Decreased facial expression variability in patients with serious cardiopulmonary disease in the emergency care setting

Gestalt clinical severity score (GCSS) as a predictor of patient severity of illness or injury

OBJECTIVE

To determine if clinical judgement is accurate to predict the severity of injury or illness, and can be used at patient arrival when other formal scoring systems are not yet available.

DESIGN

A multicenter pilot study using a prospective observational convenience sample of patients arriving by EMS to the emergency department (ED) or Trauma Center.

SETTING

Two urban, Level 1 trauma centers at academic tertiary care hospitals.

PATIENTS

Medical and trauma patients age 18 and older transported by EMS (N = 216). Exclusion criteria (prior to arrival): intubation, assisted ventilation (BVM or NPPV), CPR in progress, prisoners, or previously present motor or speech deficits.

MEASUREMENTS

Completion of a novel 15-point scale of Verbal, Motor, and Facial Expression within 1-2 min of arrival by a clinician outside of the treatment team. Primary endpoint was the immediate disposition from the ED or Trauma Center: Home, Brief Observation (<24 h), Admission to Floor, ICU (OR and IR as surrogates since these patients ultimately go to the ICU), or Morgue.

RESULTS

Univariate analysis revealed a strong, positive monotonic correlation between GCSS and disposition (Rho = 0.693, p < .0001). Multivariable logistic regression revealed the "best" model included GCSS and age (group 18-44 years old versus all the other age groups) (p < .0001). There was a 156% increase in the odds of being discharged home (versus being admitted) for a one-unit increase in GCSS (OR = 2.56, 95% CI 1.94, 3.37).

CONCLUSIONS

Physicians can make accurate predictions of severity of injury and illness using a gestalt method and the scoring system we have developed as patient disposition correlates well with GCSS score. GCSS is most accurate with the 18-44 age group.

Identifying emotional Facial Expressions in Practice: A Study on Medical Students

BACKGROUND

Successful identification of emotional expression in patients is of considerable importance in the diagnosis of diseases and while developing rapport between physicians and patients. Despite the importance of such skills, this aspect remains grossly overlooked in conventional medical training in India. This study aims to explore the extent to which medical students can identify emotions by observing photographs of male and female subjects expressing different facial expressions.

METHODS

A total of 106 medical students aged 18-25, without any diagnosed mental illnesses, were shown images of the six universal facial expressions (anger, sadness, fear, happiness, disgust, and surprise) at 100% intensity with an exposure time of 2 seconds for each image. The participants marked their responses after each image was shown. Collected data were analyzed using Statistical Package for the Social Sciences.

RESULTS

Participants could identify 76.54% of the emotions on average, with higher accuracy for positive emotions (95.6% for happiness) and lower for negative emotions (46% for fear). There were no significant variations in identification with respect to sex of the observers. However, it was seen that participants could identify emotions better from male faces than those from female faces, a finding that was statistically significant. Negative emotions were identified more accurately from male faces, while positive emotions were identified better from female ones.

CONCLUSIONS

Male participants identified emotions better from male faces, while females identified positive emotions better from female faces and negative ones from male faces.

Impact of Patient Affect on Physician Estimate of Probability of Serious Illness and Test Ordering

PURPOSE

The authors hypothesize patient facial affect may influence clinician pretest probability (PTP) estimate of cardiopulmonary emergency (CPE) and desire to order a computerized tomographic pulmonary angiogram (CTPA).

METHOD

This prospective study was conducted at three Indiana University-affiliated hospitals in two parts: collecting videos of patients undergoing CTPA for suspected acute pulmonary embolism watching a humorous video (August 2014-April 2015) and presenting the medical histories and videos to clinicians to determine the impact of patient facial affect on physicians' PTP estimate of CPE and desire to order a CTPA (June-November 2015). Patient outcomes were adjudicated as CPE+ or CPE- by three independent reviewers. Physicians completed a standardized test of facial affect recognition, read standardized medical histories, then viewed videos of the patients' faces. Clinicians marked their PTP estimate of CPE and desire for a CTPA before and after seeing the video on a visual analog scale (VAS).

