The injury severity score: an operations perspective.

BACKGROUND: The statistical evaluation of aggregation functions for trauma grades, such as the Injury Severity Score (ISS), is largely based on measurements of their Pearson product-moment correlation with mortality. However, correlation analysis makes assumptions about the nature of the involved random variables (cardinality) and their relationship (linearity) that may not be applicable to ordinal scores such as the ISS. Moreover, using correlation as a sole evaluation criterion neglects the dynamic properties of these aggregation functions scores. METHODS: We analyze the domain and ordinal properties of the ISS comparatively to arbitrary linear and cubic aggregation functions. Moreover, we investigate the axiomatic properties of the ISS as a multicriteria aggregation procedure. Finally, we use a queuing simulation with various empirical distributions of Abbreviated Injury Scale (AIS) grades reported in the literature, to evaluate the queuing performance of the three aggregation functions. RESULTS: We show that the assumptions required for the computation of Pearson's product-moment correlation coefficients are not applicable to the analysis of the association between the ISS and mortality. We suggest the use of Mutual Information, a information-theoretic statistic that is able to assess general dependence rather than a specialized, linear view based on curve-fitting. Using this metric on the same data set as the seminal study that introduced the ISS, we show that the sum of cubes conveys more information on mortality than the ISS. Moreover, we highlight some unintended, undesirable axiomatic properties of the ISS that can lead to bias in its use as a patient triage criterion. Lastly, our queuing simulation highlights the sensitivity of the queuing performance of different aggregation procedures to the underlying distribution of AIS grades among patients. CONCLUSIONS: Viewing the ISS, and other possible aggregation functions for multiple AIS scores, as mere operational indicators of the priority of care, rather than cardinal measures of the response of the human body to multiple injuries (as was conjectured in the seminal study introducing the ISS) offers a perspective for their construction and evaluation on more robust grounds than the correlation coefficient. In this regard, Mutual Information appears as a more appropriate measure for the study of the association between injury severity and mortality, and queuing simulations as an actionable way to adapt the choice of an aggregation function to the underlying distribution of AIS scores.

The impact of referral letter quality on timely access to specialised mental health care: a quantitative study of the reliability of patient triage.

BACKGROUND: Patients referred to specialised mental health care are usually triaged based on referral information provided by general practitioners. However, knowledge about this system's ability to ensure timely access to and equity in specialised mental health care is limited. We aimed to investigate to the degree to which patient triage, based on referral letter information, corresponds to triage based on a hospital specialist's consultation with the patient, and whether the degree of correspondence is affected by the quality of the referral letter. METHODS: We gathered information from three specialised mental health centres in Norway regarding patients that were referred and offered health care (N = 264). Data consisted of triage decisions for each patient (i.e., the hospital specialist's assessment of maximum acceptable waiting time), which were determined on the basis of a) referral information and b) meeting the patient. Referral letter quality was evaluated using the Quality of Referral information-Mental Health checklist. The reliability of priority setting and the impact of referral letter quality on this measure were investigated using descriptive analyses, binary logistic regression and Nadaraya-Watson kernel regression. RESULTS: In 143 (54%) cases, the triage decision based on referral information corresponded with the decision based on patient consultation. In 70 (27%) cases, the urgency of need for treatment was underestimated when based on referral information compared with that based on information from patient consultation. Referral letter quality could not explain the differences between the two triage decisions. However, when a cut-off value of 7 on the Quality of Referral information-Mental Health scale was used, low-quality letters were found more frequently among patients whose urgency of need was underestimated, compared with those whose need was overestimated. CONCLUSIONS: Deciding the urgency of patient need for specialised mental health care based on referral information is a reliable system in many situations. However, the possibility of under- and overestimation is present, implying risks to patient safety and inappropriate use of resources. Improving the content of referral letters does not appear to reduce this risk when the letters are of acceptable quality. TRIAL REGISTRATION: NCT01374035 .

Dental care during COVID-19 pandemic: Survey of experts' opinion.

