Identifying patients at imminent risk of death is critical in the management of trauma patients. This study measures the vital sign thresholds associated with death among trauma patients.

This study included data from patients ≥15 years of age in the American College of Surgeons Trauma Quality Improvement Program (TQIP) database. Patients with vital signs of zero were excluded. Documented prehospital and emergency department (ED) vital signs included systolic pressure, heart rate, respiratory rate, and calculated shock index (SI). The area under the receiver operator curves (AUROC) was used to assess the accuracy of these variables for predicting 24-hour survival. Optimal thresholds to predict mortality were identified using Youden’s Index, 90% specificity, and 90% sensitivity. Additional analyses examined patients 70+ years of age.

There were 1,439,221 subjects in the 2019-2020 datasets that met inclusion for this analysis with <0.1% (10,270) who died within 24 hours. The optimal threshold for prehospital systolic pressure was 110, pulse rate was 110, SI was 0.9, and respiratory rate was 15. The optimal threshold for the ED systolic was 112, pulse rate was 107, SI was 0.9, and respiratory rate was 21. Among the elderly sub-analysis, the optimal threshold for prehospital systolic was 116, pulse rate was 100, SI was 0.8, and respiratory rate was 21. The optimal threshold for ED systolic was 121, pulse rate was 95, SI was 0.8, and respiratory rate was 21.

Systolic blood pressure (SBP) and SI offered the best predictor of mortality among trauma patients. The SBP values predictive of mortality were significantly higher than the traditional 90mmHg threshold. This dataset highlights the need for better methods to guide resuscitation as initial vital signs have limited accuracy in predicting subsequent mortality.

Prehospital vital signs are used to triage trauma patients to mobilize appropriate resources and personnel prior to patient arrival in the emergency department (ED). Due to inherent challenges in obtaining prehospital vital signs, concerns exist regarding their accuracy and ability to predict first ED vitals.

The objective of this study was to determine the correlation between prehospital and initial ED vitals among patients meeting criteria for highest levels of trauma team activation (TTA). The hypothesis was that in a medical system with short transport times, prehospital and first ED vital signs would correlate well.

Patients meeting criteria for highest levels of TTA at a Level I trauma center (2008-2018) were included. Those with absent or missing prehospital vital signs were excluded. Demographics, injury data, and prehospital and first ED vital signs were abstracted. Prehospital and initial ED vital signs were compared using Bland-Altman intraclass correlation coefficients (ICC) with good agreement as >0.60; fair as 0.40-0.60; and poor as <0.40).

After exclusions, 15,320 patients were included. Mean age was 39 years (range 0-105) and 11,622 patients (76%) were male. Mechanism of injury was blunt in 79% (n = 12,041) and mortality was three percent (n = 513). Mean transport time was 21 minutes (range 0-1,439). Prehospital and first ED vital signs demonstrated good agreement for Glasgow Coma Scale (GCS) score (ICC 0.79; 95% CI, 0.77-0.79); fair agreement for heart rate (HR; ICC 0.59; 95% CI, 0.56-0.61) and systolic blood pressure (SBP; ICC 0.48; 95% CI, 0.46-0.49); and poor agreement for pulse pressure (PP; ICC 0.32; 95% CI, 0.30-0.33) and respiratory rate (RR; ICC 0.13; 95% CI, 0.11-0.15).

Despite challenges in prehospital assessments, field GCS, SBP, and HR correlate well with first ED vital signs. The data show that these prehospital measurements accurately predict initial ED vitals in an urban setting with short transport times. The generalizability of these data to settings with longer transport times is unknown.

We sought to assess the presence and reporting quality of peer-reviewed literature concerning the accuracy, precision, and reliability of home monitoring technologies for vital signs and glucose determinations in older adult populations.

A narrative literature review was undertaken searching the databases Medline, Embase, and Compendex. Peer-reviewed publications with keywords related to vital signs, monitoring devices and technologies, independent living, and older adults were searched. Publications between the years 2012 and 2018 were included. Two reviewers independently conducted title and abstract screening, and four reviewers independently undertook full-text screening and data extraction with all disagreements resolved through discussion and consensus.