RESULTS

Fifty physicians completed all 73 videos. Seeing the patient's face produced a > 10% absolute change in PTP estimate of CPE in 1,204/3,650 (33%) cases and desire for a CTPA in 1,095/3,650 (30%) cases. The mean area under the receiver operating characteristic curve for CPE estimate was 0.55 ± 0.15, and the change in CPE VAS was negatively correlated with physicians' standardized test scores (r = -0.23).

CONCLUSIONS

Clinicians may use patients' faces to make clinically important inferences about presence of serious illness and need for diagnostic testing. However, these inferences may fail to align with actual patient outcomes.

Emergency Department Cardiopulmonary Evaluation of Low-Risk Chest Pain Patients with Self-Reported Stress and Anxiety

BACKGROUND

Chest pain is a high-risk emergency department (ED) chief complaint; the majority of clinical resources are directed toward detecting and treating cardiopulmonary emergencies. However, at follow-up, 80%-95% of these patients have only a symptom-based diagnosis; a large number have undiagnosed anxiety disorders.

OBJECTIVE

Our aim was to measure the frequency of self-identified stress or anxiety among chest pain patients, and compare their pretest probabilities, care processes, and outcomes.

METHODS

Patients were divided into two groups: explicitly self-reported anxiety and stress or not at 90-day follow-up, then compared on several variables: ultralow (<2.5%) pretest probability, outcome rates for acute coronary syndrome (ACS) and pulmonary embolism (PE), radiation exposure, total costs at 30 days, and 90-day recidivism.

RESULTS

Eight hundred and forty-five patients were studied. Sixty-seven (8%) explicitly attributed their chest pain to "stress" or "anxiety"; their mean ACS pretest probability was 4% (95% confidence interval 2.9%-5.7%) and 49% (33/67) had ultralow pretest probability (0/33 with ACS or PE). None (0/67) were diagnosed with anxiety. Seven hundred and seventy-eight did not report stress or anxiety and, of these, 52% (403/778) had ultralow ACS pretest probability. Only one patient (0.2%; 1/403) was diagnosed with ACS and one patient (0.4%; 1/268) was diagnosed with PE. Patients with self-reported anxiety had similar radiation exposure, associated costs, and nearly identical (25.4% vs. 25.7%) ED recidivism to patients without reported anxiety.

CONCLUSIONS

Without prompting, 8% of patients self-identified "stress" or "anxiety" as the etiology for their chest pain. Most had low pretest probability, were over-investigated for ACS and PE, and not investigated for anxiety syndromes.

Role of physician perception of patient smile on pretest probability assessment for acute pulmonary embolism

BACKGROUND

Many clinicians use a global visual interpretation of patient appearance to decide if a patient looks sick or not. For patients with suspected acute pulmonary embolism (PE), we tested the relationship between visual appearance of a happy patient facial affect and probability of PE+ on CT pulmonary angiography (CTPA).

METHODS

Eligible patients were selected by usual care to undergo CTPA, the criterion standard for PE+ or PE-. Prior to CTPA result, trained study personnel obtained physician pretest probability using the gestalt method (visual analogue scale, 0%-100%), the Wells score (0-12) and physicians' impression of whether the patient smiled during the initial examination (smile+). Patients' faces were also video recorded and analysed with an automated neural network-based algorithm (Noldus FaceReader) for happy affect.

RESULTS

Of the 208 patients enrolled, 27 were PE+ and smile+ was more frequent in patients with PE+ than PE-, a finding confirmed by the Noldus. The diagnostic sensitivity and specificity of smile was low, and physicians overestimated presence of an alternative diagnosis more likely to PE with smile+ than smile- patients in patients with true PE. As a result, the area under the receiver operating characteristic curve (AUROC) was lower for the Wells score in smile+ patients. However, the physicians' mean gestalt estimate of PE did not differ with smile status, nor did smile status affect the AUROC for gestalt.

CONCLUSIONS

In patients with suspected PE, physician recollection of patients' smile+ was more common in PE+ patients, and was associated with a less accurate Wells score, primarily because physicians overestimated probability of alternative diagnosis. However, the overall diagnostic accuracy of physicians' gestalt did not differ with perceived smile status. These data suggest that the patients' smile had less effect on the numeric gestalt pretest probability assessment than on the binary decision about an alternative diagnosis.