WaLIDD score, a new tool to diagnose dysmenorrhea and predict medical leave in university students

Abstract

Background: Dysmenorrhea is a frequent and misdiagnosed symptom affecting the quality of life in young women. A working ability, location, intensity, days of pain, dysmenorrhea (WaLIDD) score was designed to diagnose dysmenorrhea and to predict medical leave.

Methods: This cross-sectional design included young medical students, who completed a self-administered questionnaire that contained the verbal rating score (VRS; pain and drug subscales) and WaLIDD scales. The correlation between scales was established through Spearman test. The area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and likelihood ratio (LR +/-) were evaluated to diagnose students availing medical leave due to dysmenorrhea; moreover, to predict medical leave in students with dysmenorrhea, a binary logistic regression was performed.

Results: In all, 585 students, with a mean age of 21 years and menarche at 12 years, participated. Most of them had regular cycles, 5 days of menstrual blood flow and 1-2 days of lower abdominal pain. The WaLIDD scale presented an adequate internal consistency and strong correlation with VRS subscales. With a cutoff of >6 for WaLIDD and 2 for VRS subscales (drug subscale and pain subscale) to identify students with dysmenorrhea, these scales presented an area under the curve (AUC) ROC of 0.82, 0.62, and 0.67, respectively. To identify students taking medical leave due to dysmenorrhea, WaLIDD (cutoff >9) and VRS subscales (cutoff >2) presented an AUC ROC of 0.97, 0.68, and 0.81; moreover, the WaLIDD scale showed a good LR +14.2 (95% CI, 13.5-14.9), LR -0.00 (95% CI, undefined), and predictive risk (OR 5.38; 95% CI, 1.78-16.2).

Conclusion: This research allowed a comparison between two multidimensional scales regarding their capabilities, one previously validated and a new one, to discriminate among the general population of medical students, among those with dysmenorrhea or those availing medical leave secondary to dysmenorrhea. WaLIDD score showed a larger effect size than the pain and drug score in the students. In addition, this study demonstrated the ability to predict this combination of events.

Keywords: clinical decision making; diagnosis; dysmenorrhea; medical students; sick leave.

Conflict of interest statement

Disclosure The authors report no conflicts of interest in this work.

Figures

Figure 1

ROC curves of VRS sub-scores and WaLIDD score in dysmenorrhea cases. Notes: WaLIDD score AUC 0.817 (95% CI, 0.781–0.852); pain score AUC 0.623 (95% CI, 0.570–0.623); drug score AUC 0.678 (95% CI, 0.628–0.727). Abbreviations: AUC, area under the curve; ROC, receiver operating characteristic; VRS, verbal rating score; WaLIDD, working ability, location, intensity, days of pain, dysmenorrhea.

Figure 2

Dysmenorrhea scores in a general population of university students with dysmenorrhea, medical leave, or both features. Notes: The pain and drug scales, both with 0–3 points interval, and working ability, location, intensity, days of pain, dysmenorrhea (WaLIDD) scale with 0–12 points interval, are represented in all university students (general population), with dysmenorrhea (D), with medical leave (ML), or both features (D + ML). Bars without lines or dots represent scores in the general population (pain, drug, WaLIDD); horizontal lines represent students classified with dysmenorrhea (pain D, drug D, WaLIDD D); crossed lines represent students with medical leave (pain ML, drug ML, WaLIDD ML); and dots represent students with dysmenorrhea and medical leave (pain D + ML, drug D + ML, WaLIDD D + ML).

Figure 3

ROC curves of VRS sub-scores and WaLIDD score in dysmenorrhea cases with medical leave. Notes: WaLIDD score AUC 0.974 (95% CI, 0.951–0.997); pain score AUC 0.793 (95% CI, 0.618–0.968); and drug score AUC 0.810 (95% CI, 0.700–0.920). Abbreviations: AUC, area under the curve; ROC, receiver operating characteristic; VRS, verbal rating score; WaLIDD, working ability, location, intensity, days of pain, dysmenorrhea.