Missing Data, Data Cleansing, and Treatment From a Primary Study

Koszalinski, Rebecca S.; Tansakul, Varisara; Khojandi, Anahita; Li, Xueping

doi:10.1097/cin.0000000000000473

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…We cleaned the dataset before we conducted any analyses, by identifying and repairing erroneous data such as outliers, duplicates, and where words rather than figures had been entered. 20 We then randomly divided the dataset equally into derivation and validation groups.…”

Section: Methodsmentioning

confidence: 99%

Development and validation of a trauma frailty scale in severely injured patients: the Nottingham Trauma Frailty Index

Alqarni,

Nightingale,

Norrish

et al. 2024

Bone Joint J

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AimsFrailty greatly increases the risk of adverse outcome of trauma in older people. Frailty detection tools appear to be unsuitable for use in traumatically injured older patients. We therefore aimed to develop a method for detecting frailty in older people sustaining trauma using routinely collected clinical data.MethodsWe analyzed prospectively collected registry data from 2,108 patients aged ≥ 65 years who were admitted to a single major trauma centre over five years (1 October 2015 to 31 July 2020). We divided the sample equally into two, creating derivation and validation samples. In the derivation sample, we performed univariate analyses followed by multivariate regression, starting with 27 clinical variables in the registry to predict Clinical Frailty Scale (CFS; range 1 to 9) scores. Bland-Altman analyses were performed in the validation cohort to evaluate any biases between the Nottingham Trauma Frailty Index (NTFI) and the CFS.ResultsIn the derivation cohort, five of the 27 variables were strongly predictive of the CFS (regression coefficient B = 6.383 (95% confidence interval 5.03 to 7.74), p < 0.001): age, Abbreviated Mental Test score, admission haemoglobin concentration (g/l), pre-admission mobility (needs assistance or not), and mechanism of injury (falls from standing height). In the validation cohort, there was strong agreement between the NTFI and the CFS (mean difference 0.02) with no apparent systematic bias.ConclusionWe have developed a clinically applicable tool using easily and routinely measured physiological and functional parameters, which clinicians and researchers can use to guide patient care and to stratify the analysis of quality improvement and research projects.Cite this article: Bone Joint J 2024;106-B(4):412–418.

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Section: Methodsmentioning

confidence: 99%

Development and validation of a trauma frailty scale in severely injured patients: the Nottingham Trauma Frailty Index

Alqarni,

Nightingale,

Norrish

et al. 2024

Bone Joint J

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“…The survey responses were downloaded in the form of Excel spreadsheet. Consequently, the manual copying of the answers did not cause transcription (Koszalinski et al , 2018). According to Baur et al (2015), missing responses may cause significant problems if their proportion to the total volume of responses is greater than 10%.…”

Section: Methodsmentioning

confidence: 99%

Examines the value of cloud computing adoption as a proxy for IT flexibility and effectiveness

A. Mjlae

2023

IDD

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Purpose The purpose of this study is to investigate the value of cloud computing adoption (CCA) as a proxy for information technology (IT) flexibility (ITF) and IT effectiveness (ITE) among Small- and medium-sized enterprises (SMEs) in Jordan. Design/methodology/approach A research framework with five hypotheses has been developed based on the results of previous studies. Partial least squares-structural equation modeling has been used for data analysis. Findings The results revealed that elements of ITF in two domains, IT technical resource (connectivity, modularityand compatibility) and IT human resource (IT personnel skills) specific to CCA, were significantly correlated with ITE. Research limitations/implications The findings have crucial implications: they contribute to the research community, administrators and cloud computing providers (CSPs) concerning the framework-improved procedure for CCA. The proposed model can enhance the awareness of service providers about why some SMEs accept cloud computing services, whereas actually the same ones having the same type of business do not. In addition, the above providers should enhance their interaction with the SMEs that contributed to the cloud computing knowledge to make a well-organized setting for the CCA, specifically, SMEs need that adopt an on-premise private cloud architecture. Moreover, necessary to determine the challenges in deploying solutions from the perspective of CSPs. The sample has been limited to Jordan respondents. Practical implications The research studies about the usage of cloud computing have shown its effects on SMEs today. Also, the different impacts of cloud computing on other sectors are at the center of attention. SMEs could get significant advantages by carefully considering and managing CCA from the ITF and ITE perspective. Originality/value To the best of the author’s knowledge, this is the first study to develop a framework for CCA based on the standpoint of ITF in two domains, IT technical resources (connectivity, modularity and compatibility) and IT human resources (IT personnel skills) and effectiveness.

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Using multivariate long short-term memory neural network to detect aberrant signals in health data for quality assurance

Miran

Nelson

Redd

et al. 2021

International Journal of Medical Informatics

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Missing Data, Data Cleansing, and Treatment From a Primary Study

Cited by 4 publications

References 11 publications

Development and validation of a trauma frailty scale in severely injured patients: the Nottingham Trauma Frailty Index

Development and validation of a trauma frailty scale in severely injured patients: the Nottingham Trauma Frailty Index

Examines the value of cloud computing adoption as a proxy for IT flexibility and effectiveness

Using multivariate long short-term memory neural network to detect aberrant signals in health data for quality assurance

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