OBJECTIVES: The current COVID-19 outbreak in conjunction with the need to provide safe dental treatments and the limited knowledge on the efficacy of protective measures has posed dentists into a challenging situation. Therefore, the present article aimed at collecting experiences and recommendations of frontline clinical experts on critical aspects of dental treatment provision during pandemic. MATERIAL & METHODS: From a total of 32 European countries, one leading academic expert in Oral and Maxillofacial Surgery or Oral Surgery per country was asked to participate in an anonymous online 10-item survey on COVID-19 covering the topics of safety of dental settings, personal protective equipment (PPE), and patient-related measures to reduce transmission risk. Data collection took place from April 12th to May 22nd, 2020. RESULTS: A total of 27 experts from different European countries completed the survey. The transmission risk of SARS-CoV-2 in dental settings for aerosol-generating procedures was considered high by all experts except two. For aerosol-free and aerosol-generating procedures, more than 80% of the experts recommended face protection and caps for every single treatment. For aerosol-generating procedures, additional measures (FFP2/FFP3 masks and gowns) were suggested by the vast majority of the experts. To reduce transmission risk, all experts recommended limiting aerosol-generating procedures and reducing the number of patients in waiting areas as well as hand hygiene for the patients. CONCLUSION: The limitation of aerosol-generating procedures along with the usage of adequate personal protection equipment was considered to be crucial to protect dental healthcare providers and patients, thus reducing the transmission risk of COVID-19.

Multisource Data Framework for Prehospital Emergency Triage in Real-Time IoMT-Based Telemedicine Systems.

BACKGROUND AND OBJECTIVE: The Internet of Medical Things (IoMT) has revolutionized telemedicine by enabling the remote monitoring and management of patient care. Nevertheless, the process of regeneration presents the difficulty of effectively prioritizing the information of emergency patients in light of the extensive amount of data generated by several integrated health care devices. The main goal of this study is to be improving the procedure of prioritizing emergency patients by implementing the Real-time Triage Optimization Framework (RTOF), an innovative method that utilizes diverse data from the Internet of Medical Things (IoMT). METHODS: The study's methodology utilized a variety of Internet of Medical Things (IoMT) data, such as sensor data and texts derived from electronic medical records. Tier 1 supplies sensor and textual data, and Tier 3 imports textual data from electronic medical records. We employed our methodologies to handle and examine data from a sample of 100,000 patients afflicted with hypertension and heart disease, employing artificial intelligence algorithms. We utilized five machine-learning algorithms to enhance the accuracy of triage. RESULTS: The RTOF approach has remarkable efficacy in a simulated telemedicine environment, with a triage accuracy rate of 98%. The Random Forest algorithm exhibited superior performance compared to the other approaches under scrutiny. The performance characteristics attained were an accuracy rate of 98%, a precision rate of 99%, a sensitivity rate of 98%, and a specificity rate of 100%. The findings show a significant improvement compared to the present triage methods. CONCLUSIONS: The efficiency of RTOF surpasses that of existing triage frameworks, showcasing its significant ability to enhance the quality and efficacy of telemedicine solutions. This work showcases substantial enhancements compared to existing triage approaches, while also providing a scalable approach to tackle hospital congestion and optimize resource allocation in real-time. The results of our study emphasize the capacity of RTOF to mitigate hospital overcrowding, expedite medical intervention, and enable the creation of adaptable telemedicine networks. This study highlights potential avenues for further investigation into the integration of the Internet of Medical Things (IoMT) with machine learning to develop cutting-edge medical technologies.

Retrospective chart analysis to determine the impact of a patient-facing digital risk stratification tool combined with a clinical screener for hereditary cancer genetic risk assessment triage in a community oncology clinic.

The purpose of this study was to evaluate the utility of adding a clinical screener to the patient-facing digital risk stratification tool triage process for the identification of patients eligible for a genetic risk assessment for hereditary cancer. Digital risk stratification entries were retrospectively reviewed to determine the overall number of patients eligible for genetic risk assessment. These were also analyzed to determine how many patients were re-contacted by the clinical screener, and how many of those recontacted patients met criteria after their personal and family history was revised by the clinical screener. There was an 89.9% digital risk stratification triage tool completion rate, with 22.6% requiring contact from the clinical screener. Of the 640 patients who completed the digital tool, 5.9% met criteria for testing after their personal and/or family history was revised by the clinical screener. Overall, 51.1% of patients met criteria for a genetic risk assessment. The addition of a clinical screener further increased identification of patients eligible for genetic risk assessment. About half of patients who met criteria after being contacted by the clinical screener met criteria based on their personal diagnosis of cancer alone. Incorporation of a clinical screener to the digital screening process may serve to reduce barriers to patient completion of the tool and increase rates of patient identification for cancer genetic services.

