Derivation of a clinical risk score for traumatic orbital fracture

A clinical decision aid for patients with suspected midfacial and mandibular fractures (the REDUCTION-I study): a prospective multicentre cohort study

Purpose

To assess physical examination findings related to maxillofacial trauma to identify patients at risk of midfacial and mandibular fractures and then to construct a clinical decision aid to rule out the presence of midfacial and mandibular fractures in emergency department patients.

Methods

We performed a prospective multicentre cohort study in four hospitals in the Netherlands, including consecutive patients with maxillofacial trauma. Each patient received a standardized physical examination consisting of 15 and 14 findings for midfacial and mandibular traumas, respectively. Consequently, clinical decision aids were constructed with the focus being on ruling out the presence of midfacial and mandibular fractures, and diagnostic accuracy was calculated.

Results

A total of 993 consecutive patients were identified of whom 766 and 280 patients were suspected of midfacial and mandibular fractures, respectively. Midfacial fractures were diagnosed in 339 patients (44.3%), whereas mandibular fractures were observed in 66 patients (23.6%). The decision aid for midfacial trauma consisting of peri-orbital hematoma, epistaxis, ocular movement limitation, infra-orbital nerve paresthesia, palpable step-off and tooth mobility or avulsion, produced a sensitivity of 89.7 (86.0–92.5), a specificity of 42.6 (38.0–47.4), and a negative predictive value of 83.9% (78.4–88.2). The decision aid for mandibular trauma consisting of the angular compression test, axial chin pressure test, objective malocclusion, tooth mobility or avulsion and the tongue blade bite test resulted in a sensitivity of 98.5 (91.9–99.7), a specificity of 34.6 (28.5–41.2), and a negative predictive value of 98.7% (92.8–99.8).

Conclusion

The constructed clinical decision aids for maxillofacial trauma may aid in stratifying patients suspected for midfacial and mandibular fractures to reduce unnecessary diagnostic imaging.

Clinical Trial Registration

The study was registered at ClinicalTrials.gov with the identifier NCT03314480.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00068-022-01968-1.

Diagnostic accuracy of physical examination findings for midfacial fractures: a systematic review and meta-analysis

Objectives

To conduct a systematic review and meta-analysis to assess the diagnostic accuracy of physical examination findings and related clinical decision aids for midfacial fractures in comparison to computed tomography and cone beam computed tomography.

Material and methods

A systematic review was performed by searching the MEDLINE, Cochrane, EMBASE, and CINAHL databases. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity, specificity, and diagnostic odds ratios with the corresponding 95% confidence intervals were calculated for each physical examination finding and reported clinical decision aids.

Results

After screening 2367 records, 12 studies were included. High risk of patient selection bias was detected in three studies (25%). Additionally, high concerns regarding applicability were found for the patient selection in five studies (41.7%), and for the reference standard in eleven studies (91.7%). Of the total 42 individual physical examination findings, only 31 were suitable for a meta-analysis. High specificity and low sensitivity were found for most findings. The pooled diagnostic odds ratio ranged from 1.07 to 11.38. Clinical decision aids were reported by 8 studies, but none were constructed specifically for midfacial fractures.

Conclusion

Based on the current available evidence, the absence of physical examination findings can successfully identify patients who do not have a midfacial fracture, but the presence of individual findings does not necessarily mean that the patient has a midfacial fracture. Although various clinical decision aids were presented, none focused on exclusively midfacial fractures.

Clinical relevance

The diagnostic accuracy of physical examination findings can be used to diagnose a midfacial fracture so as to reduce unnecessary imaging, health care costs, and exposure to ionizing radiation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00784-022-04423-y.

A clinical decision aid to discern patients without and with midfacial and mandibular fractures that require treatment (the REDUCTION-II study): a prospective multicentre cohort study

Purpose

To assess the diagnostic accuracy of physical examination findings and to construct clinical decision aids to discern emergency department patients without and with midfacial and mandibular fractures that require treatment.

