scholarly journals First Use of Multiple Imputation with the National Tuberculosis Surveillance System

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Christopher Vinnard ◽  
E. Paul Wileyto ◽  
Gregory P. Bisson ◽  
Carla A. Winston
Keyword(s):  
Multiple Imputation ◽  
Odds Ratio ◽  
Surveillance System ◽  
High Rate ◽  
Isoniazid Resistance ◽  
Imputation Methods ◽  
Covariate Data ◽  
Missing Covariate Data ◽  
National Tuberculosis ◽  
Control And Prevention

Aims. The purpose of this study was to compare methods for handling missing data in analysis of the National Tuberculosis Surveillance System of the Centers for Disease Control and Prevention. Because of the high rate of missing human immunodeficiency virus (HIV) infection status in this dataset, we used multiple imputation methods to minimize the bias that may result from less sophisticated methods. Methods. We compared analysis based on multiple imputation methods with analysis based on deleting subjects with missing covariate data from regression analysis (case exclusion), and determined whether the use of increasing numbers of imputed datasets would lead to changes in the estimated association between isoniazid resistance and death. Results. Following multiple imputation, the odds ratio for initial isoniazid resistance and death was 2.07 (95% CI 1.30, 3.29); with case exclusion, this odds ratio decreased to 1.53 (95% CI 0.83, 2.83). The use of more than 5 imputed datasets did not substantively change the results. Conclusions. Our experience with the National Tuberculosis Surveillance System dataset supports the use of multiple imputation methods in epidemiologic analysis, but also demonstrates that close attention should be paid to the potential impact of missing covariates at each step of the analysis.

scholarly journals Propensity Score Estimation Using Classification and Regression Trees in the Presence of Missing Covariate Data

2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Bas B.L. Penning de Vries ◽  
Maarten van Smeden ◽  
Rolf H.H. Groenwold
Keyword(s):  
Logistic Regression ◽  
Missing Data ◽  
Propensity Score ◽  
Multiple Imputation ◽  
Incomplete Data ◽  
Regression Trees ◽  
Covariate Data ◽  
Missing Covariate Data ◽  
Classification And Regression ◽  
Cart Algorithm

AbstractData mining and machine learning techniques such as classification and regression trees (CART) represent a promising alternative to conventional logistic regression for propensity score estimation. Whereas incomplete data preclude the fitting of a logistic regression on all subjects, CART is appealing in part because some implementations allow for incomplete records to be incorporated in the tree fitting and provide propensity score estimates for all subjects. Based on theoretical considerations, we argue that the automatic handling of missing data by CART may however not be appropriate. Using a series of simulation experiments, we examined the performance of different approaches to handling missing covariate data; (i) applying the CART algorithm directly to the (partially) incomplete data, (ii) complete case analysis, and (iii) multiple imputation. Performance was assessed in terms of bias in estimating exposure-outcome effects among the exposed, standard error, mean squared error and coverage. Applying the CART algorithm directly to incomplete data resulted in bias, even in scenarios where data were missing completely at random. Overall, multiple imputation followed by CART resulted in the best performance. Our study showed that automatic handling of missing data in CART can cause serious bias and does not outperform multiple imputation as a means to account for missing data.

scholarly journals A stochastic multiple imputation algorithm for missing covariate data in tree-structured survival analysis

2010 ◽  
Vol 29 (29) ◽  
pp. 3004-3016 ◽  
Author(s):  
Meredith L. Wallace ◽  
Stewart J. Anderson ◽  
Sati Mazumdar
Keyword(s):  
Survival Analysis ◽  
Multiple Imputation ◽  
Covariate Data ◽  
Missing Covariate Data

Evaluation of the National Tuberculosis Surveillance System in Sana’a City, Yemen (Preprint)

2021 ◽  
Author(s):  
Fadwa Salem ◽  
Essam Mahyoub ◽  
Abdulbary Al-Hammadi ◽  
Labiba Saeed Anam ◽  
Yousef Khader
Keyword(s):  
Surveillance System ◽  
Financial Support ◽  
Qualitative Evaluation ◽  
Electronic System ◽  
Key Stakeholders ◽  
System P ◽  
Catchment Areas ◽  
National Tuberculosis ◽  
Control And Prevention ◽  
Key Aspects

