Statistical Risk Characteristics and Risk Scoring of Hospital-Acquired Malnutrition for Pediatric Patients
Background. Malnutrition is a global health problem and challenge for every country. It may occur in any form and affect all levels of age including children. We pay particular attention to the so-called hospital-acquired malnutrition (HaM) for pediatric patients. Our aim was to explore statistical...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Journal of Nutrition and Metabolism |
| Online Access: | http://dx.doi.org/10.1155/2020/4305487 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832566286020771840 |
|---|---|
| author | Khreshna Syuhada Dessie Wanda Risti Nur’aini Chairun Ardiantari Ayu Susilo |
| author_facet | Khreshna Syuhada Dessie Wanda Risti Nur’aini Chairun Ardiantari Ayu Susilo |
| author_sort | Khreshna Syuhada |
| collection | DOAJ |
| description | Background. Malnutrition is a global health problem and challenge for every country. It may occur in any form and affect all levels of age including children. We pay particular attention to the so-called hospital-acquired malnutrition (HaM) for pediatric patients. Our aim was to explore statistical risk factors or characteristics as well as to forecast risk scoring for such malnutrition. Methods. This study employed a cross-sectional design involving children from 1 month to 18 years of age who were hospitalized for at least 72 hours. We used secondary data from 308 medical records of pediatric patients who were admitted to the hospital in 2017. We excluded the data if the patient had tumors or organomegaly, fluid retention, and dehydration. HaM was determined based on a weight loss each day during hospitalization until the day of discharge. Statistical data analysis is carried out for both descriptive and inferential statistics. Our predictive model is yielded by linear regression, and risk scoring is obtained through logistic regression. Results. The findings showed several risk factors or characteristics for HaM prevalence: sex, age, medical diagnosis, diet, nutrition route, and NEWS score. The early warning system to pediatric patients is conducted by calculating malnutrition-at-risk in which a value beyond 100.5 is considered as having high potential risk for HaM. Conclusion. Nurses are expected to monitor pediatric patients’ condition, including measuring the anthropometry regularly, in order to identify the initial signs of HaM. |
| format | Article |
| id | doaj-art-8305373940114f8eb9c64bb93803a5e1 |
| institution | Kabale University |
| issn | 2090-0724 2090-0732 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Nutrition and Metabolism |
| spelling | doaj-art-8305373940114f8eb9c64bb93803a5e12025-02-03T01:04:30ZengWileyJournal of Nutrition and Metabolism2090-07242090-07322020-01-01202010.1155/2020/43054874305487Statistical Risk Characteristics and Risk Scoring of Hospital-Acquired Malnutrition for Pediatric PatientsKhreshna Syuhada0Dessie Wanda1Risti Nur’aini2Chairun Ardiantari3Ayu Susilo4Statistics Research Division, Institut Teknologi Bandung, Bandung, IndonesiaFaculty of Nursing, Universitas Indonesia, Depok, IndonesiaStatistics Research Division, Institut Teknologi Bandung, Bandung, IndonesiaFaculty of Nursing, Universitas Indonesia, Depok, IndonesiaStatistics Research Division, Institut Teknologi Bandung, Bandung, IndonesiaBackground. Malnutrition is a global health problem and challenge for every country. It may occur in any form and affect all levels of age including children. We pay particular attention to the so-called hospital-acquired malnutrition (HaM) for pediatric patients. Our aim was to explore statistical risk factors or characteristics as well as to forecast risk scoring for such malnutrition. Methods. This study employed a cross-sectional design involving children from 1 month to 18 years of age who were hospitalized for at least 72 hours. We used secondary data from 308 medical records of pediatric patients who were admitted to the hospital in 2017. We excluded the data if the patient had tumors or organomegaly, fluid retention, and dehydration. HaM was determined based on a weight loss each day during hospitalization until the day of discharge. Statistical data analysis is carried out for both descriptive and inferential statistics. Our predictive model is yielded by linear regression, and risk scoring is obtained through logistic regression. Results. The findings showed several risk factors or characteristics for HaM prevalence: sex, age, medical diagnosis, diet, nutrition route, and NEWS score. The early warning system to pediatric patients is conducted by calculating malnutrition-at-risk in which a value beyond 100.5 is considered as having high potential risk for HaM. Conclusion. Nurses are expected to monitor pediatric patients’ condition, including measuring the anthropometry regularly, in order to identify the initial signs of HaM.http://dx.doi.org/10.1155/2020/4305487 |
| spellingShingle | Khreshna Syuhada Dessie Wanda Risti Nur’aini Chairun Ardiantari Ayu Susilo Statistical Risk Characteristics and Risk Scoring of Hospital-Acquired Malnutrition for Pediatric Patients Journal of Nutrition and Metabolism |
| title | Statistical Risk Characteristics and Risk Scoring of Hospital-Acquired Malnutrition for Pediatric Patients |
| title_full | Statistical Risk Characteristics and Risk Scoring of Hospital-Acquired Malnutrition for Pediatric Patients |
| title_fullStr | Statistical Risk Characteristics and Risk Scoring of Hospital-Acquired Malnutrition for Pediatric Patients |
| title_full_unstemmed | Statistical Risk Characteristics and Risk Scoring of Hospital-Acquired Malnutrition for Pediatric Patients |
| title_short | Statistical Risk Characteristics and Risk Scoring of Hospital-Acquired Malnutrition for Pediatric Patients |
| title_sort | statistical risk characteristics and risk scoring of hospital acquired malnutrition for pediatric patients |
| url | http://dx.doi.org/10.1155/2020/4305487 |
| work_keys_str_mv | AT khreshnasyuhada statisticalriskcharacteristicsandriskscoringofhospitalacquiredmalnutritionforpediatricpatients AT dessiewanda statisticalriskcharacteristicsandriskscoringofhospitalacquiredmalnutritionforpediatricpatients AT ristinuraini statisticalriskcharacteristicsandriskscoringofhospitalacquiredmalnutritionforpediatricpatients AT chairunardiantari statisticalriskcharacteristicsandriskscoringofhospitalacquiredmalnutritionforpediatricpatients AT ayususilo statisticalriskcharacteristicsandriskscoringofhospitalacquiredmalnutritionforpediatricpatients |