scholarly journals Effect of Ribavirin on Recovery Time in COVID-19 Patients: A Real-world Retrospective Cohort Study

2020 ◽  
Author(s):  
Yuanlong Hu ◽  
Xue Zhu ◽  
Ning Shen ◽  
Xinhua Jia ◽  
Xingcai Zhang ◽  
...  
Keyword(s):  
Cohort Study ◽  
Linear Regression ◽  
Regression Model ◽  
Real World ◽  
Linear Regression Model ◽  
Retrospective Cohort Study ◽  
Recovery Time ◽  
Retrospective Cohort ◽  
Specific Drug ◽  
Clinical Benefits

Abstract Background: Up to now, there is still no specific drug against COVID-19. However, Ribavirin may bring clinical benefits to COVID-19 patients.Methods: This study was designed as a real-world retrospective cohort study based on electronic medical record (EMR), and linear regression model was used to evaluate the effect of Ribavirin on recovery time.Results: 342 patients were enrolled in this study. Both unadjusted and unadjusted models showed that interferon or Lopinavir-Ritonavir combined with Ribavirin could shorten the recovery time of patients, which was evident in all subgroups considered except the severe subgroup and after fine adjustments.Conclusion: This study shows that interferon or Lopinavir-Ritonavir combined with Ribavirin can shorten the recovery time of patients with non-severe COVID-19.

scholarly journals Time to recovery from COVID-19 and its predictors among patients admitted to treatment center of Wollega University Referral Hospital (WURH), Western Ethiopia: Survival analysis of retrospective cohort study

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252389
Author(s):  
Tadesse Tolossa ◽  
Bizuneh Wakuma ◽  
Dejene Seyoum Gebre ◽  
Emiru Merdassa Atomssa ◽  
Motuma Getachew ◽  
...  
Keyword(s):  
Cohort Study ◽  
Regression Model ◽  
Median Time ◽  
Retrospective Cohort Study ◽  
Recovery Time ◽  
Retrospective Cohort ◽  
Cox Regression ◽  
Older Age ◽  
Treatment Center ◽  
P Value

Introduction Despite its alarming spread throughout the world, no effective drug and vaccine is discovered for COVID-19 so far. According to WHO, the recovery time from COVID-19 was estimated to be 2 weeks for patients with mild infection, and 3 to 6 weeks for those with serious illnesses. A studies regarding the median recovery time and its predictors are limited globally and specifically in Ethiopia. Therefore, the aim of this study was to estimate the median time to recovery from COVID-19 and its predictors among COVID-19 cases admitted to WURH, Western Ethiopian. Methods This was a hospital-based retrospective cohort study conducted among 263 adult patients admitted with COVID-19 in WURH treatment center from March 29, 2020 through September 30, 2020. Epidata version 3.2 was used for data entry, and STATA version 14 for analysis. A Cox proportional hazard regression model was fitted to determine factors associated with recovery time. A variable with P-value ≤ 0.25 at bivariable Cox regression analysis were selected for multivariable Cox proportional model. Multivariable Cox regression model with 95% CI and Adjusted Hazard Ratio (AHR) was used to identify a significant predictor of time to recovery from COVID-19 at P-value < 0.05. Results The mean age of patient was 36.8 (SD± 10.68) years. At the end of follow up, two hundred twenty seven observations were developed an event (recovered) with median time to recovery of 18 days with IQR of 10–27 days. The overall incidence rate of recovery was of 4.38 per 100 (95% CI: 3.84, 4.99) person-days observations. Being older age (AHR = 1.59, 95% CI: 1.02, 2.49), presence of fever on admission (AHR = 1.78, 95% CI: 1.21, 2.62), and comorbidity (AHR = 0.56, 95% CI, 0.34, 0.90) were found to have statistically significant association with recovery time. Conclusion and recommendations In general, the median recovery time of patients with COVID-19 cases was long, and factors such as older age group, presence of fever, and comorbidity was an independent predictors of delayed recovery from COVID-19. Intervention to further reduce recovery time at treatment center has to focus on patients those shows symptoms and with comorbidities.

scholarly journals LDL-cholesterol change and goal attainment following statin intensity titration among Asians in primary care: a retrospective cohort study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Hao Sen Andrew Fang ◽  
Qiao Gao ◽  
Mong Li Lee ◽  
Wynne Hsu ◽  
Ngiap Chuan Tan
Keyword(s):  
Primary Care ◽  
Clinical Trials ◽  
Cohort Study ◽  
Real World ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Goal Attainment ◽  
Real World Data ◽  
World Data ◽  
Asian Patients

