Screening Unit | output | 1 | 77,930 | 13 | 233,381 |
Background: The diagnosis of COVID-19 based on clinical evaluation is difficult because symptoms often overlap with other respiratory diseases. A clinical score predictive of COVID-19 based on readily assessed variables may be useful in settings with restricted or no access to molecular diagnostic tests. Methods: A score based on demographics and symptoms was developed in a cross-sectional study including patients attended in a dedicated COVID-19 screening unit. A backward stepwise logistic regression model was constructed and values for each variable were assigned according to their {beta} coefficient values in the final model. Receiver operating characteristic (ROC) curve was constructed and its area under the curve (AUC) was calculated. Results: A total of 464 patients were included: 98 (21.1%) COVID-19 and 366 (78.9%) non-COVID-19 patients. The score included variables independently associated with COVID-19 in the final model: age equal or above 60 years (2 points), fever (2), dyspnea (1), fatigue (1 point) and coryza (-1). Score values were significantly higher in COVID-19 than non-COVID-19 patients: median (Interquartile Range), 3 (2-4), and 1 (0-2), respectively; P<0.001. The score had an AUC of 0.80 (95% Confidence Interval [CI], 0.76-0.86). The specificity of scores equal or greater than 4 and 5 points were 90.4 (95%CI, 87.0-93.3) and 96.2 (95%CI, 93.7-97.9), respectively. Conclusions: This preliminary score based on patients symptoms is a feasible tool that may be useful in setting with restricted or no access to molecular tests in a pandemic period, owing to the high specificity. Further studies are required to validate the score in other populations. | input | 2 | 77,930 | 13 | 233,382 |
Please summerize the given abstract to a title | instruction | 0 | 77,935 | 13 | 233,395 |
Systemic thrombosis in a large cohort of COVID-19 patients despite thromboprophylaxis: A retrospective study | output | 1 | 77,935 | 13 | 233,396 |
BACKGROUND: Incidence of thrombotic events associated to Coronavirus disease-2019 (COVID-19) is difficult to assess and reported rates differ significantly. Optimal thromboprophylaxis is unclear. OBJECTIVES: We aimed to analyze the characteristics of patients with a confirmed thrombotic complication including inflammatory and hemostatic parameters, compare patients affected by arterial vs venous events and examine differences between survivors and non-survivors. We reviewed compliance with thromboprophylaxis and explored how the implementation of a severity-adjusted protocol could have influenced outcome. METHODS: Single-cohort retrospective study of COVID-19 patients admitted, from March 3 to May 3 2020, to the Infanta Leonor University Hospital in Madrid, epicenter of the Spanish outbreak. RESULTS: Among 1127 patients, 80 thrombotic events were diagnosed in 69 patients (6.1% of the entire cohort). Forty-three patients (62%) suffered venous thromboembolism, 18 (26%) arterial episodes and 6 (9%) concurrent venous and arterial thrombosis. Most patients (90%) with a confirmed thrombotic complication where under low-molecular-weight heparin treatment. Overt disseminated intravascular coagulation (DIC) was rare. Initial ISTH DIC score and pre-event CRP were significantly higher among non-survivors. In multivariate analysis, arterial localization was an independent predictor of mortality (OR = 18, 95% CI: 2.4-142, p < .05). CONCLUSIONS: Despite quasi-universal thromboprophylaxis, COVID-19 lead to a myriad of arterial and venous thrombotic events. Considering the subgroup of patients with thrombotic episodes, arterial events appeared earlier in the course of disease and conferred very poor prognosis, and an ISTH DIC score ≥ 3 at presentation was identified as a potential predictor of mortality. Severity-adjusted thromboprophylaxis seemed to decrease the number of events and could have influenced mortality. Randomized controlled trials are eagerly awaited. | input | 2 | 77,935 | 13 | 233,397 |
Please summerize the given abstract to a title | instruction | 0 | 78,032 | 13 | 233,686 |
Risk factors for bacterial infections in patients with moderate to severe COVID-19: A case control study | output | 1 | 78,032 | 13 | 233,687 |
ABSTRACT Objective Bacterial infections are known to complicate respiratory viral infections and are associated with adverse outcomes in COVID-19 patients. A case control study was conducted to determine risk factors for bacterial infections where cases were defined as moderate to severe/critical COVID-19 patients with bacterial infection and those without were included as controls. Logistic regression analysis was performed. Results Out of a total of 50 cases and 50 controls, greater proportion of cases had severe or critical disease at presentation as compared to control i.e 80% vs 30% (p<0.001). Hospital acquired pneumonia (72%) and Gram negative organisms (82%) were predominant. Overall antibiotic utilization was 82% and was 64% in patients who had no evidence of bacterial infection. The median length of stay was significantly longer among cases compared to controls (12.5 versus 7.5 days) (p=0.001). The overall mortality was 30%, with comparatively higher proportion of deaths among cases (42% versus 18%) (p=0.009). Severe or critical COVID-19 at presentation (AOR: 4.42 times; 95% CI; 1.63-11.9) and use of steroids (AOR: 4.60; 95% CI 1.24-17.05) were independently associated with risk of bacterial infections. These findings have implications for antibiotic stewardship as antibiotics can be reserved for those at higher risk for bacterial superinfections. Key words Bacteria ; COVID-19; nosocomial infections; co-infection. | input | 2 | 78,032 | 13 | 233,688 |