Methods

A prospective multicentre cohort study was conducted in four hospitals in the Netherlands. Consecutive maxillofacial trauma patients were included whereupon each patient underwent a standardized physical examination consisting of 15 and 14 findings for midfacial and mandibular trauma, respectively. The primary outcome was the decision whether to treat during the emergency department stay or within 24 h of admission. The diagnostic accuracy was calculated for the individual physical examination findings and ensuing clinical decision aids with the focus being on detecting midfacial and mandibular fractures that require active treatment.

Results

A total of 766 midfacial trauma patients were identified of whom 339 (44.3%) had midfacial fractures. Of those, 74 (21.8%) required active treatment. A total of 280 mandibular trauma patients were identified of whom 66 (23.6%) had mandibular fractures. Of those, 37 (56.0%) required active treatment. The decision aid for midfacial trauma consisting of facial depression, epistaxis, ocular movement limitation, palpable step-off, objective malocclusion and tooth mobility or avulsion had a sensitivity of 97.3 (90.7–99.3), a specificity of 38.6 (35.0–42.3), and a negative predictive value of 99.3 (97.3–99.8). The decision aid for mandibular trauma consisting of mouth opening limitation, jaw movement pain, objective malocclusion and tooth mobility or avulsion resulted in a sensitivity of 100.0 (90.6–100.0), a specificity of 39.1 (33.2–45.4), and a negative predictive value of 100.0 (96.1–100.0).

Conclusion

The clinical decision aids successfully identified midfacial and mandibular trauma patients requiring active fracture treatment and so may be useful in preventing unnecessary radiological procedures in the future.

Trial Registration

The study was registered at ClinicalTrials.gov with the identifier NCT03314480.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00068-022-01892-4.

Clinical Decision Rule to Identify Orbital Wall Fracture Among Children: Retrospective Derivation and Validation Study

OBJECTIVES

Head and face injuries are leading causes of emergency department visits in children. There is yet no clinical decision rule on face CT such as pediatric head CT rules. The goal was to develop and validate a clinical decision rule for identifying orbital wall fractures in children with periorbital trauma in the emergency department.

METHODS

This was a retrospective derivation and validation study. Children younger than 18 years who underwent orbit CT after periorbital trauma were included between January 2011 and December 2013 in 3 emergency centers. Among 16 candidate clinical variables, 13 clinical signs and symptoms were selected as clinical predictors. For the fracture model, these clinical predictors were analyzed by 3-fold cross-validation. Diagnostic performance was assessed using the area under the receiver operating characteristic (AUROC) curve in both cohorts.

RESULTS

Four variables (orbital rim tenderness, periorbital ecchymosis, painful extraocular movement, and nausea/vomiting) had the best predictive model with the highest AUROC value. The AUROC values for fracture prediction were 0.793 (95% confidence interval, 0.741-0.844) and 0.809 (95% confidence interval, 0.742-0.877) in the derivation cohort and validation cohort, respectively. The sensitivity and negative predictive values were 96.4% and 93.4%, respectively, in the derivation cohort, and 97.8% and 98.1%, respectively, in the validation cohort. The sum of these scores ranged from 0 to 4. Patients with a sum of scores of 1 or higher showed significantly increased risk for fracture.

CONCLUSIONS

The 4-variable predictive model can be useful for finding clinically important orbital wall fractures in children.

Orbital Emphysema: A Case Report and Comprehensive Review of the Literature

PURPOSE

The objective of this study was to report a case of persistent and likely self-induced orbital emphysema (OE) following functional endoscopic sinus surgery with dislodgement of a previously placed orbital floor implant and to review the literature surrounding etiologies, pathophysiology, and management of OE.

METHODS

Case report and review of the literature.

RESULTS AND DISCUSSION

While blunt trauma resulting in disruption of the medial orbital wall is the most common cause of OE, there are an additional 25 underlying etiologies reported in the current literature. Pathophysiology of OE is somewhat dependent on underlying etiology but often involves a 1-way ball valve mechanism such that air may enter the orbit but not exit. When sufficient air enters the orbit, complications secondary to increased intraorbital pressure, including central retinal artery occlusion and compressive optic neuropathy, can occur. Mild cases of OE are typically observed, with most resolving within 7 to 10 days. Moderate cases are often managed by lateral canthotomy and cantholysis with possible needle decompression. Severe cases may require urgent surgical decompression. While the majority of cases of OE are benign and self-limited, there have been 4 reports in the literature documenting significant vision loss.

