Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays

Image augmentations are quintessential for effective visual representation learning across self-supervised learning techniques. While augmentation strategies for natural imaging have been studied extensively, medical images are vastly different from their natural counterparts. Thus, it is unknown whether common augmentation strategies employed in Siamese representation learning generalize to medical images and to what extent. To address this challenge, in this study, we systematically assess the effect of various augmentations on the quality and robustness of the learned representations. We train and evaluate Siamese Networks for abnormality detection on chest X-Rays across three large datasets (MIMIC-CXR, CheXpert and VinDR-CXR). We investigate the efficacy of the learned representations through experiments involving linear probing, fine-tuning, zero-shot transfer, and data efficiency. Finally, we identify a set of augmentations that yield robust representations that generalize well to both out-of-distribution data and diseases, while outperforming supervised baselines using just zero-shot transfer and linear probes by up to 20%. Our code is available at https://github.com/StanfordMIMI/siaug.Comment: Equal contributions. Oral paper at MIDL 2023. Additional experiments in appendix in V2. Keywords: Data Augmentations, Self-Supervised Learning, Medical Imaging, Chest X-rays, Siamese Representation Learnin

Priority accuracy by dispatch centers and Emergency Medical Services professionals in trauma patients:a cohort study

PURPOSE: Priority-setting by dispatch centers and Emergency Medical Services professionals has a major impact on pre-hospital triage and times of trauma patients. Patients requiring specialized care benefit from expedited transport to higher-level trauma centers, while transportation of these patients to lower-level trauma centers is associated with higher mortality rates. This study aims to evaluate the accuracy of priority-setting by dispatch centers and Emergency Medical Services professionals. METHODS: This observational study included trauma patients transported from the scene of injury to a trauma center. Priority-setting was evaluated in terms of the proportion of patients requiring specialized trauma care assigned with the highest priority (i.e., sensitivity), undertriage, and overtriage. Patients in need of specialized care were defined by a composite resource-based endpoint. An Injury Severity Score ≥ 16 served as a secondary reference standard. RESULTS: Between January 2015 and December 2017, records of 114,459 trauma patients were collected, of which 3327 (2.9%) patients were in need of specialized care according to the primary reference standard. Dispatch centers and Emergency Medical Services professionals assigned 83.8% and 74.5% of these patients with the highest priority, respectively. Undertriage rates ranged between 22.7 and 65.5% in the different prioritization subgroups. There were differences between dispatch and transport priorities in 17.7% of the patients. CONCLUSION: The majority of patients that required specialized care were assigned with the highest priority by the dispatch centers and Emergency Medical Services professionals. Highly accurate priority criteria could improve the quality of pre-hospital triage. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00068-021-01685-1

Soluble urokinase-type plasminogen activator receptor levels in patients with burn injuries and inhalation trauma requiring mechanical ventilation: an observational cohort study

Soluble urokinase-type plasminogen activator receptor (suPAR) has been proposed as a biologic marker of fibrinolysis and inflammation. The aim of this study was to investigate the diagnostic and prognostic value of systemic and pulmonary levels of suPAR in burn patients with inhalation trauma who need mechanical ventilation. suPAR was measured in plasma and nondirected lung-lavage fluid of mechanically ventilated burn patients with inhalation trauma. The samples were obtained on the day of inhalation trauma and on alternate days thereafter until patients were completely weaned from the mechanical ventilator. Mechanically ventilated patients without burns and without pulmonary disease served as controls. Systemic levels of suPAR in burn patients with inhalation trauma were not different from those in control patients. On admission and follow up, pulmonary levels of suPAR in patients with inhalation trauma were significantly higher compared with controls. Pulmonary levels of suPAR highly correlated with pulmonary levels of interleukin 6, a marker of inflammation, and thrombin-antithrombin complexes, markers of coagulation, but not plasminogen activator activity, a marker of fibrinolysis. Systemic levels of suPAR were predictive of the duration of mechanical ventilation and length of intensive care unit (ICU) stay. Duration of mechanical ventilation and length of ICU stay were significantly longer in burn-injury patients with systemic suPAR levels > 9.5 ng/ml. Pulmonary levels of suPAR are elevated in burn patients with inhalation trauma, and they correlate with pulmonary inflammation and coagulation. Although pulmonary levels of suPAR may have diagnostic value in burn-injury patients, systemic levels of suPAR have prognostic valu