Please summerize the given abstract to a title | instruction | 0 | 78,058 | 13 | 233,764 |
Mediastinal Lymphadenopathy As A Predictor Of Worse Outcome In Severe Covid-19 Cases | output | 1 | 78,058 | 13 | 233,765 |
BACKGROUND: This cross-sectional study is aimed at evaluating the association of mediastinal lymphadenopathy with COVID-19 prognosis in severe cases. Place and Duration of Study: Department of Medicine, Pak Emirates Military Hospital, Pakistan, from June to July 2020. METHODS: One hundred and fifty (150) laboratory-confirmed SARS CoV-2 infected, severe cases in Intensive Care Unit/ High Dependency Unit were included. These cases were divided into two categories, i.e., with and without mediastinal lymphadenopathy on High Resolution Computed Tomography chest. The two categories were compared on the basis of data obtained including age, gender, comorbid, White Blood Cell count, lymphocyte count, median days of hospitalization, need for invasive ventilation, Intensive Care Unit admission, clinical outcome and High-Resolution Computed Tomography chest findings. The data was compiled on a questionnaire and analysed on SPSS 24. RESULTS: Total 155 severe COVID-19 patients were reviewed, out of which 36 (23.2%) had mediastinal lymphadenopathy (category 1) and 119 (76.8%) had no mediastinal lymphadenopathy (category 2). Laboratory findings including median of white blood cells and lymphocyte percentage had no significant change in both categories. Intensive care unit admissions were 12 (33.3%) and 56 (47.1%) in category 1 and 2 respectively. Median days of hospitalization (8 days) and mortality rate (16%) were almost the same in both categories. CONCLUSIONS: Our study concludes that presence of mediastinal lymphadenopathy in severe COVID-19 cases is not associated with worse outcome. However, overall prevalence of mediastinal lymphadenopathy in severe cases is high (23.2%). | input | 2 | 78,058 | 13 | 233,766 |
Please summerize the given abstract to a title | instruction | 0 | 78,085 | 13 | 233,845 |
Mortality rates in transplant recipients and transplantation candidates in a high prevalence COVID-19 environment | output | 1 | 78,085 | 13 | 233,846 |
BACKGROUND: The risk of COVID-19 infection in transplant recipients is unknown. Patients on dialysis may be exposed to greater risk of infection due to an inability to isolate. Consideration of these competing risks is important before restarting suspended transplant programs. This study compared outcomes in kidney and kidney/pancreas transplant recipients with those on the waiting list, following admission with COVID-19 in a high prevalence region. METHODS: Audit data from all 6 London transplant centres were amalgamated. Demographic and laboratory data were collected and outcomes included mortality, intensive care (ITU) admission and ventilation. Adult patients who had undergone a kidney or kidney/pancreas transplant, and those active on the transplant waiting list at the start of the pandemic were included. RESULTS: 121 transplant recipients (TR) and 52 waiting list patients (WL) were admitted to hospital with COVID-19. 36 TR died (30%), whilst 14 WL patients died (27% p=0.71). There was no difference in rates of admission to ITU or ventilation. 24% of TR required renal replacement therapy, and 12% lost their grafts. Lymphocyte nadir and D-dimer peak showed no difference in those who did and did not die. No other co-morbidities or demographic factors were associated with mortality, except for age (odds ratio of 4.3 [95% CI 1.8 - 10.2] for mortality if aged over 60 years) in TR. CONCLUSIONS: Transplant recipients and waiting list patients have similar mortality rates after hospital admission with COVID-19. Mortality was higher in older transplant recipients. These data should inform decisions about transplantation in the COVID era. | input | 2 | 78,085 | 13 | 233,847 |
Please summerize the given abstract to a title | instruction | 0 | 78,110 | 13 | 233,920 |
Kidney damage in COVID-19 patients with or without chronic kidney disease: Analysis of clinical characteristics and related risk factors | output | 1 | 78,110 | 13 | 233,921 |
COVID-19 poses more risk to patients who already suffer from other diseases, particularly respiratory disorder In this study, we analyzed the clinical characteristics and related risk factors during hospitalization of COVID-19 patients admitted with kidney damage A total of 102 COVID-19 patients with kidney damage [irrespective of their chronic kidney disease (CKD) history] during hospitalization were included in this study The patients were divided into a core group and a group who developed critical illness or death Clinical data included age, gender, length of hospitalization, clinical manifestations, medical history, hypersensitive C-reactive protein (hs -CRP), high serum creatinine, low cardiac troponin I (cTnI), and hemoglobin Univariate and multivariate logistic regression models were used to analyze the risk factors of patients' outcome Among the outcomes, 75 patients (73 53%) were cured, 27 (26 47%) developed to critical illness or death, 20 (19 61%) of them died A total of 36 (4 26%) out of 845 COVID-19 patients, developed acute kidney injury (AKI) Decreased oxygen saturation, elevated hs-CRP, elevated serum creatinine, elevated cTnI, and anemia were related factors for COVID-19 patients who developed to critical illness or death (P <0 05) Decreased oxygen saturation, elevated hs-CRP and anemia were not independent factors, but elevated serum creatinine and elevated cTnI were independent factors for COVID-19 patients who developed to critical illness or death (P <0 05) Among COVID-19 patients with or without CKD but with kidney damage during hospitalization, patients with elevated serum creatinine and elevated Tnl, more likely to developed critical illness or death | input | 2 | 78,110 | 13 | 233,922 |