CONCLUSIONS

Although there is often a history of trauma in patients presenting with OE, many other underlying etiologies have been reported with several cases occurring spontaneously. As such, OE should be included on the differential for a patient presenting with a sudden onset of orbital signs.

Predicting orbital fractures in head injury: a preliminary study of clinical findings

Purpose

Patients presenting to emergency departments (EDs) following head injury often undergo computed tomography (CT) of the head to exclude traumatic brain injury. In many cases, this does not show the maxillofacial skeleton. A proportion of these patients also sustain facial fractures, and when fractures involve the orbits, CT imaging is useful in diagnosis and management; obtaining a second scan may cause delay, incur greater cost, and increase radiation dose. The aim of this preliminary study was to examine the value of signs and symptoms of orbital fractures in predicting a fracture on CT.

Methods

The clinical records of 47 patients who underwent CT of the face following facial trauma were retrospectively examined for the presence of signs and symptoms of orbital fractures. Sensitivity, specificity, negative predictive value (NPV) and positive predictive values (PPV) were then calculated for each sign and symptom for the presence of an orbital fracture on CT. We also described a clinical decision instrument and examined the predictive values of this.

Results

Change in the position of the globe, reduced visual acuity, subconjunctival haemorrhage and change in sensation in the maxillary division of the trigeminal nerve were the most specific signs and symptoms for orbital fracture. Our clinical decision instrument had 80.0% sensitivity, 75.0% specificity, 90.3% PPV and 56.3% NPV for predicting the presence of an orbital fracture on CT in this population.

Conclusions

Our results demonstrate that signs and symptoms of orbital fractures may be useful for predicting these injuries, and a decision instrument could be used in the ED to identify patients likely to benefit from extending the radiation field to include the orbits where CT of the head is already planned. This work is however exploratory; and further prospective validation is required before a robust instrument can be recommended for clinical use.

Automated outcome classification of emergency department computed tomography imaging reports

BACKGROUND

Reliably abstracting outcomes from free-text electronic health records remains a challenge. While automated classification of free text has been a popular medical informatics topic, performance validation using real-world clinical data has been limited. The two main approaches are linguistic (natural language processing [NLP]) and statistical (machine learning). The authors have developed a hybrid system for abstracting computed tomography (CT) reports for specified outcomes.

OBJECTIVES

The objective was to measure performance of a hybrid NLP and machine learning system for automated outcome classification of emergency department (ED) CT imaging reports. The hypothesis was that such a system is comparable to medical personnel doing the data abstraction.

METHODS

A secondary analysis was performed on a prior diagnostic imaging study on 3,710 blunt facial trauma victims. Staff radiologists dictated CT reports as free text, which were then deidentified. A trained data abstractor manually coded the reference standard outcome of acute orbital fracture, with a random subset double-coded for reliability. The data set was randomly split evenly into training and testing sets. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for certainty and temporal status. Findings were filtered for low certainty and past/future modifiers and then combined with the manual reference standard to generate decision tree classifiers using data mining tools Waikato Environment for Knowledge Analysis (WEKA) 3.7.5 and Salford Predictive Miner 6.6. Performance of decision tree classifiers was evaluated on the testing set with or without NLP processing.

RESULTS

The performance of machine learning alone was comparable to prior NLP studies (sensitivity = 0.92, specificity = 0.93, precision = 0.95, recall = 0.93, f-score = 0.94), and the combined use of NLP and machine learning showed further improvement (sensitivity = 0.93, specificity = 0.97, precision = 0.97, recall = 0.96, f-score = 0.97). This performance is similar to, or better than, that of medical personnel in previous studies.

CONCLUSIONS

A hybrid NLP and machine learning automated classification system shows promise in coding free-text electronic clinical data.