The Role of Point-of-Care Testing to Improve Acute Care and Health Care Services.

Health care is one of the most important services that need to be provided to any community. Many challenges exist in delivering proper and effective health services, including ensuring timely delivery, providing adequate care through effective management and achieving good outcomes. Point-of-care testing (POCT) plays a crucial role in delivering urgent and appropriate health services, especially in peripheral communities, emergency situations, disaster areas and overcrowded areas. We collected and reviewed secondary data about point-of-care testing from PubMed, Scopus and Google Scholar. Our findings emphasize that POCT provides fast care with minimal waiting time, avoids unnecessary investigations, aids in triage, and provides decision-makers with a clear understanding of the patient's condition to make informed decisions. We recommend point-of-care testing as a frontline investigation in emergency departments, intensive care units, peripheral hospitals, primary health care centers, disaster areas and field hospitals. Point-of-care testing can improve the quality of health services and ensure the provision of necessary health care.

Quality of referral of short children to the paediatric endocrinologist and impact of a fax communication system.

BACKGROUND/OBJECTIVES: In 2001, a chart review of children referred to the authors' endocrine clinic because of short stature revealed that many were referred with insufficient baseline data, had normal height velocity and were within genetic target height. Therefore, a two-way fax communication system was implemented between referring physicians and the authors' service before the first visit. Aspects that were assessed included whether this system increased the information accompanying the patient at referral, resulted in children with nonpathological shortness not being seen in the clinic, and was used differently by paediatricians and general practitioners. STUDY DESIGN: Between January and December 2006, 138 referrals for short stature, diagnosed with familial short stature, constitutional delay or idiopathic short stature, were audited (69 with and 69 without previous fax communication). Data collected included source of referral, clinical information provided, available growth measurements, and results from laboratory and imaging studies. RESULTS: Fax communication resulted in growth curves being provided more often (95.6% of cases versus 40.5% of cases without fax communication [P<0.001]) and more investigations being performed by the referring physician (median [range]: six [zero to 13] investigations versus one [zero to 11]; P<0.001), as well as a diagnosis of nonpathological short stature being given to 31 children based on the growth curve, laboratory and imaging results, without the children being seen in the endocrine clinic. Fax communication was also used more frequently by paediatricians (84%) than by general practitioners (15%). CONCLUSION: The fax communication system resulted in a more complete evaluation of referred patients by their physicians and reduced the number of unnecessary visits to the authors' specialty clinic while promoting medical education.

HISTORIQUE ET OBJECTIFS: En 2001, un examen des dossiers d'enfants aiguillés vers la clinique d'endocrinologie des auteurs en raison de leur petite taille a révélé que bon nombre des aiguillages ne s'accompagnaient pas de données de base suffisantes et que les patients aiguillés présentaient une croissance normale et une taille qui respectait leur cible génétique. C'est pourquoi un système de communication bidirectionnelle par télécopieur a été mis sur pied entre les médecins traitants et le service d'endocrinologie avant le premier rendez-vous. Les auteurs ont évalué si le système permettait d'avoir plus d'information au sujet du patient lors de l'aiguillage, s'il évitait que les patients dont la petite taille n'était pas d'origine pathologique soient vus à la clinique et s'il était utilisé de manière différente par les pédiatres et les omnipraticiens. MÉTHODOLOGIE: De janvier à décembre 2006, les auteurs ont évalué 138 aiguillages en raison d'une petite taille, diagnostiquée comme une petite taille familiale, un retard constitutionnel ou une petite taille idiopathique (69 avec et 69 sans communication antérieure par télécopieur). Les données colligées incluaient la source de l'aiguillage, l'information clinique fournie, les mesures de croissance transmises et les résultats des études de laboratoire et d'imagerie. RÉSULTATS: La communication par télécopieur a permis d'obtenir plus souvent les courbes de croissance (95,6 % des cas plutôt que 40,5 % [P<0,001]) et de faire faire plus d'examens par le médecin traitant (médiane [plage] : six [zéro à 13] examens au lieu d'un [zéro à 11]; P<0,001), ainsi que de poser un diagnostic de petite taille non pathologique chez 38 enfants d'après la courbe de croissance et les résultats de laboratoire et d'imagerie, sans qu'ils soient vus à la clinique d'endocrinologie. Par ailleurs, la communication par télécopieur était plus utilisée par les pédiatres (84 %) que par les omnipraticiens (15 %). CONCLUSION: Le système de communication par télécopieur a donné lieu à une évaluation plus complète des patients aiguillés par leur médecin et réduit le nombre de rendez-vous inutiles à la clinique spécialisée des auteurs, tout en favorisant la formation médicale.