Please summerize the given abstract to a title | instruction | 0 | 78,139 | 13 | 234,007 |
Development and validation of a clinical and genetic model for predicting risk of severe COVID-19 | output | 1 | 78,139 | 13 | 234,008 |
Clinical and genetic risk factors for severe coronavirus disease 2019 (COVID-19) are often considered independently and without knowledge of the magnitudes of their effects on risk. Using severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) positive participants from the UK Biobank, we developed and validated a clinical and genetic model to predict risk of severe COVID-19. We used multivariable logistic regression on a 70% training dataset and used the remaining 30% for validation. We also validated a previously published prototype model. In the validation dataset, our new model was associated with severe COVID-19 (odds ratio per quintile of risk = 1.77, 95% confidence interval (CI) 1.64–1.90) and had acceptable discrimination (area under the receiver operating characteristic curve = 0.732, 95% CI 0.708–0.756). We assessed calibration using logistic regression of the log odds of the risk score, and the new model showed no evidence of over- or under-estimation of risk (α = −0.08; 95% CI −0.21−0.05) and no evidence or over-or under-dispersion of risk (β = 0.90, 95% CI 0.80–1.00). Accurate prediction of individual risk is possible and will be important in regions where vaccines are not widely available or where people refuse or are disqualified from vaccination, especially given uncertainty about the extent of infection transmission among vaccinated people and the emergence of SARS-CoV-2 variants of concern. | input | 2 | 78,139 | 13 | 234,009 |
Please summerize the given abstract to a title | instruction | 0 | 78,218 | 13 | 234,244 |
Variability in COVID-19 in-hospital mortality rates between national health service trusts and regions in England: A national observational study for the Getting It Right First Time Programme | output | 1 | 78,218 | 13 | 234,245 |
BACKGROUND: A key first step in optimising COVID-19 patient outcomes during future case-surges is to learn from the experience within individual hospitals during the early stages of the pandemic. The aim of this study was to investigate the extent of variation in COVID-19 outcomes between National Health Service (NHS) hospital trusts and regions in England using data from March–July 2020. METHODS: This was a retrospective observational study using the Hospital Episode Statistics administrative dataset. Patients aged ≥ 18 years who had a diagnosis of COVID-19 during a hospital stay in England that was completed between March 1st and July 31st, 2020 were included. In-hospital mortality was the primary outcome of interest. In secondary analysis, critical care admission, length of stay and mortality within 30 days of discharge were also investigated. Multilevel logistic regression was used to adjust for covariates. FINDINGS: There were 86,356 patients with a confirmed diagnosis of COVID-19 included in the study, of whom 22,944 (26.6%) died in hospital with COVID-19 as the primary cause of death. After adjusting for covariates, the extent of the variation in-hospital mortality rates between hospital trusts and regions was relatively modest. Trusts with the largest baseline number of beds and a greater proportion of patients admitted to critical care had the lowest in-hospital mortality rates. INTERPRETATION: There is little evidence of clustering of deaths within hospital trusts. There may be opportunities to learn from the experience of individual trusts to help prepare hospitals for future case-surges. | input | 2 | 78,218 | 13 | 234,246 |
Please summerize the given abstract to a title | instruction | 0 | 78,259 | 13 | 234,367 |
Venous and arterial thromboembolic complications in COVID-19 patients admitted to an academic hospital in Milan, Italy | output | 1 | 78,259 | 13 | 234,368 |
BACKGROUND: Few data are available on the rate and characteristics of thromboembolic complications in hospitalized patients with COVID-19. METHODS: We studied consecutive symptomatic patients with laboratory-proven COVID-19 admitted to a university hospital in Milan, Italy (13.02.2020-10.04.2020). The primary outcome was any thromboembolic complication, including venous thromboembolism (VTE), ischemic stroke, and acute coronary syndrome (ACS)/myocardial infarction (MI). Secondary outcome was overt disseminated intravascular coagulation (DIC). RESULTS: We included 388 patients (median age 66 years, 68% men, 16% requiring intensive care [ICU]). Thromboprophylaxis was used in 100% of ICU patients and 75% of those on the general ward. Thromboembolic events occurred in 28 (7.7% of closed cases; 95%CI 5.4%-11.0%), corresponding to a cumulative rate of 21% (27.6% ICU, 6.6% general ward). Half of the thromboembolic events were diagnosed within 24 h of hospital admission. Forty-four patients underwent VTE imaging tests and VTE was confirmed in 16 (36%). Computed tomography pulmonary angiography (CTPA) was performed in 30 patients, corresponding to 7.7% of total, and pulmonary embolism was confirmed in 10 (33% of CTPA). The rate of ischemic stroke and ACS/MI was 2.5% and 1.1%, respectively. Overt DIC was present in 8 (2.2%) patients. CONCLUSIONS: The high number of arterial and, in particular, venous thromboembolic events diagnosed within 24 h of admission and the high rate of positive VTE imaging tests among the few COVID-19 patients tested suggest that there is an urgent need to improve specific VTE diagnostic strategies and investigate the efficacy and safety of thromboprophylaxis in ambulatory COVID-19 patients. | input | 2 | 78,259 | 13 | 234,369 |
