The Use of Multiple Imputation Techniques on Short-Term Clinical Complications of Patients Presenting with Traumatic Spinal Cord Injuries

Author:

Musukuma Mwiche,Sonkwe Brian,Fwemba Isaac,Musonda Patrick

Abstract

Background: With the increase in the use of secondary data in epidemiological studies, the inquiry of how to manage missing data has become more relevant. Our study applied imputation techniques on traumatic spinal cord injuries data; a medical problem where data is generally sporadic. Traumatic spinal cord injuries due to blunt force cause widespread physiological impairments, medical and non-medical problems. The effects of spinal cord injuries are a burden not only to the victims but to their families and to the entire health system of a country. This study also evaluated the causes of traumatic spinal cord injuries in patients admitted to the University Teaching Hospital and factors associated with clinical complications in these patients. Methods: The study used data from medical records of patients who were admitted to the University Teaching Hospital in Lusaka, Zambia. Patients presenting with traumatic spinal cord injuries between 1st January 2013 and 31st December 2017 were part of the study. The data was first analysed using complete case analysis, then multiple imputation techniques were applied, to account for the missing data. Thereafter, both descriptive and inferential analyses were performed on the imputed data. Results: During the study period of interest, a total of 176 patients were identified as having suffered from spinal cord injuries. Road traffic accidents accounted for 56% (101) of the injuries. Clinical complications suffered by these patients included paralysis, death, bowel and bladder dysfunction and pressure sores among other things. Eighty-eight (50%) patients had paralysis. Patients with cervical spine injuries compared to patients with thoracic spine injuries had 87% reduced odds of suffering from clinical complications (OR=0.13, 95% CI{0.08, 0.22}p<.0001). Being paraplegic at discharge increased the odds of developing a clinical complication by 8.1 times (OR=8.01, 95% CI{2.74, 23.99}, p<.001). Under-going an operation increased the odds of having a clinical complication (OR=3.71, 95% CI{=1.99, 6.88}, p<.0001). A patient who presented with Frankel Grade C or E had a 96% reduction in the odds of having a clinical complication (OR=.04, 95% CI{0.02, 0.09} and {0.02, 0.12} respectively, p<.0001) compared to a patient who presented with Frankel Grade A. Conclusion: A comparison of estimates obtained from complete case analysis and from multiple imputations revealed that when there are a lot of missing values, estimates obtained from complete case analysis are unreliable and lack power. Efforts should be made to use ideas to deal with missing values such as multiple imputation techniques. The most common cause of traumatic spinal cord injuries was road traffic accidents. Findings suggest that paralysis had the greatest negative effect on clinical complications. When the category of Frankel Grade increased from A-E, the less likely a patient was likely to succumb to clinical complications. No evidence of an association was found between age, sex and developing a clinical complication.

Funder

African Academy of Sciences

Publisher

Bentham Science Publishers Ltd.

Subject

Public Health, Environmental and Occupational Health,Community and Home Care,Health(social science)

Reference38 articles.

1. Marston L, Carpenter JR, Walters KR, Morris RW, Nazareth I, Petersen I. Issues in multiple imputation of missing data for large general practice clinical databases. Pharmacoepidemiol Drug Saf 2010; 19 (6) : 618-26.

2. Maguire A, Blak BT, Thompson M. The importance of defining periods of complete mortality reporting for research using automated data from primary care. Pharmacoepidemiol Drug Saf 2009; 18 (1) : 76-83.

3. Szatkowski L, Lewis S, McNeill A, Huang Y, Coleman T. Can data from primary care medical records be used to monitor national smoking prevalence? Journal of Epidemiology & Community Health 2011; 2011 : 120154.

4. Leacy FP, Floyd S, Yates TA, White IR. Analyses of sensitivity to the missing-at-random assumption using multiple imputation with delta adjustment: Application to a tuberculosis/HIV prevalence survey with incomplete HIV-status data. Am J Epidemiol 2017; 185 (4) : 304-15.

5. Kang H. The prevention and handling of the missing data. Korean J Anesthesiol 2013; 64 (5) : 402-6.

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