Two hundred nine articles were included. Our review showed limited assessment and low-quality reporting of evidence concerning the accuracy, precision, and reliability of home monitoring technologies. Of 209 articles describing a relevant device, only 45 percent (n = 95) provided a citation or some evidence to support their validation claim. Of forty-eight articles that described the use of a comparator device, 65 percent (n = 31) used low-quality statistical methods, 23 percent (n = 11) used moderate-quality statistical methods, and only 12 percent (n = 6) used high-quality statistical methods.

Our review found that current validity claims were based on low-quality assessments that do not provide the necessary confidence needed by clinicians for medical decision-making purposes. This narrative review highlights the need for standardized health technology reporting to increase health practitioner confidence in these devices, support the appropriate adoption of such devices within the healthcare system, and improve health outcomes.

This study aimed to ascertain the association between self-reported pain intensity and vital signs in both emergency department (ED) patients and a subgroup of patients with diagnosed conditions known to produce significant pain.

We performed a retrospective analysis of real-time, archived data from an electronic medical record system at an urban teaching hospital and regional community hospital. We included consecutive ED patients ≥16 years old who had a self-reported pain intensity ≥1 as measured during triage, from March 2005 to December 2012. The primary outcome was vital signs for self-reported pain intensity levels (mild, moderate, severe) on an 11-point verbal numerical scale. Changes in pain intensity levels were also compared to variations in vital signs. Both analyses were repeated on a subgroup of patients with diagnosed conditions recognized to produce significant pain: fracture, dislocation, or renal colic.

We included 153,567 patients (mean age of 48.4±19.3 years; 55.5% women) triaged with pain (median intensity of 7/10±3). Of these, 8.9% of patients had diagnosed conditions recognized to produce significant pain. From the total sample, the difference between mild and severe pain categories was 2.7 beats/minutes (95% CI: 2.4−3.0) for heart rate and 0.13 mm Hg (95% CI: -0.26−0.52) for systolic blood pressure. These differences generated small effect sizes and were not clinically significant. Results were similar for patients who experienced changes in pain categories and for those conditions recognized to produce significant pain.

Health care professionals cannot use vital signs to estimate or substantiate self-reported pain intensity levels or changes over time.

Vital signs remain important clinical indicators in the management of trauma. Tissue injury and ischemia cause tachycardia and hypertension, which are mediated via the sympathetic nervous system (SNS). Spinal immobilization is known to cause discomfort, and it is not known how this might influence the SNS and contribute to abnormal vital signs.

This study aimed to establish whether the pain and discomfort associated with spinal immobilization and the maneuvers commonly used in injured patients (eg, log roll) affect the Heart rate (HR), Systolic Blood Pressure (SBP) and Respiratory rate (RR). The null hypothesis was that there are no effects.

A prospective, unblinded, repeated-measure study of 53 healthy subjects was used to test the null hypothesis. Heart rate, BP and RR were measured at rest (five minutes), after spinal immobilization (10 minutes), following log roll, with partial immobilization (10 minutes) and again at rest (five minutes). A visual analog scale (VAS) for both pain and discomfort were also collected at each stage. Results were statistically compared.

Pain VAS increased significantly during spinal immobilization (3.8 mm, P < .01). Discomfort VAS increased significantly during spinal immobilization, after log roll and during partial immobilization (17.7 mm, 5.8 mm and 8.9 mm, respectively; P < .001). Vital signs however, showed no clinically relevant changes.

Spinal immobilization does not cause a change in vital signs despite a significant increase in pain and discomfort. Since no relationship appears to exist between immobilization and abnormal vital signs, abnormal vital signs in a clinical situation should not be considered to be the result of immobilization. Likewise, pain and discomfort in immobilized patients should not be disregarded due to lack of changes in vital signs.

BruijnsS, GulyH, WallisL. Effect of Spinal Immobilization on Heart Rate, Blood Pressure and Respiratory Rate. Prehosp Disaster Med. 2013;28(2):1-5.

