Severity Classification System Research Articles

Prevalence and risk factors for age-related macular degeneration in a population-based cohort study of older adults in Northern Ireland using multimodal imaging: NICOLA Study

PurposeTo report prevalence and risk factor associations for age-related macular degeneration (AMD) and AMD features from multimodal retinal grading in a multidisciplinary longitudinal population-based study of aging in Northern Ireland.Study...

Management of acute pancreatitis in the Emergency Department

Background: Heterogeneity in clinical manifestations and outcome of pancreatitis constitutes an obstacle for the creation of a common treatment algorithm by the scientific community.
 Aim: The aim of the present study was to systematically review the management of cases of acute pancreatitis in Emergency Department (ED) and her correlation with outcome.
 Methods: Search the database Pubmed and were included observational studies and randomized trials in adults in English.
 Results: The search yielded 13 studies. Of these, 3 concerned the diagnostic approach of the disease in ED and concluded that lipase is the most reliable test in diagnosis, while computed tomography of the abdomen is not recommended as a routine examination. 5 out of 13 studies analyzed the usefulness of disease severity classification systems, with the BISAP and HASP score appearing as reliable as the APACHE II and RANSON score, but having an advantage in rapid patient evaluation. The last 5, studied the need for immediate therapeutic / invasive method, with the time of surgery from the arrival at the ED being decisive as it affects the outcome of the disease. It is generally seen that the early invasive method is gaining ground in the treatment of the disease.
 Conclusion: The main goal is to predict the most severe forms of the disease in order to receive the right (invasive or not) treatment to improve survival and quality of life.

Which model is superior in predicting ICU survival: artificial intelligence versus conventional approaches

BackgroundA disease severity classification system is widely used to predict the survival of patients admitted to the intensive care unit with different diagnoses. In the present study, conventional severity classification systems were compared with artificial intelligence predictive models (Artificial Neural Network and Decision Tree) in terms of the prediction of the survival rate of the patients admitted to the intensive care unit.MethodsThis retrospective cohort study was performed on the data of the patients admitted to the ICU of Ghaemshahr’s Razi Teaching Care Center from March 20th, 2017, to September 22nd, 2019. The required data for calculating conventional severity classification models (SOFA, SAPS II, APACHE II, and APACHE IV) were collected from the patients’ medical records. Subsequently, the score of each model was calculated. Artificial intelligence predictive models (Artificial Neural Network and Decision Tree) were developed in the next step. Lastly, the performance of each model in predicting the survival of the patients admitted to the intensive care unit was evaluated using the criteria of sensitivity, specificity, accuracy, F-measure, and area under the ROC curve. Also, each model was validated externally. The R program, version 4.1, was used to create the artificial intelligence models, and SPSS Statistics Software, version 21, was utilized to perform statistical analysis.ResultsThe area under the ROC curve of SOFA, SAPS II, APACHE II, APACHE IV, multilayer perceptron artificial neural network, and CART decision tree were 76.0, 77.1, 80.3, 78.5, 84.1, and 80.0, respectively.ConclusionThe results showed that although the APACHE II model had better results than other conventional models in predicting the survival rate of the patients admitted to the intensive care unit, the other conventional models provided acceptable results too. Moreover, the findings showed that the artificial neural network model had the best performance among all the studied models, indicating the discrimination power of this model in predicting patient survival compared to the other models.

Evaluation of the Public Health Emergency Response to the COVID-19 Pandemic in Daegu, Korea During the First Half of 2020.

ObjectivesThis study evaluated the response in Daegu, Korea to the first wave of the coronavirus disease 2019 (COVID-19) pandemic according to a public health emergency response model.MethodsAfter an examination of the official data reported by the city of Daegu and the Korea Centers for Disease Control and Prevention, as well as a literature review and advisory meetings, we chose a response model. Daegu’s responses were organized into 4 phases and evaluated by applying the response model.ResultsIn phase 1, efforts were made to block further transmission of the virus through preemptive testing of a religious group. In phase 2, efforts were concentrated on responding to mass infections in high-risk facilities. Phase 3 involved a transition from a high-intensity social distancing campaign to a citizen participation–based quarantine system. The evaluation using the response model revealed insufficient systematic preparation for a medical surge. In addition, an incorporated health-related management system and protection measures for responders were absent. Nevertheless, the city encouraged the participation of private hospitals and developed a severity classification system. Citizens also played active roles in the pandemic response by practicing social distancing.ConclusionsThis study employed the response model to evaluate the early response in Daegu to the COVID-19 pandemic and revealed areas in need of improvement or maintenance. Based on the study results, creation of a systematic model is necessary to prepare for and respond to future public health emergencies like the COVID-19 pandemic.

Development and validation of a multivariable mortality risk prediction model for COPD in primary care

Risk stratification of chronic obstructive pulmonary disease (COPD) patients is important to enable targeted management. Existing disease severity classification systems, such as GOLD staging, do not take co-morbidities into account despite their high prevalence in COPD patients. We sought to develop and validate a prognostic model to predict 10-year mortality in patients with diagnosed COPD. We constructed a longitudinal cohort of 37,485 COPD patients (149,196 person-years) from a UK-wide primary care database. The risk factors included in the model pertained to demographic and behavioural characteristics, co-morbidities, and COPD severity. The outcome of interest was all-cause mortality. We fitted an extended Cox-regression model to estimate hazard ratios (HR) with 95% confidence intervals (CI), used machine learning-based data modelling approaches including k-fold cross-validation to validate the prognostic model, and assessed model fitting and discrimination. The inter-quartile ranges of the three metrics on the validation set suggested good performance: 0.90–1.06 for model fit, 0.80–0.83 for Harrel’s c-index, and 0.40–0.46 for Royston and Saurebrei’s R_D^2 with a strong overlap of these metrics on the training dataset. According to the validated prognostic model, the two most important risk factors of mortality were heart failure (HR 1.92; 95% CI 1.87–1.96) and current smoking (HR 1.68; 95% CI 1.66–1.71). We have developed and validated a national, population-based prognostic model to predict 10-year mortality of patients diagnosed with COPD. This model could be used to detect high-risk patients and modify risk factors such as optimising heart failure management and offering effective smoking cessation interventions.

