| Literature DB >> 31757059 |
Michael Doulberis1,2,3, Apostolis Papaefthymiou2,4, Jannis Kountouras2, Stergios A Polyzos5, Simone Srivastava6, Jolanta Klokowska-Röetzler3, Martin Perrig7, Sylvana Papoutsi6, Aristomenis Κ Exadaktylos3, David Shiva Srivastava3.
Abstract
Background: Abdominal pain is one of the commonest symptoms in emergency departments (EDs). Diagnosis demands full attention and critical thinking, since many diseases manifest atypically and the consequences of overlooking the symptoms may be disastrous. Despite intensive diagnostic procedures, some cases remain elusive and unclear abdominal pain (UAP) is not infrequent. Emerging evidence supports the hypothesis that functional pain might be attributed to vitamin D deficiency (VDD). People with darker or covered skin are predisposed to developing VDD. Patients in Switzerland stemming from low- and middle-income countries (LMIC) are such a population. Aim: To identify cases with UAP in LMIC patients and to compare vitamin D status with a control group.Entities:
Keywords: abdominal pain; emergency department; irritable bowel syndrome (IBS)1. Introduction; low income; middle income; migrants; vitamin D
Mesh:
Year: 2019 PMID: 31757059 PMCID: PMC6926624 DOI: 10.3390/ijerph16234607
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Flow chart of the search procedure for the identification of eligible patients. C; cardiological cases, G; gastrointestinal cases, Gy; gynecological cases; I; infectious cases, LMIC; low- and middle-income countries, N; neurological cases; U; urological/renal cases, Trauma cases, V; various cases (such as; body packer, intoxications (including alcohol), suicide attempt, rheumatological, ORL, unclear thoracic pain-dyspnea, orthopedic without trauma, thrombosis etc.).
Figure 2Schematic representation of the chosen algorithm for case selection. AP; abdominal pain, ED; emergency department, CT; computer tomography, G; gastroenterologist, Gy; gynecologist, S; surgeon, U; urologist/nephrologist.
Percentages of genders per group.
| Group | Total | ||||
|---|---|---|---|---|---|
| Controls | Patients | ||||
| Gender | Women | Count | 13 | 17 | 30 |
| % within gender | 43.3% | 56.7% | 100.0% | ||
| % within group | 48.1% | 63.0% | 55.6% | ||
| Men | Count | 14 | 10 | 24 | |
| % within gender | 58.3% | 41.7% | 100.0% | ||
| % within group | 51.9% | 37.0% | 44.4% | ||
| Total | Count | 27 | 27 | 54 | |
| % within gender | 50.0% | 50.0% | 100.0% | ||
| % within group | 100.0% | 100.0% | 100.0% | ||
Basic parameters.
| Group | n | Mean | Std. Deviation | Std. Error Mean | ||
|---|---|---|---|---|---|---|
| Age | Controls | 27 | 47.70 | 13.088 | 2.519 | 0.085 |
| Patients | 27 | 41.30 | 13.708 | 2.638 | ||
| BMI | Controls | 27 | 26.163 | 5.6835 | 1.0938 | 0.186 |
| Patients | 27 | 24.259 | 4.7021 | 0.9049 | ||
| 25OHD* (nmol/L) | Controls | 27 | 53.67 | 22.940 | 4.415 | 0.060 |
| Patients | 27 | 41.26 | 24.513 | 4.718 |
*: 25-OH-cholecalciferol.
VDD in both groups.
| Group | Total | |||||
|---|---|---|---|---|---|---|
| Controls | Patients | |||||
| 25OHD a nmol/L | ≤25 | Count | 1 | 14 | 15 | |
| % within group | 3.7% | 51.9% | 27.8% | |||
| >25 | Count | 26 | 13 | 39 | ||
| % within group | 96.3% | 48.1% | 72.2% | |||
| Total | Count | 27 | 27 | 54 | ||
| % within group | 100.0% | 100.0% | 100.0% | |||
| 25OHD b nmol/L | ≤50 | Count | 13 | 21 | 34 | |
| % within group | 48.1% | 77.8% | 63.0% | |||
| >50 | Count | 14 | 6 | 20 | ||
| % within group | 51.9% | 22.2% | 37.0% | |||
| Total | Count | 27 | 27 | 54 | ||
| % within group | 100.0% | 100.0% | 100.0% | |||
a p < 0.001; b p = 0.024; 25OHD: 25-OH-cholecalciferol; VDD: vitamin D deficiency.
Geographical regions of origin for LMIC(low- and middle-income countries) subjects.
| Frequency | Percent | Valid Percent | Cumulative Percent | |
|---|---|---|---|---|
| South America | 3 | 5.6 | 5.6 | 5.6 |
| Eastern Africa | 3 | 5.6 | 5.6 | 11.1 |
| Northern Africa | 6 | 11.1 | 11.1 | 22.2 |
| Caribbean | 1 | 1.9 | 1.9 | 24.1 |
| Eastern Asia | 5 | 9.3 | 9.3 | 33.3 |
| Southern Asia | 9 | 16.7 | 16.7 | 50.0 |
| South-eastern Asia | 2 | 3.7 | 3.7 | 53.7 |
| Southern Europe | 11 | 20.4 | 20.4 | 74.1 |
| Western Asia | 6 | 11.1 | 11.1 | 85.2 |
| Eastern Europe | 7 | 13.0 | 13.0 | 98.1 |
| Northern Europe | 1 | 1.9 | 1.9 | 100.0 |
| Total | 54 | 100.0 | 100.0 |
Figure 3Continental distribution of subjects.
Figure 4Swiss Emergency Triage Scale depicting the number of cases per category.
Types of admission and discharge for LMIC subjects.
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
|---|---|---|---|---|---|
| Police | 1 | 1.9 | 1.9 | 1.9 | |
| Self-admission | 38 | 70.4 | 70.4 | 72.2 | |
| Ambulance | 5 | 9.3 | 9.3 | 81.5 | |
| Private (GP) | 3 | 5.6 | 5.6 | 87.0 | |
| Primary utilization | 3 | 5.6 | 5.6 | 92.6 | |
| Other or not specified | 4 | 7.4 | 7.4 | 100.0 | |
| Total | 54 | 100.0 | 100.0 | ||
| Discharge | At home | 42 | 77.8 | 77.8 | 77.8 |
| Inpatient | 9 | 16.7 | 16.7 | 94.4 | |
| Other or not specified | 3 | 5.6 | 5.6 | 100.0 | |
| Total | 54 | 100.0 | 100.0 | ||
GP: general practitioner; LMIC: low- and middle-income countries.
Sub-group analysis for women.
| Group | n | Mean | Std. Deviation | Std. Error Mean | ||
|---|---|---|---|---|---|---|
| Age | Controls | 13 | 43.31 | 13.073 | 3.626 | 0.179 |
| Patients | 17 | 36.65 | 13.124 | 3.183 | ||
| BMI | Controls | 13 | 26.908 | 5.8273 | 1.6162 | 0.194 |
| Patients | 17 | 24.329 | 4.7864 | 1.1609 | ||
| 25OHD (nmol/L) | Controls | 13 | 53.31 | 25.316 | 7.021 | 0.037 |
| Patients | 17 | 36.59 | 16.382 | 3.973 |
25OHD: 25-OH-cholecalciferol.