PP13  Predicting high-risk conditions among ems patients with chest pain
Authors: Wibring Kristoffer , Herlitz Johan , Lingman Markus , Bång Angela 
Published: September 2020

Background

Chest pain is a common cause for contacting the EMS, representing 10–15% of all EMS missions. Within this group only 15% suffer from a high-risk condition. It is an important, but challenging, task to identify these patients in need of prompt hospital care.

Objective

To identify prehospital predictors of high-risk conditions among EMS patients with chest pain.

Methods

We prospectively included 2917 consecutive EMS missions concerning patients with chest pain. Data regarding, medical history, symptoms, vital parameters and troponin were collected. All patients were classified as having high-risk condition or not. High-risk condition was defined as a time-sensitive diagnose with high mortality rates in need of immediate care (based on diagnose on hospital discharge).

Results

In total 16% of included missions concerned a patient with a high-risk condition. In total 24 factors showed significantly increased odds of having a high-risk condition (table 1). Several factors also predicted lowered odds of high-risk condition.

Abstract PP13 Table 1

Factors predicting high-risk conditions, sorted by confidence interval (CI)

Total with variable% (n)Patients with high-risk condition% (n)Patients without high-risk condition% (n)High-risk vs without high-risk, p-value*Odds RatioCI 95%All100.0 (2917)16.0 (467)84.0 (2450)---ECG - ST-Elevation6.1 (164)22.9 (102)2.8 (62)< 0.0018.3375.520–12.593Prehospital Troponin T >50 ng/L11.2 (168)35.2 (90)6.3 (78)< 0.0016.3824.469–9.115ECG - ST-Depression7.6 (204)23.8 (106)4.4 (98)< 0.0014.6293.225–6.646Age ≥65 years65.2 (1902)76.7 (358)63.0 (1544)< 0.0013.8662.608–5.740NRS ≥95.1 (127)10.0 (41)4.1 (86)< 0.0013.2452.169–4.854Pain in right arm8.4 (145)16.4 (48)6.8 (97)< 0.0012.8861.967–4.235Pale16.4 (386)29.1 (111)14.0 (275)< 0.0012.4111.858–3.128Age 51–64 years18.5 (539)17.1 (80)18.7 (459)< 0.0012.7801.779–4.344Male sex50.2 (1465)63.8 (298)47.6 (1167)< 0.0012.0901.699–2.573Debut during activity22.1 (479)32.8 (116)20.0 (363)< 0.0012.1131.632–2.735Pain between scapulars2.2 (37)4.1 (12)1.8 (25)0.0032.9801.449–6.132Pain in left arm24.0 (412)33.6 (98)22.0 (314)< 0.0011.8611.406–2.462Central pain53.4 (1215)64.5 (240)51.2 (975)< 0.0011.7461.381–2.207NRS ≥632.1 (803)38.9 (159)30.8 (644)< 0.0011.6071.283–2.014Constant pain55.5 (1212)61.8 (235)49.9 (977)< 0.0011.6251.277–2.068Clammy8.7 (204)14.4 (55)7.6 (149)< 0.0011.5121.275–1.794Pain in jaw5.3 (92)7.5 (22)4.9 (70)0.0141.9071.142–3.184Breathing rate ≥25 breaths/min10.2 (297)14.7 (68)9.4 (229)0.0071.5051.118–2.026Band-shaped pain3.3 (58)5.2 (15)3.0 (43)0.0311.9741.064–3.662Quick debut, within minutes35.2 (718)42.7 (149)33.6 (569)0.0041.1941.059–1.346ECG - Premature Atrial Contractions, PAC3.5 (94)6.1 (27)3.0 (67)0.0341.7991.046–3.095Pain in right shoulder4.2 (72)6.2 (18)3.8 (54)0.0351.8301.042–3.213Oxygen saturation ≤91%3.8 (110)6.4 (30)3.3 (80)0.0461.5711.007–2.452ECG - T-wave Inversion14.5 (388)22.7 (101)12.8 (287)0.0461.4121.007–1.980

*Logistic regression, adjusted for age and sex

Conclusions

Several factors available in the prehospital setting seem to be suitable for risk assessment of patients with chest pain. Combing these factors in a scoring tool might be a feasible way to improve prehospital risk assessment.