Please summerize the given abstract to a title | instruction | 0 | 78,273 | 13 | 234,409 |
New-onset hyperglycaemia and prolonged systemic corticosteroids therapy in mild COVID-19 patients as major risk factors for invasive mucormycosis: a preliminary study | output | 1 | 78,273 | 13 | 234,410 |
BACKGROUND AND PURPOSE: Rapid surge of invasive mucormycosis has surprised the Indian healthcare system amidst the coronavirus disease-19 (COVID-19) pandemic. Hence, there is an urgent need to find the risk factors for the sudden rise in cases of invasive mucormycosis among COVID-19 patients. This study aimed to find crucial risk factors for the sudden surge of invasive mucormycosis in India MATERIALS AND METHODS: This case-control study included 77 cases of COVID-19 associated mucormycosis (CAM) who matched the controls (45 controls) in terms of age , gender, and COVID-19 disease severity. The control group included subjects that matched controls without mucormycosis confirmed by reverse transcription-polymerase chain reaction at our tertiary care center during April-May 2021. Probable predisposing factors, such as duration of diabetes mellitus (DM), history of recent hospitalization, duration of hospital stay, mode of the received oxygen supplementation, and use of steroids, zinc, vitamin c, and any other specific drugs were collected and compared between the two groups. Moreover, the laboratory parameters, like glycated hemoglobin (HbA1c), highly sensitive C-reactive protein (hs-CRP), and erythrocyte sedimentation rate (ESR) were analyzed to find out the significant association with CAM RESULTS: DM (Odds ratio=7.7, 95% CI 3.30-18.12; P=<0.0001) and high glycated hemoglobin level (HbA1c>7.5 gm %) (odds ratio=6.2, 95% CI 1.4-26.7; P=0.014) were significant risk factors for the development of invasive mucormycosis among the COVID-19 cases. A higher number of mild COVID-19 cases developed CAM, compared to the moderate to severe cases (59.7% vs 40.3%). Use of systemic corticosteroids (odd ratio=5 with 95% CI 1.5-16.9; P=0.007) was found to be a risk factor for invasive mucormycosis only in mild COVID-19 cases. Use of oxygen, zinc, and vitamin C supplementation, and proprietary medicine did not lead to a significant risk of invasive mucormycosis in cases, compared to controls. Cases with invasive mucormycosis had a higher level of inflammatory markers (hs-CRP and ESR, P=<0.001 and 0.002, respectively), compared to the controls. CONCLUSION: Uncontrolled and new-onset DM and the use of systemic corticosteroids in mild cases were significantly associated with a higher risk of invasive mucormycosis in COVID-19 cases. There should be a strong recommendation against the use of systemic corticosteroids in mild COVID-19 cases | input | 2 | 78,273 | 13 | 234,411 |
Please summerize the given abstract to a title | instruction | 0 | 78,388 | 13 | 234,754 |
Mortality and Severity in COVID-19 Patients on ACEIs and ARBs—A Systematic Review, Meta-Analysis, and Meta-Regression Analysis | output | 1 | 78,388 | 13 | 234,755 |
Purpose: The primary objective of this systematic review is to assess association of mortality in COVID-19 patients on Angiotensin-converting-enzyme inhibitors (ACEIs) and Angiotensin-II receptor blockers (ARBs). A secondary objective is to assess associations with higher severity of the disease in COVID-19 patients. Materials and Methods: We searched multiple COVID-19 databases (WHO, CDC, LIT-COVID) for longitudinal studies globally reporting mortality and severity published before January 18th, 2021. Meta-analyses were performed using 53 studies for mortality outcome and 43 for the severity outcome. Mantel-Haenszel odds ratios were generated to describe overall effect size using random effect models. To account for between study results variations, multivariate meta-regression was performed with preselected covariates using maximum likelihood method for both the mortality and severity models. Result: Our findings showed that the use of ACEIs/ARBs did not significantly influence either mortality (OR = 1.16 95% CI 0.94–1.44, p = 0.15, I(2) = 93.2%) or severity (OR = 1.18, 95% CI 0.94–1.48, p = 0.15, I(2) = 91.1%) in comparison to not being on ACEIs/ARBs in COVID-19 positive patients. Multivariate meta-regression for the mortality model demonstrated that 36% of between study variations could be explained by differences in age, gender, and proportion of heart diseases in the study samples. Multivariate meta-regression for the severity model demonstrated that 8% of between study variations could be explained by differences in age, proportion of diabetes, heart disease and study country in the study samples. Conclusion: We found no association of mortality or severity in COVID-19 patients taking ACEIs/ARBs. | input | 2 | 78,388 | 13 | 234,756 |
Please summerize the given abstract to a title | instruction | 0 | 78,398 | 13 | 234,784 |
Association of procalcitonin levels with the progression and prognosis of hospitalized patients with COVID-19 | output | 1 | 78,398 | 13 | 234,785 |
