scholarly journals Delay of Detection Of COVID-19 Patients In Bangladesh; An Application To Cox Proportional Hazard Model

Author(s):  
Sujan Rudra ◽  
Shuva Das ◽  
Md. Ehsanul Hoque ◽  
Abul Kalam ◽  
Mohammad Arifur Rahman

Abstract Objective: To delineate the survival rate of the patients with coronavirus disease 2019 (COVID-19) who did the diagnostic tests lately after the development of symptoms. The aim is to determine the socio-demographic risk factors associated with the delay of the detection of COVID-19 patients. Methods: For this cross-sectional study, 300 patients were selected who were diagnosed as COVID-19 patients in the Molecular Biology Laboratory of Chittagong Medical College, Chattogram, Bangladesh. Data were collected from May to July 2020. Clinical characteristics were obtained from over phone interviews and laboratory diagnosis by Real-time Reverse Transcriptase Polymerase Chain Reaction (rRT-PCR). Cox proportional hazard model is applied to estimate risk factors affecting the delay of detection of COVID-19 patients.Result: Female mortality rate was 44.9% higher compared to males, graduates died 32% more than undergraduates, unmarried peoples’ death rate were 56% more than married and those who were in traveling irregularly and in contact with symptomatic patients, were 86% more died than non-travelers.Conclusion: Early diagnosis of COVID-19 can save a huge amount of lives and special attention should be emphasized on the significant explanatory variable.

2020 ◽  
Author(s):  
Sujan Rudra ◽  
Shuva Das ◽  
Md. Ehsanul Hoque ◽  
Abul Kalam ◽  
Mohammad Arifur Rahman

Abstract Objective: To delineate the survival rate of the patients with coronavirus disease 2019 (COVID-19) who did the diagnostic tests lately after the development of symptoms. The aim is to determine the socio-demographic risk factors associated with the delay of the detection of COVID-19 patients. Methods: For this cross-sectional study, 300 patients were selected who were diagnosed as COVID-19 patients in the Molecular Biology Laboratory of Chittagong Medical College, Chattogram, Bangladesh. Data were collected from May to July 2020. Clinical characteristics were obtained from over phone interviews and laboratory diagnosis by Real-time Reverse Transcriptase Polymerase Chain Reaction (rRT-PCR). Cox proportional hazard model is applied to estimate risk factors affecting the delay of detection of COVID-19 patients.Result: Female mortality rate was 44.9% higher compared to males, graduates died 32% more than undergraduates, unmarried peoples’ death rate were 56% more than married and those who were in traveling irregularly and in contact with symptomatic patients, were 86% more died than non-travelers.Conclusion: Early diagnosis of COVID-19 can save a huge amount of lives and special attention should be emphasized on the significant explanatory variable.


Author(s):  
Asifa Kamal ◽  
Abeera Shakeel ◽  
Admin

Abstract Objective: To investigate differentials and determinants of neonatal mortality in Pakistan. Methods: Study design was cross sectional. Data from Pakistan Demographic and Health Survey (PDHS 2017-18) was used. Data collection period for PDHS 2017-18 was from 22 November 2017 to 30 April 2018. Neonatal mortality rates (NMRs) were computed to observe the differentials in NMR for various categories of socio-demographic factors. Cox proportional hazard model was fitted to identify significant factors affecting neonatal mortality. Results: Hazard of neonatal mortality had significantly decreased as household size increased (HR 0.41 and HR 0.36). Household with improved toilet facility had significantly lower chances (HR 0.57) of neonatal death as compared to that with unimproved toilet facility. Significantly elevated risk (HR 5.56) of neonate death was observed in case of multiple births. Children had better chances (HR 0.32; HR 0.34) of surviving in neonatal period as duration of birth spacing increased (24-35 months; 36 or more months). Conclusion: Household size, improved toilet facilities, multiple births and preceding birth intervals were found to have significant effect on neonatal mortality. Significant protective factors of neonate deaths were large household size, improved toilet facilities, singleton births and long birth interval. Keywords: PDHS 2017-18, Neonatal Mortality Rate, Cox Proportional Hazard Model


2021 ◽  
Vol 11 ◽  
Author(s):  
Haisheng Qian ◽  
Xiaofeng Ji ◽  
Chang Liu ◽  
Yini Dang ◽  
Xuan Li ◽  
...  