BACKGROUND Tuberculosis (TB) surveillance system in Yemen has not been evaluated before and it is not clear if the system is able to monitor the TB problem in Yemen efficiently and effectively OBJECTIVE This study aimed to assess the usefulness of the national tuberculosis surveillance system, assess the performance of tuberculosis programs regarding the eight attributes and identify strengths and weakness of the system. METHODS A quantitative and qualitative evaluation of the National Tuberculosis surveillance system was conducted using the Centers for Disease Control and Prevention (CDC) updated guidelines. The study was carried out in ten districts in Sana’a City. Twenty-eight public health facilities providing TB services for whole population in their assigned catchment areas in Sana’a city were purposively selected. All key stakeholders were interviewed based on their involvement with key aspects of TB surveillance activities. RESULTS A total of 54 persons participated in the evaluation. The overall score percent for usefulness was 71%, indicating an average rank. The TB Surveillance System had an average flexibility (score percent = 78%), poor stability (score percent = 15%), poor simplicity (score percent = 59%), and poor acceptability (score percent = 12%). The timeliness was ranked as average. The sensitivity of the TB surveillance system was 96% and the PPV of the TB surveillance system was 73%. CONCLUSIONS The usefulness, flexibility, PVP, timeliness, and data quality of the TB surveillance system were rated as an average. The system’s stability, acceptability and simplicity were rated as poor. The main weaknesses in the TB surveillance system include lack of governmental financial support, paper-based system, and lack of regular staff training. Developing an electronic system, involvement of private sector in reporting system, securing governmental financial support, and training the staff on TB surveillance are strongly recommended to improve the performance of the system.

scholarly journals Performance After Anterior Cruciate Ligament Reconstruction in National Basketball Association Players

2021 ◽  
Vol 9 (2) ◽  
pp. 232596712098164
Author(s):  
Steven F. DeFroda ◽  
Devan D. Patel ◽  
John Milner ◽  
Daniel S. Yang ◽  
Brett D. Owens
Keyword(s):  
Anterior Cruciate Ligament ◽  
Acl Reconstruction ◽  
Odds Ratio ◽  
Cruciate Ligament ◽  
Case Series ◽  
National Basketball Association ◽  
High Rate ◽  
Return To Play ◽  
Lower Percentage ◽  
Anterior Cruciate

Background: Anterior cruciate ligament (ACL) injury in National Basketball Association (NBA) players can have a significant impact on player longevity and performance. Current literature reports a high rate of return to play, but there are limited data on performance after ACL reconstruction (ACLR). Purpose/Hypothesis: To determine return to play and player performance in the first and second seasons after ACLR in NBA players. We hypothesized that players would return at a high rate. However, we also hypothesized that performance in the first season after ACLR would be worse as compared with the preinjury performance, with a return to baseline by postoperative year 2. Study Design: Case series; Level of evidence, 4. Methods: An online database of NBA athlete injuries between 2010 and 2019 was queried using the term ACL reconstruction. For the included players, the following data were recorded: name; age at injury; position; height, weight, and body mass index; handedness; NBA experience; dates of injury, surgery, and return; knee affected; and postoperative seasons played. Regular season statistics for 1 preinjury season and 2 postoperative seasons were compiled and included games started and played, minutes played, and player efficiency rating. Kaplan-Meier survivorship plots were computed for athlete return-to-play and retirement endpoints. Results: A total of 26 athletes underwent ACLR; of these, 84% (95% CI, 63.9%-95.5%) returned to play at a mean 372.5 days (95% CI, 323.5-421.5 days) after surgery. Career length after injury was a mean of 3.36 seasons (95% CI, 2.27-4.45 seasons). Factors that contributed to an increased probability of return to play included younger age at injury (odds ratio, 0.71 [95% CI, 0.47-0.92]; P = .0337) and fewer years of experience in the NBA before injury (odds ratio, 0.70 [95% CI, 0.45-0.93]; P = .0335). Postoperatively, athletes played a significantly lower percentage of total games in the first season (48.4%; P = .0004) and second season (62.1%; P = .0067) as compared with the preinjury season (78.5%). Player efficiency rating in the first season was 19.3% less than that in the preinjury season ( P = .0056). Performance in the second postoperative season was not significantly different versus preinjury. Conclusion: NBA players have a high rate of RTP after ACLR. However, it may take longer than a single season for elite NBA athletes to return to their full preinjury performance. Younger players and those with less NBA experience returned at higher rates.

scholarly journals Exploring the mechanisms of collaboration between the Tuberculosis and Diabetes Programs for the control of TB-DM Comorbidity in Ghana

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Rita Suhuyini Salifu ◽  
Khumbulani W. Hlongwana
Keyword(s):  
Communicable Disease ◽  
Control Program ◽  
Communicable Diseases ◽  
Local Health ◽  
National Tuberculosis Control Program ◽  
National Tuberculosis ◽  
Local Health Facility ◽  
Control And Prevention ◽  
And Control ◽  
Non Communicable Disease

Abstract Objectives To explore the mechanisms of collaboration between the stakeholders, including National Tuberculosis Control Program (NTP) and the Non-Communicable Disease Control and Prevention Program (NCDCP) at the national, regional, and local (health facility) levels of the health care system in Ghana. This is one of the objectives in a study on the “Barriers and Facilitators to the Implementation of the Collaborative Framework for the Care and Control of Tuberculosis and Diabetes in Ghana” Results The data analysis revealed 4 key themes. These were (1) Increased support for communicable diseases (CDs) compared to stagnant support for non-communicable diseases (NCDs), (2) Donor support, (3) Poor collaboration between NTP and NCDCP, and (4) Low Tuberculosis-Diabetes Mellitus (TB-DM) case detection.

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