Dataset Information

Development of a categorical naming test in Korean: Standardization and clinical application for patients with stroke.

ABSTRACT:

Purpose

The purpose of this study was to develop and standardize a new categorical naming test, titled the Categorical Naming Test (CNT), for stroke patients, and to investigate its validity and clinical usefulness for patients with stroke.

Materials and methods

The CNT was developed based on semantic category, imageability, and psycholinguistic factors such as word frequency and word length. The test materials included two main semantic categories (living objects and artificial objects) comprising 60 items. We standardized the CNT on 221 healthy adults and administered the CNT to 112 stroke patients.

Results

Internal consistency and concurrent validity of the test were high. The mean total CNT scores varied significantly according to participants' age, sex, and education. Among healthy controls, the scores for naming living objects were significantly higher than those for artificial objects. The analysis of stroke patients showed that the total CNT score revealed a statistically significant difference based on the patients' lesion laterality and presence of aphasia, after controlling for age, sex, and education. However, the categorical scores achieved by comparing the naming scores for living and artificial objects showed no significant differences according to lesion laterality, stroke type, and presence of aphasia.

Conclusion

The CNT is a newly developed version of an overt naming task with high internal consistency validity for stroke patients in Korea. The newly developed CNT can prove useful in evaluating naming ability in stroke patients.

SUBMITTER: Hwang YM

PROVIDER: S-EPMC7895370 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Development of a categorical naming test in Korean: Standardization and clinical application for patients with stroke.

Hwang Yu Mi YM Na Yoonhye Y Pyun Sung-Bom SB

PloS one 20210219 2

<h4>Purpose</h4>The purpose of this study was to develop and standardize a new categorical naming test, titled the Categorical Naming Test (CNT), for stroke patients, and to investigate its validity and clinical usefulness for patients with stroke.<h4>Materials and methods</h4>The CNT was developed based on semantic category, imageability, and psycholinguistic factors such as word frequency and word length. The test materials included two main semantic categories (living objects and artificial o ...[more]

PMID: 33606717

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Project description:BACKGROUND:Data standardization is essential in electronic health records (EHRs) for both clinical practice and retrospective research. However, it is still not easy to standardize EHR data because of nonidentical duplicates, typographical errors, or inconsistencies. To overcome this drawback, standardization efforts have been undertaken for collecting data in a standardized format as well as for curating the stored data in EHRs. To perform clinical big data research, the stored data in EHR should be standardized, starting from laboratory results, given their importance. However, most of the previous efforts have been based on labor-intensive manual methods. OBJECTIVE:We aimed to develop an automatic standardization method for eliminating the noises of categorical laboratory data, grouping, and mapping of cleaned data using standard terminology. METHODS:We developed a method called standardization algorithm for laboratory test-categorical result (SALT-C) that can process categorical laboratory data, such as pos +, 250 4+ (urinalysis results), and reddish (urinalysis color results). SALT-C consists of five steps. First, it applies data cleaning rules to categorical laboratory data. Second, it categorizes the cleaned data into 5 predefined groups (urine color, urine dipstick, blood type, presence-finding, and pathogenesis tests). Third, all data in each group are vectorized. Fourth, similarity is calculated between the vectors of data and those of each value in the predefined value sets. Finally, the value closest to the data is assigned. RESULTS:The performance of SALT-C was validated using 59,213,696 data points (167,938 unique values) generated over 23 years from a tertiary hospital. Apart from the data whose original meaning could not be interpreted correctly (eg, ** and _^), SALT-C mapped unique raw data to the correct reference value for each group with accuracy of 97.6% (123/126; urine color tests), 97.5% (198/203; (urine dipstick tests), 95% (53/56; blood type tests), 99.68% (162,291/162,805; presence-finding tests), and 99.61% (4643/4661; pathogenesis tests). CONCLUSIONS:The proposed SALT-C successfully standardized the categorical laboratory test results with high reliability. SALT-C can be beneficial for clinical big data research by reducing laborious manual standardization efforts.

Project description:The availability of fast validated screening for dementia is a critical clinical need to improve neurologic examination time efficiency. This study validated a 1-minute timed categorical recall (TCR) method, naming as many US cities as possible and compared TCR to the Folstein Minimental Status Exam (MMSE) as a preliminary cognitive screening tool. Random uncompensated 349 volunteers were recruited ages 18 to 97 from local free clinics, retirement homes, university faculty, and students in Lynchburg, Virginia 2015 to 2020. Participants' demographic and medical information were collected. After 1 minute preparation, participants were rapidly named as many US cities as possible until they were told to stop (1 minute). The time limitation was withheld in advance. Number of cities and organizational strategies were recorded. Folstein MMSE administration immediately after TCR was administered to 122 subjects recruited in the final 2 study years as a comparison benchmark. A multiple linear regression model and a regression tree model were used to identify important variables for the number of cities named and determine subgroups and their thresholds. TCR resulted in accuracy rate (0.80), sensitivity (0.78), and specificity (0.81). The global TCR threshold (9 cities named) is superseded by 4 subgroup thresholds, categorized by statistically important variables (age, education level, and number of states visited) as follows: For those visiting ≥8 states and 1. 18 to 71 ages with a master's degree or above, the threshold was naming 20 cities; 2. 18 to 29 ages with a bachelor's degree or below, the threshold was naming 17 cities; 3. 30 to 71 ages with a bachelor's degree or below, the threshold was naming 10 cities. For those visiting <8 states or for ages 72 to 97 (regardless of education levels and number of states visited), the threshold was naming 8 cities. American cities are common knowledge across ages and backgrounds, making it a useful bedside screen for dementia. In clinical practice, patients who report fewer cities than the threshold of 9 cities should receive further cognitive testing. If the patient meets the criteria for a subgroup, then the higher subgroup thresholds apply. TCR is a more time-efficient preliminary dementia screening tool with improved sensitivity and similar specificity compared with MMSE.

Dataset Information

Development of a categorical naming test in Korean: Standardization and clinical application for patients with stroke.

Purpose

Materials and methods

Results

Conclusion

Publications

Development of a categorical naming test in Korean: Standardization and clinical application for patients with stroke.

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