Abstract Background Clinical trials have demonstrated that either initiating or up-titrating a statin dose substantially reduce Low-Density Lipoprotein-Cholesterol (LDL-C) levels. However, statin adherence in actual practice tends to be suboptimal, leading to diminished effectiveness. This study aims to use real-world data to determine the effect on LDL-C levels and LDL-C goal attainment rates, when selected statins are titrated in Asian patients. Methods A retrospective cohort study over a 5-year period, from April 2014 to March 2019 was conducted on a cohort of multi-ethnic adult Asian patients with clinical diagnosis of Dyslipidaemia in a primary care clinic in Singapore. The statins were classified into low-intensity (LI), moderate-intensity (MI) and high-intensity (HI) groups according to the 2018 American College of Cardiology and American Heart Association (ACC/AHA) Blood Cholesterol Guidelines. Patients were grouped into “No statin”, “Non-titrators” and “Titrators” cohorts based on prescribing patterns. For the “Titrators” cohort, the mean percentage change in LDL-C and absolute change in LDL-C goal attainment rates were computed for each permutation of statin intensity titration. Results Among the cohort of 11,499 patients, with a total of 266,762 visits, there were 1962 pairs of LDL-C values associated with a statin titration. Initiation of LI, MI and HI statin resulted in a lowering of LDL-C by 21.6% (95%CI = 18.9–24.3%), 28.9% (95%CI = 25.0–32.7%) and 25.2% (95%CI = 12.8–37.7%) respectively. These were comparatively lower than results from clinical trials (30 to 63%). The change of LDL-C levels due to up-titration, down-titration, and discontinuation were − 12.4% to − 28.9%, + 13.2% to + 24.6%, and + 18.1% to + 32.1% respectively. The improvement in LDL-C goal attainment ranged from 26.5% to 47.1% when statin intensity was up-titrated. Conclusion In this study based on real-world data of Asian patients in primary care, it was shown that although statin titration substantially affected LDL-C levels and LDL-C goal attainment rates, the magnitude was lower than results reported from clinical trials. These results should be taken into consideration and provide further insight to clinicians when making statin adjustment recommendations in order to achieve LDL-C targets in clinical practice, particularly for Asian populations.

scholarly journals Lasting s-ketamine block of spreading depolarizations in subarachnoid hemorrhage: a retrospective cohort study

Critical Care ◽  
2019 ◽  
Vol 23 (1) ◽  
Author(s):  
Edgar Santos ◽  
Arturo Olivares-Rivera ◽  
Sebastian Major ◽  
Renán Sánchez-Porras ◽  
Lorenz Uhlmann ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Subarachnoid Hemorrhage ◽  
Regression Model ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Logistic Regression Model ◽  
Poisson Model ◽  
High Dose ◽  
First Line

Abstract Objective Spreading depolarizations (SD) are characterized by breakdown of transmembrane ion gradients and excitotoxicity. Experimentally, N-methyl-d-aspartate receptor (NMDAR) antagonists block a majority of SDs. In many hospitals, the NMDAR antagonist s-ketamine and the GABAA agonist midazolam represent the current second-line combination treatment to sedate patients with devastating cerebral injuries. A pressing clinical question is whether this option should become first-line in sedation-requiring individuals in whom SDs are detected, yet the s-ketamine dose necessary to adequately inhibit SDs is unknown. Moreover, use-dependent tolerance could be a problem for SD inhibition in the clinic. Methods We performed a retrospective cohort study of 66 patients with aneurysmal subarachnoid hemorrhage (aSAH) from a prospectively collected database. Thirty-three of 66 patients received s-ketamine during electrocorticographic neuromonitoring of SDs in neurointensive care. The decision to give s-ketamine was dependent on the need for stronger sedation, so it was expected that patients receiving s-ketamine would have a worse clinical outcome. Results S-ketamine application started 4.2 ± 3.5 days after aSAH. The mean dose was 2.8 ± 1.4 mg/kg body weight (BW)/h and thus higher than the dose recommended for sedation. First, patients were divided according to whether they received s-ketamine at any time or not. No significant difference in SD counts was found between groups (negative binomial model using the SD count per patient as outcome variable, p = 0.288). This most likely resulted from the fact that 368 SDs had already occurred in the s-ketamine group before s-ketamine was given. However, in patients receiving s-ketamine, we found a significant decrease in SD incidence when s-ketamine was started (Poisson model with a random intercept for patient, coefficient − 1.83 (95% confidence intervals − 2.17; − 1.50), p < 0.001; logistic regression model, odds ratio (OR) 0.13 (0.08; 0.19), p < 0.001). Thereafter, data was further divided into low-dose (0.1–2.0 mg/kg BW/h) and high-dose (2.1–7.0 mg/kg/h) segments. High-dose s-ketamine resulted in further significant decrease in SD incidence (Poisson model, − 1.10 (− 1.71; − 0.49), p < 0.001; logistic regression model, OR 0.33 (0.17; 0.63), p < 0.001). There was little evidence of SD tolerance to long-term s-ketamine sedation through 5 days. Conclusions These results provide a foundation for a multicenter, neuromonitoring-guided, proof-of-concept trial of ketamine and midazolam as a first-line sedative regime.

scholarly journals Sampling the Porridge: A Comparison of Ordered Variable Regression with F and R2 and Multiple Linear Regression with Corrected F and R2 in the Presence of Multicollinearity

2020 ◽  
Vol 18 (1) ◽  
pp. 2-39
Author(s):  
Grayson L. Baird ◽  
Stephen L. Bieber
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Real World ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Real World Data ◽  
World Data

Differences between the multiple linear regression model with Corrected R2 and Corrected F and the ordered variable regression model with R2 and F when intercorrelation is present are illustrated with simulated and real-world data.

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