scholarly journals Survival Time Data Analysis and Proportional Hazard Model

2015 ◽  
Vol 11 (1) ◽  
pp. 29-36
Author(s):  
Hideo Nakazawa
Keyword(s):  
Data Analysis ◽  
Survival Time ◽  
Hazard Model ◽  
Proportional Hazard ◽  
Proportional Hazard Model ◽  
Time Data ◽  
Survival Time Data

scholarly journals A Study of Factors Affecting the Length of Hospital Stay of COVID-19 Patients by Cox-Proportional Hazard Model in a South Indian Tertiary Care Hospital

2021 ◽  
Vol 12 ◽  
pp. 215013272110002
Author(s):  
Gayathri Thiruvengadam ◽  
Marappa Lakshmi ◽  
Ravanan Ramanujam
Keyword(s):  
Hospital Stay ◽  
Tertiary Care ◽  
Length Of Hospital Stay ◽  
Hazard Model ◽  
Cox Proportional Hazard Model ◽  
Care Hospital ◽  
Proportional Hazard ◽  
Proportional Hazard Model ◽  
Cox Proportional Hazard ◽  
South Indian

Background: The objective of the study was to identify the factors that alter the length of hospital stay of COVID-19 patients so we have an estimate of the duration of hospitalization of patients. To achieve this, we used a time to event analysis to arrive at factors that could alter the length of hospital stay, aiding in planning additional beds for any future rise in cases. Methods: Information about COVID-19 patients was collected between June and August 2020. The response variable was the time from admission to discharge of patients. Cox proportional hazard model was used to identify the factors that were associated with the length of hospital stay. Results: A total of 730 COVID-19 patients were included, of which 675 (92.5%) recovered and 55 (7.5%) were considered to be right-censored, that is, the patient died or was discharged against medical advice. The median length of hospital stay of COVID-19 patients who were hospitalized was found to be 7 days by the Kaplan Meier curve. The covariates that prolonged the length of hospital stay were found to be abnormalities in oxygen saturation (HR = 0.446, P < .001), neutrophil-lymphocyte ratio (HR = 0.742, P = .003), levels of D-dimer (HR = 0.60, P = .002), lactate dehydrogenase (HR = 0.717, P = .002), and ferritin (HR = 0.763, P = .037). Also, patients who had more than 2 chronic diseases had a significantly longer length of stay (HR = 0.586, P = .008) compared to those with no comorbidities. Conclusion: Factors that are associated with prolonged length of hospital stay of patients need to be considered in planning bed strength on a contingency basis.

Development and validation of a prognostic model for survival time data: application to prognosis of HIV positive patients treated with antiretroviral therapy

2004 ◽  
Vol 23 (15) ◽  
pp. 2375-2398 ◽  
Author(s):  
Margaret May ◽  
Patrick Royston ◽  
Matthias Egger ◽  
Amy C. Justice ◽  
Jonathan AC Sterne ◽  
...  
Keyword(s):  
Antiretroviral Therapy ◽  
Survival Time ◽  
Prognostic Model ◽  
Hiv Positive ◽  
Time Data ◽  
Data Application ◽  
Development And Validation ◽  
Survival Time Data

Interactions of increased pO2 and pCO2 effects in producing convulsions and death in mice

1961 ◽  
Vol 16 (1) ◽  
pp. 1-7 ◽  
Author(s):  
John R. Marshall ◽  
Christian J. Lambertsen
Keyword(s):  
Carbon Dioxide ◽  
High Pressure ◽  
Blood Flow ◽  
Latent Period ◽  
Survival Time ◽  
Brain Blood Flow ◽  
Time Data ◽  
Cortical Depression ◽  
Survival Time Data ◽  
Very High

In 379 mice subjected to from 1 to 11 atm. of pO2 and 0 to 304 mm Hg of pCO2 for 90 minutes, oxygen was convulsigenic at pressures greater than 3 atm. and lethal at greater than 4 atm. Carbon dioxide in 1 atm. of O2 was not convulsigenic but was lethal at very high tensions. In the presence of O2 at high pressure (OHP) small elevations of CO2 tension shortened the preconvulsive latent period, whereas CO2 tensions greater than 120 mm Hg inhibited convulsions. Survival time in OHP was shortened by the addition of CO2. An interaction between OHP and CO2 effects is suggested by both the preconvulsive latent period and survival time data. The effects of CO2 on OHP and electroshock convulsions are compared and possible reasons for differences are discussed in light of the previously demonstrated general cortical depression and inhibition of convulsions by CO2. The potentiation of OHP convulsions by low CO2 tensions is probably due to effects on brain blood flow. Although death can occur without convulsions there is a tendency for animals susceptible to convulsions to be also susceptible to the lethal properties of OHP with CO2. Submitted on July 28, 1960

Correlated gamma frailty models for bivariate survival time data

2018 ◽  
Vol 28 (10-11) ◽  
pp. 3437-3450
Author(s):  
Adelino Martins ◽  
Marc Aerts ◽  
Niel Hens ◽  
Andreas Wienke ◽  
Steven Abrams
Keyword(s):  
Survival Time ◽  
Frailty Models ◽  
Current Status Data ◽  
Current Status ◽  
Mortality Data ◽  
Time Data ◽  
Additive Decomposition ◽  
Bivariate Survival ◽  
Gamma Frailty ◽  
Survival Time Data

Frailty models have been developed to quantify both heterogeneity as well as association in multivariate time-to-event data. In recent years, numerous shared and correlated frailty models have been proposed in the survival literature allowing for different association structures and frailty distributions. A bivariate correlated gamma frailty model with an additive decomposition of the frailty variables into a sum of independent gamma components was introduced before. Although this model has a very convenient closed-form representation for the bivariate survival function, the correlation among event- or subject-specific frailties is bounded above which becomes a severe limitation when the values of the two frailty variances differ substantially. In this article, we review existing correlated gamma frailty models and propose novel ones based on bivariate gamma frailty distributions. Such models are found to be useful for the analysis of bivariate survival time data regardless of the censoring type involved. The frailty methodology was applied to right-censored and left-truncated Danish twins mortality data and serological survey current status data on varicella zoster virus and parvovirus B19 infections in Belgium. From our analyses, it has been shown that fitting more flexible correlated gamma frailty models in terms of the imposed association and correlation structure outperforms existing frailty models including the one with an additive decomposition.

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