The impact of the Trauma Triage App on pre-hospital trauma triage: design and protocol of the stepped-wedge, cluster-randomized TESLA trial

Abstract Background Field triage of trauma patients is crucial to get the right patient to the right hospital within a particular time frame. Minimization of undertriage, overtriage, and interhospital transfer rates could substantially reduce mortality rates, life-long disabilities, and costs. Identification of patients in need of specialized trauma care is predominantly based on the judgment of Emergency Medical Services professionals and a pre-hospital triage protocol. The Trauma Triage App is a smartphone application that includes a prediction model to aid Emergency Medical Services professionals in the identification of patients in need of specialized trauma care. The aim of this trial is to assess the impact of this new digital approach to field triage on the primary endpoint undertriage. Methods The Trauma triage using Supervised Learning Algorithms (TESLA) trial is a stepped-wedge cluster-randomized controlled trial with eight clusters defined as Emergency Medical Services regions. These clusters are an integral part of five inclusive trauma regions. Injured patients, evaluated on-scene by an Emergency Medical Services professional, suspected of moderate to severe injuries, will be assessed for eligibility. This unidirectional crossover trial will start with a baseline period in which the default pre-hospital triage protocol is used, after which all clusters gradually implement the Trauma Triage App as an add-on to the existing triage protocol. The primary endpoint is undertriage on patient and cluster level and is defined as the transportation of a severely injured patient (Injury Severity Score ≥ 16) to a lower-level trauma center. Secondary endpoints include overtriage, hospital resource use, and a cost-utility analysis. Discussion The TESLA trial will assess the impact of the Trauma Triage App in clinical practice. This novel approach to field triage will give new and previously undiscovered insights into several isolated components of the diagnostic strategy to get the right trauma patient to the right hospital. The stepped-wedge design allows for within and between cluster comparisons. Trial registration Netherlands Trial Register, NTR7243. Registered 30 May 2018, https://www.trialregister.nl/trial/7038

The ARID1B spectrum in 143 patients: from nonsyndromic intellectual disability to Coffin–Siris syndrome

Purpose: Pathogenic variants in ARID1B are one of the most frequent causes of intellectual disability (ID) as determined by large-scale exome sequencing studies. Most studies published thus far describe clinically diagnosed Coffin–Siris patients (ARID1B-CSS) and it is unclear whether these data are representative for patients identified through sequencing of unbiased ID cohorts (ARID1B-ID). We therefore sought to determine genotypic and phenotypic differences between ARID1B-ID and ARID1B-CSS. In parallel, we investigated the effect of different methods of phenotype reporting. Methods: Clinicians entered clinical data in an extensive web-based survey. Results: 79 ARID1B-CSS and 64 ARID1B-ID patients were included. CSS-associated dysmorphic features, such as thick eyebrows, long eyelashes, thick alae nasi, long and/or broad philtrum, small nails and small or absent fifth distal phalanx and hypertrichosis, were observed significantly more often (p < 0.001) in ARID1B-CSS patients. No other significant differences were identified. Conclusion: There are only minor differences between ARID1B-ID and ARID1B-CSS patients. ARID1B-related disorders seem to consist of a spectrum, and patients should be managed similarly. We demonstrated that data collection methods without an explicit option to report the absence of a feature (such as most Human Phenotype Ontology-based methods) tended to underestimate gene-related features

Development and validation of a novel prediction model to identify patients in need of specialized trauma care during field triage : design and rationale of the GOAT study

Background: Adequate field triage of trauma patients is crucial to transport patients to the right hospital. Mistriage and subsequent interhospital transfers should be minimized to reduce avoidable mortality, life-long disabilities, and costs. Availability of a prehospital triage tool may help to identify patients in need of specialized trauma care and to determine the optimal transportation destination. Methods: The GOAT (Gradient Boosted Trauma Triage) study is a prospective, multi-site, cross-sectional diagnostic study. Patients transported by at least five ground Emergency Medical Services to any receiving hospital within the Netherlands are eligible for inclusion. The reference standards for the need of specialized trauma care are an Injury Severity Score ≥ 16 and early critical resource use, which will both be assessed by trauma registrars after the final diagnosis is made. Variable selection will be based on ease of use in practice and clinical expertise. A gradient boosting decision tree algorithm will be used to develop the prediction model. Model accuracy will be assessed in terms of discrimination (c-statistic) and calibration (intercept, slope, and plot) on individual participant's data from each participating cluster (i.e., Emergency Medical Service) through internal-external cross-validation. A reference model will be externally validated on each cluster as well. The resulting model statistics will be investigated, compared, and summarized through an individual participant's data meta-analysis. Discussion: The GOAT study protocol describes the development of a new prediction model for identifying patients in need of specialized trauma care. The aim is to attain acceptable undertriage rates and to minimize mortality rates and life-long disabilities