Objective: Esophageal adenosquamous carcinoma (ASC) is a rare pathological type of cancer. Its clinical features and prognosis is poorly understood. The purpose of this study was to identify the characteristics of ASC patients and analyze the risk factors of esophageal carcinoma.Methods: Patients with esophageal cancer in the SEER database diagnosed from 1975–2016 were obtained. The epidemiology, clinical characteristics, and outcomes between these three groups were compared. The nomogram and online dynamic nomogram were constructed according to the Cox proportional hazard model.Results: The age-adjusted incidences of AC (1975–1999), AC (1999–2016), and ASC (1975–1989) increased over time (p < 0.05). Age-adjusted incidences of SqCC (1986–2012) and ASC (1989–2016) decreased (p < 0.05). Survival of patients with ASC was significantly worse when compared to AC and SqCC (ASC vs. AC, p < 0.001, ASC vs. SqCC, p = 0.01). ASC, older age, black race, male, overlapping site, higher tumor grade, lymph node metastasis, and a higher summary stage or AJCC stage were considered to be risk factors for a poor survival in the multivariate Cox analysis. The ROC curves and AUC indicated that the model has a good discrimination ability (AUC were 0.774 for a 3-year OS and 0.782 for a 5-year OS). An online dynamic nomogram was built based on the Cox proportional hazard model for convenient clinical use.Conclusions: ASC is somewhat closer to AC rather than SqCC in terms of the demographics and tumor site, but has a worse OS than both AC and SqCC.


2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
Y Nishimoto ◽  
Y Yamashita ◽  
T Morimoto ◽  
S Saga ◽  
Y Sato ◽  
...  

Abstract Background/Introduction Cancer is a strong risk factor for the development of venous thromboembolism (VTE) including pulmonary embolism (PE) and deep vein thrombosis (DVT). Patients with VTE have a long-term risk of recurrence, which can be prevented by anticoagulation therapy. Prolonged anticoagulation therapy is recommended for patients with cancer-associated VTE, although the risk of recurrence might depend on the individual patient. Purpose We aimed to identify the risk factors of recurrence in patients with cancer-associated VTE. Methods The COMMAND VTE Registry is a multicenter retrospective registry enrolling 3027 consecutive patients with acute symptomatic VTE among 29 Japanese centers between January 2010 and August 2014. The present study population consisted of 695 cancer-associated VTE patients. The primary outcome measure in the present study was recurrent VTE, which was defined as PE and/or DVT with symptoms accompanied by confirmation of a new thrombus or exacerbation of the thrombus by objective imaging examinations or autopsy. Discontinuation of anticoagulation was defined as a withdrawal of anticoagulation therapy lasting >14 days for any reason. We selected clinically relevant variables and variables with P values <0.1 in a univariate analysis as potential risk factors, and constructed a multivariable Cox proportional hazard model for recurrent VTE incorporating the anticoagulation therapy status as a time-updated covariate. Results Among the 695 study patients, recurrent VTE occurred in 78 patients, of whom 54 (69%) occurred within 6 months. The cumulative incidence of recurrent VTE was 7.7% at 3-months, 8.9% at 6-months, 11.8% at 1-year, and 17.7% at 5-years. The cumulative incidence of discontinuation of anticoagulation therapy was 18.0% at 3-months, 29.5% at 6-months, 43.4% at 1-year, and 66.5% at 5-years. The cumulative 5-year incidence of recurrent VTE was most frequent in patients with uterus/ovary cancer (26.0%), followed by those with lung cancer (24.7%). The multivariable Cox proportional hazard model revealed that chronic kidney disease (HR, 2.27; 95% CI, 1.36–3.77, P=0.002), a high D-dimer level at the time of VTE diagnosis (HR, 2.85; 95% CI, 1.71–4.74, P<0.001), advanced cancer (HR, 1.69; 95% CI, 1.05–2.72, P=0.03) and discontinuation of anticoagulation therapy (HR, 2.66; 95% CI, 1.53–4.63, P<0.001) were independently associated with an increased risk of recurrent VTE. No cancer site was independently associated with an increased risk for recurrent VTE when adjusting for the above mentioned risk factors in the multivariable Cox proportional hazard model, although the risk of recurrent VTE numerically differed according to the cancer site. Conclusions Among patients with cancer-associated VTE, chronic kidney disease, a high D-dimer level at the time of VTE diagnosis, advanced cancer, and discontinuation of anticoagulation therapy were independent risk factors of recurrence. FUNDunding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Research Institute for Production Development, Mitsubishi Tanabe Pharma Corporation Figure 1 Figure 2


2021 ◽  
Vol 12 ◽  
pp. 215013272110002
Author(s):  
Gayathri Thiruvengadam ◽  
Marappa Lakshmi ◽  
Ravanan Ramanujam

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.


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