Rationale: Coronavirus disease 2019 (COVID-19) was first announced in Wuhan, and has rapidly evolved into a pandemic. However, the risk factors associated with the severity and mortality of COVID-19 are yet to be described in detail. Methods: We retrospectively reviewed the information of 1525 cases from the Leishenshan Hospital in Wuhan. Univariate and multivariate Cox regression analyses were generated to explore the relationship between procalcitonin (PCT) level and the progression and prognosis of COVID-19. Univariate and multivariate logistic regression analyses were performed to explore the relationship between disease severity in hospitalized patients and their PCT levels. Survival curves and the cumulative hazard function for COVID-19 progression were conducted in the two groups. To further detect the relationship between the computed tomography score and survival days, curve-fitting analyses were performed. Results: Patients in the elevated PCT group had a higher incidence of severe and critical severity conditions (P < 0.001), death, and higher computed tomography (CT) scores. There was an association between elevated PCT levels and mortality in the univariate ((hazard ratio [1], 3.377; 95% confidence interval [2], 1.012-10.344; P = 0.033) and multivariate Cox regression analysis (HR, 4.933; 95% CI, 1.170-20.788; P = 0.030). Similarly, patients with elevated PCT were more likely to have critically severe disease conditions in the univariate (odds ratio [2], 7.247; 95% CI, 3.559-14.757; P < 0.001) and multivariate logistic regression analysis (OR, 10.679; 95% CI, 4.562-25.000; P < 0.001). Kaplan-Meier curves showed poorer prognosis for patients with elevated PCT (P = 0.024). The CT score 1 for patients with elevated PCT peaked at day 40 following the onset of symptoms then decreased gradually, while their total CT score was relatively stable. Conclusion: PCT level was shown as an independent risk factor of in-hospital mortality among COVID-19 patients. Compared with inpatients with normal PCT levels, inpatients with elevated PCT levels had a higher risk for overall mortality and critically severe disease. These findings may provide guidance for improving the prognosis of patients with critically severe COVID-19. | input | 2 | 78,398 | 13 | 234,786 |
Please summerize the given abstract to a title | instruction | 0 | 78,425 | 13 | 234,865 |
Patient-reported symptom severity and pulse oximetry in the COVID-19 remote monitoring programme in ireland | output | 1 | 78,425 | 13 | 234,866 |
Rationale: A total of 60,287 (1,267/100,000) cases of Covid-19 (SARS-CoV-2) were recorded in Ireland by 30 October 2020. An important strategy to free up in-hospital capacity was development of a remote monitoring platform to support at-home care or early discharge of lower-risk patients with mild/moderate Covid-19 symptoms. Methods: The monitoring platform consisted of a patient-facing app + pulse oximeter (Bluetoothconnected Nonin 3230) enabling patients to record symptoms (e.g. breathlessness, diarrhea;severity rated on a 10-point scale), temperature & oxygen saturation (SpO2). Patients were prompted to record measurement 4 times/day. Patient-recorded data was viewed in real time by their healthcare centre via a dedicated web-based monitoring portal. Criteria for remote monitoring included: Covid-19 symptoms, positive for SARS-CoV-2, young age, absence of serious concomitant conditions, need for continued observation post-discharge. Treatment centres emailed app installation instructions and supplied a pulse oximeter to their patients. Treatment centres & patients received alerts if pulse oximetry values crossed pre-defined thresholds. Results: Between 13 March and 31 October 2020, 1,045 patients at 8 primary & 15 secondary care centres had used the remote monitoring platform [median duration: 13 days (interquartile range 10-23 days)]. 11 patients were admitted to hospital and 12 previously hospitalized patients were readmitted. 933 patients (89%) gave consent to use of their pseudonymised data for research. Symptoms and physiological markers of severity of infection varied considerably. 871 patients recorded breathlessness data with 53 rating severity as 6/10 and 23 as 8/10. 300 patients recorded diarrhea data with 24 rating severity as 6/10 and 6 as 8/10 (see Figure). SpO2 data were available for 907 patients. 733 patients reported SpO2 94-96%, 334 reported SpO2 92-93%and 265 patients reported SpO2 ≤91% at least once during the monitoring period. Conclusions: Remote monitoring of Covid-19 in appropriate patients can free up in-hospital capacity. The majority of these patients were willing to provide pseudonymised data to support research on Covid-19. . | input | 2 | 78,425 | 13 | 234,867 |
Please summerize the given abstract to a title | instruction | 0 | 78,434 | 13 | 234,892 |
The demographic characteristics, prognosis, and relationship with cancer subtypes of hospitalized COVID-19 patients with malignancy: A single-center experience | output | 1 | 78,434 | 13 | 234,893 |