Accuracy of pediatric trauma field triage a systematic review

IMPORTANCE Field triage of pediatric patients with trauma is critical for transporting the right patient to the right hospital. Mortality and lifelong disabilities are potentially attributable to erroneously transporting a patient in need of specialized care to a lower-level trauma center. OBJECTIVE To quantify the accuracy of field triage and associated diagnostic protocols used to identify children in need of specialized trauma care. EVIDENCE REVIEW MEDLINE, Embase, PsycINFO, and Cochrane Register of Controlled Trials were searched from database inception to November 6, 2017, for studies describing the accuracy of diagnostic tests to identify children in need of specialized trauma care in a prehospital setting. Identified articles with a study population including patients not transported by emergency medical services were excluded. Quality assessment was performed using a modified version of the Quality Assessment of Diagnostic Accuracy Studies-2. FINDINGS After deduplication, 1430 relevant articles were assessed, a full-text review of 38 articles was conducted, and 5 of those articles were included. All studies were observational, published between 1996 and 2017, and conducted in the United States, and data collection was prospective in 1 study. Three different protocols were studied that analyzed a combined total of 1222 children in need of specialized trauma care. One protocol was specifically developed for a pediatric out-of-hospital cohort. The percentage of pediatric patients requiring specialized trauma care in each study varied between 2.6% (110 of 4197) and 54.7% (58 of 106). The sensitivity of the prehospital triage tools ranged from 49.1% to 87.3%, and the specificity ranged from 41.7% to 84.8%. No prehospital triage protocol alone complied with the international standard of 95% or greater sensitivity. Undertriage and overtriage rates, representative of the quality of the full diagnostic strategy to transport a patient to the right hospital, were not reported for inclusive trauma systems or emergency medical services regions. CONCLUSIONS AND RELEVANCE It is crucial to transport the right patient to the right hospital. Yet the quality of the full diagnostic strategy to determine the optimal receiving hospital is unknown. None of the investigated field triage protocols complied with current sensitivity targets. Improved efforts are needed to develop accurate child-specific tools to prevent undertriage and its potential life-threatening consequences

Compliance to prehospital trauma triage protocols worldwide: A systematic review

Background: Emergency medical services (EMS) providers must determine the injury severity on-scene, using a prehospital trauma triage protocol, and decide on the most appropriate hospital destination for the patient. Many severely injured patients are not transported to higher-level trauma centres. An accurate triage protocol is the base of prehospital trauma triage; however, ultimately the quality is dependent on the destination decision by the EMS provider. The aim of this systematic review is to describe compliance to triage protocols and evaluate compliance to the different categories of triage protocols. Methods: An extensive search of MEDLINE/Pubmed, Embase, CINAHL and Cochrane library was performed to identify all studies, published before May 2018, describing compliance to triage protocols in a trauma system. The search terms were a combination of synonyms for ‘compliance,’ ‘trauma,’ and ‘triage’. Results: After selection, 11 articles were included. The studies showed a variety in compliance rates, ranging from 21% to 93% for triage protocols, and 41% to 94% for the different categories. The compliance rate was highest for the criterion: penetrating injury. The category of the protocol with the lowest compliance rate was: vital signs. Compliance rates were lower for elderly patients, compared to adults under the age of 55. The methodological quality of most studies was poor. One study with good methodological quality showed that the triage protocol identified only a minority of severely injured patients, but many of whom were transported to higher-level trauma centres. Conclusions: The compliance rate ranged from 21% to 94%. Prehospital trauma triage effectiveness could be increased with an accurate triage protocol and improved compliance rates. EMS provider judgment could lower the undertriage rate, especially for severely injured patients meeting none of the criteria. Future research should focus on the improvement of triage protocols and the compliance rate