Support Systems of Clinical Decisions in the Triage of the Emergency Department Using Artificial Intelligence: The Efficiency to Support Triage.

Purpose: In the Emergency Departments (ED) the current triage systems that are been implemented are based completely on medical education and the perception of each health professional who is in charge. On the other hand, cutting-edge technology, Artificial Intelligence (AI) can be incorporated into healthcare systems, supporting the healthcare professionals' decisions, and augmenting the performance of triage systems. The aim of the study is to investigate the efficiency of AI to support triage in ED. Patients­Methods: The study included 332 patients from whom 23 different variables related to their condition were collected. From the processing of patient data for input variables, it emerged that the average age was 56.4 ± 21.1 years and 50.6% were male. The waiting time had an average of 59.7 ± 56.3 minutes while 3.9% ± 0.1% entered the Intensive Care Unit (ICU). In addition, qualitative variables related to the patient's history and admission clinics were used. As target variables were taken the days of stay in the hospital, which were on average 1.8 ± 5.9, and the Emergency Severity Index (ESI) for which the following distribution applies: ESI: 1, patients: 2; ESI: 2, patients: 18; ESI: 3, patients: 197; ESI: 4, patients: 73; ESI: 5, patients: 42. Results: To create an automatic patient screening classifier, a neural network was developed, which was trained based on the data, so that it could predict each patient's ESI based on input variables.The classifier achieved an overall accuracy (F1 score) of 72.2% even though there was an imbalance in the classes. Conclusions: The creation and implementation of an AI model for the automatic prediction of ESI, highlighted the possibility of systems capable of supporting healthcare professionals in the decision-making process. The accuracy of the classifier has not reached satisfactory levels of certainty, however, the performance of similar models can increase sharply with the collection of more data.

Characteristics of a trauma population in an ambulance organisation in Sweden: results from an observational study.

BACKGROUND: Globally, injuries are a major health problem, and in Sweden, injuries are the second most common reason for ambulance dispatch. However, there is a knowledge gap regarding the epidemiology of injuries requiring assessment by emergency medical services (EMS) in Sweden. The aim of the present study was to describe the prehospital population with injuries that have been assessed and treated by EMS. METHODS: A randomly selected retrospective sample was collected from 1 January through 31 December 2019 in a region in southwestern Sweden. Data were collected from ambulance and hospital medical records. RESULTS: Among 153,724 primary assignments, 26,697 (17.4%) were caused by injuries. The study cohort consisted of 5,235 patients, of whom 50.5% were men, and the median age was 63 years. The most common cause of injury was low-energy fall (51.4%), and this was the cause in 77.8% of those aged > 63 years and in 26.7% of those aged ≤ 63 years. The injury mechanism was a motor vehicle in 8.0%, a motorcycle in 2.1% and a bicycle in 4.0%. The most common trauma location was the residential area (55.5% overall; 77.9% in the elderly and 34.0% in the younger group). In the prehospital setting, the most frequent clinical sign was a wound (33.2%), a closed fracture were seen in 18.9% and an open fracture in 1.0%. Pain was reported in 74.9% and 42.9% reported severe pain. Medication was given to 42.4% of patients before arrival in the hospital. The most frequent triage colour according to the RETTS was orange (46.7%), whereas only 4.4% were triaged red. Among all patients, 83.6% were transported to the hospital, and 27.8% received fracture treatment after hospital admission. The overall 30-day mortality rate was 3.4%. CONCLUSION: Among EMS assignments in southwestern Sweden, 17% were caused by injury equally distributed between women and men. More than half of these cases were caused by low-energy falls, and the most common trauma location was a residential area. The majority of the victims had pain upon arrival of the EMS, and a large proportion appeared to have severe pain.