Undoubtedly, cancer patients have suffered the most from the COVID-19 pandemic process. However, cancer is a heterogeneous disease, and each patient has responded differently to COVID-19. We aimed to describe the clinical characteristics and outcomes of patients with cancer and COVID-19. We retrospectively reviewed 45 cancer patients hospitalized in the Cerrahpasa Medical Faculty COVID-19 department from March 23 to October 23, 2020. We analyzed the demographic characteristics, symptoms, laboratory findings, treatment, prognosis, and cancer subtypes of patients and mortality who were hospitalized for COVID-19. Between March 23 and October 23, 2020, 45 hospitalized cancer patients who had laboratory-confirmed COVID-19 infection were included, with a median age of 60 years (range: 23-92). Patients were divided into two groups a survivor and a non-survivor. Symptoms, demographic information, comorbidities, treatments for COVID-19, and laboratory findings of the two groups were evaluated separately. Two parameters were found, which showed a significant difference between non-survivors and survivors displaying a disadvantage for COPD and low platelet count (p = 0.044-0.038). The mortality rate of all patients was 66%. The presence of comorbidities such as COPD and low platelet count in cancer patients with COVID-19 infection may draw the attention of physicians. | input | 2 | 78,434 | 13 | 234,894 |
Please summerize the given abstract to a title | instruction | 0 | 78,455 | 13 | 234,955 |
Mortality in patients with diabetes by COVID 19 a systematic review | output | 1 | 78,455 | 13 | 234,956 |
Background: Diabetes mellitus might be associated with severity and death in patients with COVID-19;but its mechanisms are still unknown. Objective: to carry out a systematic review of what has been published so far on mortality in patients with COVID-19 associated with diabetes comorbidity. Methods: : A search was carried out in PubMed, Ovid MEDLINE, EMBASE and EMBASE Classic and Google Scholar databases;up to April 2020 using the search medical subheadings (MeSH) terms : "mortality from Coronavirus", "mortality from COVID-19" and "mortality in patients with diabetes by COVID-19". Enrolled studies were assessed independently by two blinded researchers. Studies quality was assessed using the Jedad scale. The articles score equal or greater than two points were considered highly methodological quality. Results: : Initially, 65 articles were found and 46 were excluded for not meeting the eligibility criteria. Among the 10 remaining, 3 were excluded because had Jedad score lower than two points. Among the remaining seven, two were excluded because they were meta-analysis. Eventually, five articles remained for final analysis. For all, mortality among patients with diabetes was higher than without diabetes. The risk of global mortality among diabetes patients was 8.9 times higher (p<0.0001) than without diabetes The time of diagnosis could be more determining for mortality, meanwhile HB1Ac level was not determining Conclusion: Mortality risk observed by COVID-19 is higher among diabetes patients than healthy age matched peers. This result can be partially explained by hormonal signaling changes, such as blood clotting and abnormal pancreas functioning. | input | 2 | 78,455 | 13 | 234,957 |
Please summerize the given abstract to a title | instruction | 0 | 78,457 | 13 | 234,961 |
Association of Cancer Diagnosis and Therapeutic Stage With Mortality in Pediatric Patients With COVID-19, Prospective Multicenter Cohort Study From Latin America | output | 1 | 78,457 | 13 | 234,962 |
BACKGROUND: Children with cancer are at risk of critical disease and mortality from COVID-19 infection. In this study, we describe the clinical characteristics of pediatric patients with cancer and COVID-19 from multiple Latin American centers and risk factors associated with mortality in this population. METHODS: This study is a multicenter, prospective cohort study conducted at 12 hospitals from 6 Latin American countries (Argentina, Bolivia, Colombia, Ecuador, Honduras and Peru) from April to November 2021. Patients younger than 14 years of age that had an oncological diagnosis and COVID-19 or multisystemic inflammatory syndrome in children (MIS-C) who were treated in the inpatient setting were included. The primary exposure was the diagnosis and treatment status, and the primary outcome was mortality. We defined “new diagnosis” as patients with no previous diagnosis of cancer, “established diagnosis” as patients with cancer and ongoing treatment and “relapse” as patients with cancer and ongoing treatment that had a prior cancer-free period. A frequentist analysis was performed including a multivariate logistic regression for mortality. RESULTS: Two hundred and ten patients were included in the study; 30 (14%) died during the study period and 67% of patients who died were admitted to critical care. Demographics were similar in survivors and non-survivors. Patients with low weight for age (<-2SD) had higher mortality (28 vs. 3%, p = 0.019). There was statistically significant difference of mortality between patients with new diagnosis (36.7%), established diagnosis (1.4%) and relapse (60%), (p <0.001). Most patients had hematological cancers (69%) and they had higher mortality (18%) compared to solid tumors (6%, p= 0.032). Patients with concomitant bacterial infections had higher mortality (40%, p = 0.001). MIS-C, respiratory distress, cardiovascular symptoms, altered mental status and acute kidney injury on admission were associated with higher mortality. Acidosis, hypoxemia, lymphocytosis, severe neutropenia, anemia and thrombocytopenia on admission were also associated with mortality. A multivariate logistic regression showed risk factors associated with mortality: concomitant bacterial infection OR 3 95%CI (1.1–8.5), respiratory symptoms OR 5.7 95%CI (1.7–19.4), cardiovascular OR 5.2 95%CI (1.2–14.2), new cancer diagnosis OR 12 95%CI (1.3–102) and relapse OR 25 95%CI (2.9–214). CONCLUSION: Our study shows that pediatric patients with new onset diagnosis of cancer and patients with relapse have higher odds of all-cause mortality in the setting of COVID-19. This information would help develop an early identification of patients with cancer and COVID-19 with higher risk of mortality. | input | 2 | 78,457 | 13 | 234,963 |
