| Title |
Prediction of risk of depressive symptoms in menopausal women based on hot flash and sweating symptoms: a multicentre study
|
|---|---|
| Published in |
Clinical Interventions in Aging, November 2017
|
| DOI | 10.2147/cia.s148688 |
| Pubmed ID | |
| Authors |
Yanwei Zheng, Yibei Zhou, Jiangshan Hu, Jieping Zhu, Qi Hua, Minfang Tao |
| Abstract |
The present study aimed to develop a symptom-based (namely, hot flashes and sweating) scoring system for predicting the risk of depressive symptoms in menopausal women via a multicentre cross-sectional survey. The data examined in the present study were obtained from 1,004 women aged 40-60 years who underwent physical examination at A Hospital. The basic information was obtained using a questionnaire-based survey. A self-rating depression scale was used to obtain the depressive symptom scores, while the Kupperman Menopausal Index was used to obtain the scores for the frequency of hot flashes and sweating. A logistic regression model was also established. The resulting β coefficient was employed to calculate and predict the risk of depressive symptoms in these women and a risk scoring system was established. The scoring system was validated using samples from 2 other centers (validation sample 1: B Hospital, 440 women; validation sample 2: C Hospital, 247 women). The scoring system developed to predict the risk of depressive symptoms in menopausal women was based on hot flash and sweating symptoms and associated with menopausal status, hot flash scores, education level (high school education and below) and being diabetic. The scoring system yielded a total score of 0-54 points. For women in the study sample, the area under the curve (AUC) of depressive symptom risk score was 0.750 (95% CI, 0.708-0.793). Validation sample 1 had an AUC of 0.731 (95% CI, 0.667-0.794), while validation sample 2 had an AUC of 0.744 (95% CI, 0.669-0.820). The optimal cut-off score to assess depressive symptoms in women participating in the present study was 31 points. The sensitivity and specificity for predicting depressive symptoms in the study sample were 0.667 and 0.701, respectively. In contrast, the sensitivity was 0.840 in validation sample 1 and 0.879 in validation sample 2. The hot flash and sweating symptom-based scoring system developed to predict the risk of depressive symptoms in menopausal women relies on non-laboratory survey data. The system is simple, practical, and convenient to use. For Chinese huge population of menopausal women, the scoring system should be considered a reliable screening tool for depressive symptoms. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 16% |
| Researcher | 5 | 11% |
| Student > Master | 4 | 9% |
| Student > Ph. D. Student | 4 | 9% |
| Librarian | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 21 | 48% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 16% |
| Psychology | 5 | 11% |
| Nursing and Health Professions | 2 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Sports and Recreations | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 25 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 December 2017.
All research outputs
#16,725,651
of 25,382,440 outputs
Outputs from Clinical Interventions in Aging
#1,182
of 1,968 outputs
Outputs of similar age
#206,464
of 340,752 outputs
Outputs of similar age from Clinical Interventions in Aging
#41
of 62 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,968 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one is in the 36th percentile – i.e., 36% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 340,752 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.