Decreased readmission rates following use of modified trauma-specific frailty index in older trauma patients: A follow-up study.

INTRODUCTION: Post-discharge readmission rates using modified Trauma-Specific Frailty Index (mTSFI) compared to the Emergency Severity Index (ESI) are unknown. In our pilot study, we demonstrated that mTSFI usage more accurately triages older trauma patients. In the current study, we hypothesized that adult trauma patients triaged using mTSFI would have lower readmission rates at the 30-day interval post discharge. METHODS: Retrospective review of readmission rates for 96 trauma patients ≥ 50 years old was performed. The two study groups were categorized as mTSFI-concordant and ESI-concordant. Fisher's exact test was performed. RESULTS: Mean ages for ESI and mTSFI groups were 63.8 (SD 10.6) and 65.2 (SD 10.8) years. The 30-day readmission rate was 0% (0/32) in the mTSFI group vs 11% (7/64) in the ESI group (p = 0.104). CONCLUSIONS: Utilization of mTSFI for adult trauma patients may lead to lower 30-day readmission rates compared to using ESI, despite our sample sizes being too small to demonstrate a statistically significant difference.

Integrated medical resource consumption stratification in hospitalized patients: an Auto Triage Management model based on accurate risk, cost and length of stay prediction.

Triage management plays important roles in hospitalized patients for disease severity stratification and medical burden analysis. Although progression risks have been extensively researched for numbers of diseases, other crucial indicators that reflect patients' economic and time costs have not been systematically studied. To address the problems, we developed an automatic deep learning based Auto Triage Management (ATM) Framework capable of accurately modelling patients' disease progression risk and health economic evaluation. Based on them, we can first discover the relationship between disease progression and medical system cost, find potential features that can more precisely aid patient triage in resource allocation, and allow treatment plan searching that has cured patients. Applying ATM in COVID-19, we built a joint model to predict patients' risk, the total length of stay (LoS) and cost when at-admission, and remaining LoS and cost at a given hospitalized time point, with C-index 0.930 and 0.869 for risk prediction, mean absolute error (MAE) of 5.61 and 5.90 days for total LoS prediction in internal and external validation data.

Limited Additive Diagnostic Impact of Isolated Gastrointestinal Involvement for the Triage of Children with Suspected COVID-19.

The strategy for the selection of patients with a suspected SARS-CoV-2 infection is relevant for the organization of a children's hospital to provide optimal separation into COVID-19 and non-COVID-19 areas and pathways. We analyzed the proportion of children with COVID-19 presenting with gastrointestinal (GI) symptoms in 137 consecutive patients admitted between January 2020 and August 2021. GI symptoms were present as follows: diarrhea in 35 patients (26%), vomiting in 16 (12%), and both of them in five (3%); the combination of fever, respiratory symptoms, and diarrhea was observed in 16 patients (12%). Of the 676 adult patients with COVID-19 admitted to our hospital in the same time interval, 62 (9.2%) had diarrhea, 30 (4.4%) had vomiting, and 11 (1.6%) had nausea; only one patient, a 38-year-old male, presented with isolated GI symptoms at the diagnosis. Although diarrhea was observed in one quarter of cases, one-half of them had the complete triad of fever, respiratory syndrome, and diarrhea, and only five had isolated diarrhea, of which two were diagnosed with a Campylobacter infection. The occurrence of either respiratory symptoms or gastrointestinal symptoms in our patients was not related to the patient age, while younger children were more likely to have a fever. Of the 137 patients, 73 (53%) could be tested for their serum level of SARS-CoV-2 specific IgG antibodies. The observed titer ranged between 0 (n = 3) and 1729 BAU/mL (median, 425 BAU/mL). Of 137 consecutive patients with COVID-19 admitted to our referral children's hospital, only three presented with an isolated GI manifestation. It is interesting to note that this finding turned out to be fully in keeping with what was observed on adult patients with COVID-19 in our hospital. The additive diagnostic impact of gastrointestinal involvement for the triage of children with suspected COVID-19 appears limited.