Triage criteria rely on physiologic, anatomic, and mechanistic indicators of injury to minimize over-triage and under-triage, which remain persistendy high (35%—65%). The Visensia Index Score (VIS) is a proprietary algorithm in a bedside monitor (OBS Medical, IN) mat integrates five vital signs: (1) heart rate; (2) respiratory rate; (3) blood pressure; (4) pulse oximetry; and (5) temperature. It calculates a score ranging from 1 (no abnormality) to 5 (severe abnormalities). The aim of this study was to explore the utility of VIS in identifying trauma patients likely to have a poor prognosis on arrival to the emergency departments.

After Institutional Review Board approval, the trauma registry was used to review 117 patients admitted to a Level-1 Trauma Center over a six month period. The first set of vital signs was obtained upon arrival to the emergency department. An initial VIS and a mean VIS (based on multiple VS) was calculated. The analysis included a multivariate mathematical technique and k-means cluster analysis. Clusters of populations with different Visensia scores were compared and differences in their outcomes were analyzed.

Two major clusters were identified: VIS Scores >3 increased the risk of mortality as compared to those with scores <3; odds ratio 3.3 [1.04–10.3; p <0.001). There was no association with length of intensive care unit stay, hospital days; or Injury Severity Scale (ISS) scores.

Cluster analysis, a novel multidimensional approach, shows association of a higher VIS (>3) as a useful point-of-care parameter to identify trauma patients likely to have a poorer prognosis, much more than retrospectively computed ISS and Trauma and Injury Severity Scores (TRISS).

Vital signs (VS) data collected in prehospital care and recorded in trauma registries are often missing or unreliable as it is difficult to record dynamic changes while performing resuscitation and stabilization. The purpose of this study was to test the hypothesis that analysis of continuous vital signs improves data quality, and predicts life-saving interventions (LSI) better than use of retrospectively compiled Trauma Registry (TR) data.

After Institutional Review Board approval, six emergency medical services helicopters were equipped with a Vital Signs Data Recorder (VSDR) to capture continuous VS from the patient onto a handheld personal digital assistant (PDA). Prehospital LSIs (fluid bolus, cardiopul-monary resuscitation, drugs, intubation, etc.) and those performed within two hours after arrival in the trauma resuscitation unit were considered outcome variables. The VSDR and TR data were compared using Bland-Altman method. A multivariate analysis was performed to determine which VS variable best predicted LSIs using the values in the TR and the VSDR.

Prehospital VSDR data were collected from 177 patients. There was a significant difference between the highest and lowest heart rate, systolic blood pressure (SBP), and oxygen saturation between the VSDR and the TR data (p <0.001).The VSDR highest heart rate and lowest oxygen saturation recorded predicted LSIs while none of the TR vital signs did so in a multivariate model. The SBP was not an independent predictor of LSI.

The VSDR data increased the odds of predicting LSIs compared to the TR data. Using continuous vital signs in prehospital care may lead to the development of better trauma prognostic models.

A reported in-field, prospective evaluation of 227 prehospital patient assessments by advanced life support (ALS) emergency medical technicians (EMTs) found a frequent failure to measure vital signs. The objective of this retrospective review was to report the omission frequency of vital signs found in a centralized emergency medical services (EMS) data collection system.

The EMS database contained information from 90,480 optically scanned, prehospital patient encounter forms. Each record identified EMT skill levels, response times, dispatch type, vital signs, medical and trauma information, treatment, and patient disposition. Records for 1989 and 1990 were collected from 92 rural EMS providers who responded to emergency medical and trauma events.

Of 90,480 emergency responses, 14,129 (15.6%) were false alarms, deceased, or canceled without vital patient contact. Valid encounters were documented for 76,351 (84.4%) patient contacts. Systolic blood pressure measurements were not recorded for 13,262 (17.4%) patients. Diastolic blood pressure was not recorded for 14,272 (18.7%) patients. A pulse record was not recorded for 12,125 (15.9%) patients. A ventilatory rate was absent in 12,958 (17.0%) patient records.

This study found a frequent failure by non-metropolitan basic life support (BLS) and advanced life support (ALS) EMTs to record vital signs on prehospital emergency patient encounter forms. It supports a previous report of direct in-field observations of ALS EMTs failing to measure vital signs during patient assessment. The impact of vital sign omissions upon individual patient care can be assessed only by receiving medical control physicians. In the absence of effective emergency physician networking, the statewide magnitude of the problem among BLS and ALS EMTs has not been recognized as a system issue.