Please summerize the given abstract to a title | instruction | 0 | 78,657 | 13 | 235,561 |
Vital Signs Prediction for COVID-19 Patients in ICU | output | 1 | 78,657 | 13 | 235,562 |
This study introduces machine learning predictive models to predict the future values of the monitored vital signs of COVID-19 ICU patients. The main vital sign predictors include heart rate, respiration rate, and oxygen saturation. We investigated the performances of the developed predictive models by considering different approaches. The first predictive model was developed by considering the following vital signs: heart rate, blood pressure (systolic, diastolic and mean arterial, pulse pressure), respiration rate, and oxygen saturation. Similar to the first approach, the second model was developed using the same vital signs, but it was trained and tested based on a leave-one-subject-out approach. The third predictive model was developed by considering three vital signs: heart rate (HR), respiration rate (RR), and oxygen saturation (SpO [Formula: see text]). The fourth model was a leave-one-subject-out model for the three vital signs. Finally, the fifth predictive model was developed based on the same three vital signs, but with a five-minute observation rate, in contrast with the aforementioned four models, where the observation rate was hourly to bi-hourly. For the five models, the predicted measurements were those of the three upcoming observations (on average, three hours ahead). Based on the obtained results, we observed that by limiting the number of vital sign predictors (i.e., three vital signs), the prediction performance was still acceptable, with the average mean absolute percentage error (MAPE) being [Formula: see text] , and [Formula: see text] for heart rate, oxygen saturation, and respiration rate, respectively. Moreover, increasing the observation rate could enhance the prediction performance to be, on average, [Formula: see text] , and [Formula: see text] for heart rate, oxygen saturation, and respiration rate, respectively. It is envisioned that such models could be integrated with monitoring systems that could, using a limited number of vital signs, predict the health conditions of COVID-19 ICU patients in real-time. | input | 2 | 78,657 | 13 | 235,563 |
Please summerize the given abstract to a title | instruction | 0 | 78,792 | 13 | 235,966 |
Elevated interleukin levels are associated with higher severity and mortality in COVID 19 - A systematic review, meta-analysis, and meta-regression | output | 1 | 78,792 | 13 | 235,967 |
BACKGROUND AND AIMS: COVID 19 pneumonia commonly leads to ARDS. The occurrence of ARDS in COVID 19 patients is thought to occur secondary to an exaggerated immunologic response. In this meta-analysis, we aim to comprehensively study the various levels of immunological parameters in patients with COVID 19. MATERIALS AND METHODS: We performed a systematic literature search from PubMed, EuropePMC, SCOPUS, Cochrane Central Database, and medRxiv with the search terms, "COVID-19" and "Interleukin". The outcome of interest was prognosis in COVID 19 patients. RESULTS: We performed meta analysis of 16 studies. Higher counts of CD4 and CD8 with Lower Levels of TNF-a, IL2R, IL6, IL8 were observed on patients with good prognosis compared to patients with poor prognosis; -0.57 (pg/mL) (-1.10, -0.04, p = 0.04), (I2 91%, p < 0.001); -579.84 (U/mL) (-930.11, -229.57, p < 0.001), (I2 96%, p < 0.001); -1.49 (pg/mL) (-1.97, -1.01, p < 0.001), (I2 94%, p < 0.001); -0.80 (pg/mL) (-1.21, -0.40, p < 0.001), (I2 79%, p < 0.001); -2.51 (pg/mL) (-3.64, -1.38, p < 0.00001), (I2 98%, p < 0.001) respectively. Meta-regression showed age and hypertension (coefficient: 1.99, and -1.57, p = 0.005, and 0.006) significantly influenced association between IL-6 and poor outcome. CONCLUSION: Elevated immune response to coronavirus occurs in COVID 19 patients. Higher counts of CD4 and CD8 were seen in patients with good prognosis compared to patients with poor prognosis, with Lower levels of TNF-a, IL2R, IL6, IL8, were observed in patients with good prognosis compared to patients with poor prognosis. | input | 2 | 78,792 | 13 | 235,968 |
Please summerize the given abstract to a title | instruction | 0 | 78,796 | 13 | 235,978 |
Hyponatremia is associated with poor outcome in COVID-19 | output | 1 | 78,796 | 13 | 235,979 |
AIM: Our objective was to describe the impact of hyponatremia on the outcomes of COVID-19 patients [outcomes selected: intensive care unit (ICU) admission, mechanical ventilation or death]. METHODS: Two groups of COVID-19 patients were retrospectively screened on the basis of plasma sodium level at admission: hyponatremic (sodium < 135 mM, n = 92) or normonatremic (sodium ≥ 135 mM, n = 198) patients. Pearson's chi-2 (qualitative variables) and Student's T tests (quantitative variables) were used to compare the two groups. A multiple logistic regression model was used to explore the association between patients' clinical data and outcomes. RESULTS: Hyponatremia was frequent but generally mild. There were more male patients in the hyponatremic group (p = 0.014). Pulmonary lesions on the first thoracic CT-scan performed during hospitalization