Time to antibiotic administration and patient outcomes in community-acquired pneumonia: results from a prospective cohort study.

OBJECTIVES: Community-acquired pneumonia (CAP) is a frequently occurring disease linked to high mortality and morbidity. Previous studies indicated that the administration of antibiotics within 4 hrs of admission can improve key patient outcomes associated with CAP, such as mortality and time to clinical stability. However, the results have been heterogeneous and may not be applicable to all healthcare settings. Therefore, we designed a cohort study to estimate the impact of timely antibiotic administration on outcomes in patients admitted with CAP. METHODS: The impact of antibiotic administration within 4 hrs of admission and other covariates were estimated for 30-day mortality, stability within 72 hrs, 30-day readmission and time to discharge, using multivariable regression models. Sensitivity analyses were performed on a subset of patients with the most severe CAP and a propensity score matched cohort. RESULTS: In total, 2264 patients were included. Of these, 273 (12.1%) died within 30 days of admission, 1277 (56.4%) were alive and stable within 72 hrs and 334 (14.8%) were discharged alive and readmitted within 30 days. Median length of hospital stay was 5 days (interquartile range 3-8). In all models, the administration of antibiotics within 4 hrs of admission had no significant effect on the outcomes. The adjusted odds ratios (OR) derived from the multivariable models for 30-day mortality, stability within 72 hrs and 30-day readmission were 1.01 (95% confidence interval (CI) 0.76; 1.33), 0.88 (95% CI 0.74; 1.05) and 1.05 (95% CI 0.82; 1.34). The adjusted hazard ratio (HR) for time to discharge was 1.00 (95% CI 0.91; 1.10). DISCUSSION: A strict 4-hr threshold for antibiotic administration in all patients admitted with CAP is not reasonable. Instead, our results suggested that patients should be triaged and prioritized according to age, comorbidities, clinical condition and pneumonia severity.

Development and validation of a predictive model to determine the level of care in patients confirmed with COVID-19.

BACKGROUND: The COVID-19 pandemic has imposed significant challenges on hospital capacity. While mitigating unnecessary crowding in hospitals is favourable to reduce viral transmission, it is more important to prevent readmissions with impaired clinical status due to initially inappropriate level of care. A validated predictive tool to assist clinical decisions for patient triage and facilitate remote stratification is of critical importance. METHODS: We conducted a retrospective study in patients with confirmed COVID-19 stratified into two levels of care, namely ambulatory care and hospitalization. Data on socio-demographics, clinical symptoms, and comorbidities were collected during the first (N = 571) and second waves (N = 174) of the pandemic in Belgium (2 March to 6 December 2020). Univariate and multivariate logistic regressions were performed to build and validate the prediction model. RESULTS: Significant predictors of hospitalization were old age (OR = 1.08, 95%CI:1.06-1.10), male gender (OR = 4.41, 95%CI: 2.58-7.52), dyspnoea (OR 6.11, 95%CI: 3.58-10.45), dry cough (OR 2.89, 95%CI: 1.54-5.41), wet cough (OR 4.62, 95%CI: 1.93-11.06), hypertension (OR 2.20, 95%CI: 1.17-4.16) and renal failure (OR 5.39, 95%CI: 1.00-29.00). Rhinorrhea (OR 0.43, 95%CI: 0.24-0.79) and headache (OR 0.36, 95%CI: 0.20-0.65) were negatively associated with hospitalization. A receiver operating characteristic (ROC) curve was constructed and the area under the ROC curve was 0.931 (95% CI: 0.910-0.953) for the prediction model (first wave) and 0.895 (95% CI: 0.833-0.957) for the validated dataset (second wave). CONCLUSION: With a good discriminating power, the prediction model might identify patients who require ambulatory care or hospitalization and support clinical decisions by Emergency Department staff and general practitioners.

Triage and Allocation of Neurocritical Care Resources During the COVID 19 Pandemic - A National Survey.

Objective: In light of the ongoing COVID-19 pandemic and the associated hospitalization of an overwhelming number of ventilator-dependent patients, medical and/or ethical patient triage paradigms have become essential. While guidelines on the allocation of scarce resources do exist, such work within the subdisciplines of intensive care (e.g., neurocritical care) remains limited. Methods: A 16-item questionnaire was developed that sought to explore/quantify the expert opinions of German neurointensivists with regard to triage decisions. The anonymous survey was conducted via a web-based platform and in total, 96 members of the Initiative of German Neurointensive Trial Engagement (IGNITE)-study group were contacted via e-mail. The IGNITE consortium consists of an interdisciplinary panel of specialists with expertise in neuro-critical care (i.e., anesthetists, neurologists and neurosurgeons). Results: Fifty members of the IGNITE consortium responded to the questionnaire; in total the respondents were in charge of more than 500 Neuro ICU beds throughout Germany. Common determinants reported which affected triage decisions included known patient wishes (98%), the state of health before admission (96%), SOFA-score (85%) and patient age (69%). Interestingly, other principles of allocation, such as a treatment of "youngest first" (61%) and members of the healthcare sector (50%) were also noted. While these were the most accepted parameters affecting the triage of patients, a "first-come, first-served" principle appeared to be more accepted than a lottery for the allocation of ICU beds which contradicts much of what has been reported within the literature. The respondents also felt that at least one neurointensivist should serve on any interdisciplinary triage team. Conclusions: The data gathered in the context of this survey reveal the estimation/perception of triage algorithms among neurointensive care specialists facing COVID-19. Further, it is apparent that German neurointensivists strongly feel that they should be involved in any triage decisions at an institutional level given the unique resources needed to treat patients within the Neuro ICU.

Goldilocks, the Three Bears and Intensive Care Unit Utilization: Delivering Enough Intensive Care But Not Too Much. A Narrative Review.

Professional societies have developed recommendations for patient triage protocols, but wide variations in triage patterns for many acute conditions exist among hospitals in the United States. Differences in hospitals' triage patterns can be attributed to factors such as physician behavior, hospital policy and real-time conditions such as intensive care unit capacity. The patient safety concern is that patients evaluated for admission to the intensive care unit during times of high intensive care unit capacity may have adverse outcomes related to delays in care. Because standardization of a national triage policy is not feasible due to differing resources available at each hospital, local guidelines should prevail that take into account hospitals' local resources. The goal would be to better match intensive care unit bed supply with demand.

Recommendations for Dental Care during COVID-19 Pandemic.

Dental clinics were suspected to be a hotspot for nosocomial transmission of coronavirus disease 19 (COVID-19), yet there has been no clear recommendation about emergency dental care and appropriate personal protective equipment during pandemics. In this paper, we aim to summarize recommendations for (i) patient risk assessment, (ii) patient triage, and (iii) measures to prevent infection of health professionals and nosocomial transmission in dental clinics. The available evidence was collected by performing searches on PubMed, Embase, and Cochrane databases. We reviewed papers on COVID-19, severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), influenza, and related respiratory viral diseases. Legal and ethical frameworks, as well as international (e.g., World Health Organization (WHO)) and national (e.g., public health institutes, dental associations) guidelines were screened to summarize recommendations related to dental emergency care. To assess the patient risk, a questionnaire was developed to classify patients at unknown, high, and very high risk. Patient triage recommendations were summarized in a flow chart that graded the emergency level of treatments (i.e., urgent, as soon as possible, and postpone). Measures to prevent disease transmission based on current evidence were grouped for dental health professionals, dental clinics, and patients. The present recommendations may support health professionals implement preventative measures during the pandemic.

Ophthalmology Practice During the Coronavirus Disease 2019 Pandemic: The University of Pittsburgh Experience in Promoting Clinic Safety and Embracing Video Visits.