were significantly more extensive in the hyponatremic group (p = 0.010). ICU admission, mechanical ventilation or death were significantly more frequent in hyponatremic compared to normonatremic patients (37 versus 14%; p < 0.001; 17 versus 6%; p = 0.003; 18 versus 9%, p = 0.042, respectively). Hyponatremia was an independent predictor of adverse outcomes (adjusted Odds-ratio: 2.77 [1.26-6.15, p = 0.011]). CONCLUSIONS: Our study showed an independent relationship between hyponatremia at admission and transfer to ICU, use of mechanical ventilation or death in COVID-19 patients. Hyponatremia may reflect the severity of underlying pulmonary lesions. Our results support the use of sodium levels as a simple bedside screening tool for the early identification of SARS-CoV-2 infected patients at high risk of poor outcome. | input | 2 | 78,796 | 13 | 235,980 |
Please summerize the given abstract to a title | instruction | 0 | 78,800 | 13 | 235,990 |
Health system saturation in managing COVID-19 patients in Monastir, Tunisia | output | 1 | 78,800 | 13 | 235,991 |
BACKGROUND: COVID-19 emerged in late 2019 and quickly became a serious public health problem worldwide. This study aimed to determine the average length of stay, occupancy bed rate and bed turnover rate for COVID-19 patients in Monastir university hospital between the 1st October 2020 and 28th february 2021. METHODS: This is a cross-sectional study that enrolled all hospitalizations for COVID19 in Monastir University hospital, the unique third level healthcare in this region, between the 1st October 2020 and 28th february 2021. The following indicators: the average length of stay, the occupancy bed rate and the bed turnover rate were calculated during the study period. RESULTS: We included 762 hospitalizations for COVID-19 during the study period. The average age of our population was 64,22 years (standard deviation= 14,17). Male predominance was noted with sex ratio=1,63. The median length of stay was significantly longer in the intensive care unit (ICU) than in the other departments (11 (7;16) days, versus 7(2;14) days), p = 0.008. The average number of beds available for COVID-19 patients during the study period was 13 in the ICU and 65 in the other wards. The bed turnover rate and the bed occupancy rate per month were respectively 2,66 patient/bed/month and 96,26% in the ICU versus 1,74 patient/bed/month and 62,26% in the other wards. The occupancy bed rate in the ICU exceeded the 100% during the outbreak of January and February 2021 (129,72% and 120,66% respectively). CONCLUSIONS: Despite the efforts by the health services and social isolation measures in Tunisia, this study highlighted the saturation of our health system with an overload in intensive care units. KEY MESSAGES: Length of stay for patients with Covid-19 was significantly the longest in ICU. The occupancy bed rate, exceeding 100% in ICU, highlighted the health system collapse in managing COVID-19 patients. | input | 2 | 78,800 | 13 | 235,992 |
Please summerize the given abstract to a title | instruction | 0 | 78,866 | 13 | 236,188 |
Demographic and Clinical Characteristics Associated With Severity, Clinical Outcomes, and Mortality of COVID-19 Infection in Gabon | output | 1 | 78,866 | 13 | 236,189 |
IMPORTANCE: Since the emergence of COVID-19 in central China, sub-Saharan African countries, with the exception of South Africa, have been relatively spared during the COVID-19 pandemic. Consequently, few descriptive studies from this region are available. OBJECTIVE: To describe the clinical characteristics and outcomes of patients with COVID-19 infection in Gabon, from March to June 2020. DESIGN, SETTING, AND PARTICIPANTS: A single-center, cross-sectional study of 837 patients with COVID-19 was conducted from March to June 2020 in the Armed Forces Hospital in Libreville, Gabon. MAIN OUTCOMES AND MEASURES: Demographic and clinical characteristics and imaging findings of hospitalized patients with COVID-19. RESULTS: Of the 837 patients enrolled, 572 (68.3%) were men, and 264 (31.5%) were women (male to female ratio, 2:1); the median (interquartile range [IQR]) age was 35 (30-45) years (mean [SD] age, 38.0 [12.2] years. The mortality rate associated with COVID-19 was low (1.4%). Of these 837 patients, 524 (62.6%) were categorized as having no symptoms, 282 (33.7%) as having mild symptoms, and 31 (3.7%) as having severe symptoms. Patients with severe symptoms were older (mean [SD] age, 46.1 [14.7] years) than patients with mild symptoms (mean [SD] age, 41.3 [12.5] years) and those with no symptoms (mean [SD] age, 35.7 [11.3] years) (Kruskal-Wallis χ(2)(2) = 53.5; P < .001). History of diabetes was the principal risk factor associated with both severe symptoms in 5 of 31 patients (16.1%) and mild symptoms in 11 of 282 (3.9%) compared with no symptoms in 5 of 524 (0.9%) (Pearson χ(2)(2) = 30.9; P < .001). Patients with severe symptoms and a fatal outcome were older (mean [SD] age, 53.4 [15.1] years) than survivors (mean [SD] age, 41.5 [12.9] years) (t(20.83) = 2.2; P = .03). CONCLUSIONS AND RELEVANCE: In this single-center, cross-sectional study in Libreville, Gabon, the mortality rate associated with COVID-19 infection from March to June 2020 was low, and patients who died of COVID-19 infection were younger on average than reported elsewhere, possibly reflecting a smaller elderly population in Gabon. | input | 2 | 78,866 | 13 | 236,190 |
Please summerize the given abstract to a title | instruction | 0 | 78,984 | 13 | 236,542 |
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