The coronavirus disease 2019 pandemic has led to widespread change as public health strategies for containment have emphasized social distancing and remaining at home. These policies have led to downscaled clinic volumes, cancellation of elective procedures, enhanced personal protective strategies in the clinic, and adoption of telemedicine encounters. We describe the evidence-based practical approach taken in our ophthalmology department to continue delivering eye care during the pandemic by rescheduling visits, enhancing clinic safety, and adopting virtual video encounters.

Unenhanced CT for clinical triage of elderly patients presenting to the emergency department with acute abdominal pain.

PURPOSE: The purpose of this study was to compare the diagnostic accuracy and inter-reader agreement of unenhanced computed tomography (CT) to those of contrast-enhanced CT for triage of patients older than 75years admitted to emergency department (ED) with acute abdominal pain (AAP). PATIENTS AND METHODS: Two hundred and eight consecutive patients presenting with AAP to the ED who underwent CT with unenhanced and contrast-enhanced images were retrospectively included. There were 90 men and 118 women with a mean age of 85.4±4.9 (SD) (range: 75-101.4years). Three readers reviewed unenhanced CT images first, and then unenhanced and contrast-enhanced CT images as a single set. Diagnostic accuracy was compared to the standard of reference defined as the final diagnosis obtained after complete clinico-biological and radiological evaluation. Correctness of the working diagnosis proposed by the ED physician was evaluated. Intra- and inter-reader agreements were calculated using the kappa test and interclass correlation. Subgroup analyses were performed for patients requiring only conservative management and for those requiring intervention. RESULTS: Diagnostic accuracy ranged from 64% (95% CI: 62-66%) to 68% (95% CI: 66-70%) for unenhanced CT, and from 68% (95% CI: 66-70%) to 71% (95% CI: 69-73%) for both unenhanced and contrast-enhanced CT. Contrast-enhanced CT did not significantly improve the diagnostic accuracy (P=0.973-0.979). CT corrected the working diagnosis proposed by the ED physician in 59.1% (range: 58.1-60.0%) and 61.2% (range: 57.6-65.5%) of patients before and after contrast injection (P>0.05). Intra-observer agreement was moderate to substantial (k=0.513-0.711). Inter-reader agreement was substantial for unenhanced (kappa=0.745-0.789) and combined unenhanced and contrast-enhanced CT (kappa=0.745-0.799). Results were similar in subgroup analyses. CONCLUSION: Unenhanced CT alone is accurate and associated with high degrees of inter-reader agreement for clinical triage of patients older than 75years with AAP in the emergency setting.

Diagnostic performance evaluation of a computer-aided simple triage system for coronary CT angiography in patients with intermediate risk for acute coronary syndrome.

RATIONALE AND OBJECTIVES: Given the significance of coronary artery disease as the most important socioeconomic health care problem in the Western World, the application of computer-aided simple triage (CAST) systems to this disease would be desirable. MATERIALS AND METHODS: In total, 93 patients with acute chest pain and an intermediate risk score for acute coronary syndrome underwent coronary computed tomography angiography (cCTA). Among those, 74 were of adequate image quality for automated analysis by a commercially available CAST system (COR Analyzer, RCADIA, Haifa, Israel). CAST findings were compared to human expert interpretation for the detection of significant stenosis (≥50%) in the left main, left anterior descending, circumflex, right coronary artery, or arterial branches. Further, one inexperienced observer evaluated all studies for significant stenoses alone and after 1 month guided by a CAST system as an initial read. RESULTS: Human expert interpretation identified 37/74 patients with stenosis ≥50%, whereas the CAST detected 45 patients. The CAST system demonstrated a sensitivity of 100%/79% and a specificity of 78%/89% on a per-patient/per-vessel level, respectively. With CAST, the inexperienced readers' per-vessel sensitivity and positive predictive values significantly improved (P = .011, P = .009) from 69% and 41% to 91% and 74%, respectively. CONCLUSIONS: The investigated CAST system for automatic stenosis detection can accurately identify patients with coronary artery stenosis ≥50% and may be of use as initial interpretation and triage of cCTA studies as well as a second reader for inexperienced readers, in absence of expert readers.