How Can We Quantify and Compare Harm in Surgical Trials?

To describe methods that can be used to quantify and compare harm caused by surgical interventions in ophthalmology trials. Perspective study. A published landmark glaucoma trial was used as an exemplar. A consensus-derived classification system of severity of complications was applied to published data of the Tube Versus Trabeculectomy glaucoma trial. The severity grade of each complication was multiplied to the number of patients who incurred that complication to estimate a total harm score for each intervention. Graphical tools were also used to display the differences in complications between trial arms. A review of literature on best practice for reporting harm data was also conducted. Analyzing treatment harm is challenging with the relatively small number of events and sample sizes used in randomized controlled trials. However, quantification and graphical representation of harm after surgery is possible. Reframing the research question to one for detecting signals of adverse reactions and use of Bayesian analyses can be useful. Analysis of harm data in clinical trials needs further attention. A severity classification system and a total harm score can be used to quantify harm after glaucoma surgery. Graphical tools can also help interpret complication data.

COVID-19 Among Lung Transplant Recipients: A Single Center Study

BackgroundWhen COVID-19 became a pandemic, it was difficult to predict how it would affect lung transplant recipients. The aim of this study was to assess the mortality, influence on graft function as well as attitude toward SARS-CoV-2 vaccination among lung transplant recipients from a single center.MethodsWe analyzed medical data pertaining to 124 recipients who received lung transplants between 2008-2021 from a single center and original questionnaire on the COVID-19 severity classification system and the patients’ attitude toward SARS-CoV-2 vaccination. Graft function was assessed by spirometry and a 6-minute walk test (6MWT), at least at the first postCOVID-19 visit.ResultsAmong 29 patients who were confirmed to have COVID-19, 6 people died during or directly after contracting this infectious disease. The significant decrease in spirometry and distance in a 6MWT has been rarely observed in COVID-19 survivors. After vaccination ( n=107 patients) , most patients reported mild symptoms with slight pain and discomfort at the injection site being the most common (51.4%). 67.7% of all studiedpatients did not have any fears regarding the vaccination. Others reported being significantly worried about its effects (19.4% agreed to receive a vaccination anyway and 12.9% refused to be vaccinated).ConclusionsCOVID-19 may present significant mortality among lung transplant recipients. The short-term safety and outcomes of vaccinations among these patients seemed encouraging. We are aware of the small study group limitations and hope to research this issue further.

Assessing, grading, and reporting intraoperative adverse events during and after surgery.

Intraoperative adverse events (iAEs) are under-reported, have poorly standardized nomenclature, and are plagued by barriers to reporting and cultural acceptance. Not surprisingly, although surgeons are willing to report iAEs, they often under-report these events, especially those of lower severity, owing to perceived clinical insignificance1. Attempts to overcome reporting deficits with surgical black-box systems, otherwise known as medical data recorders, have continued to receive pushback despite the potential benefits for quality improvement2,3. Until these systems gain further traction, integration of iAE reporting into the sign-out portion of the WHO safety checklist might be a useful aide-memoire4,5. Barriers to reporting, such as institutional, emotional, and litigious concerns, remain challenging to overcome6. Further, the intransigent blame culture continues to detract from a universally shared goal of improved patient safety6. The, regrettably, common lack of institutional support for litigation concerns, and an absence of clear definitions of what should be reported and how to report, might be surmountable with improved awareness of available resources. There are several iAE classification systems available, including, but not limited to: Modified Satava, the iAE severity classification system (Massachusetts General Hospital), the European Association of Surgical Endoscopy classification7,8, intraoperative adverse incident classification (European Association of Urology)9, and the classification of intraoperative adverse events (ClassIntra®)10. These systems are universally available and can be used to clearly delineate what constitutes an iAE. However, with the exception of ClassIntra®, many of these systems have yet to be validated and are known to have high inter-rater variability10–13. In the absence of a single best system, a vital first step is to record and grade iAEs prospectively, regardless of which system is chosen, so that we can move on to understanding the real-world implications of iAEs. Although these classification systems are useful for grading iAEs, they stop short of providing guidelines for reporting in publications or daily practice.

A universal severity classification for natural disasters

The magnitude of a disaster’s severity cannot be easily assessed because there is no global method that provides real magnitudes of natural disaster severity levels. Therefore, a new universal severity classification scheme for natural disasters is developed and is supported by data. This universal system looks at the severity of disasters based on the most influential impact factor and gives a rating from zero to ten: Zero indicates no impact and ten is a worldwide devastation. This universal system is for all types of natural disasters, from lightning strikes to super-volcanic eruptions and everything in between, that occur anywhere in the world at any time. This novel universal severity classification system measures, describes, compares, rates, ranks, and categorizes impacts of disasters quantitatively and qualitatively. The severity index is useful to diverse stakeholder groups, including policy makers, governments, responders, and civilians, by providing clear definitions that help convey the severity levels or severity potential of a disaster. Therefore, this universal system is expected to avoid inconsistencies and to connect severity metrics to generate a clear perception of the degree of an emergency; the system is also expected to improve mutual communication among stakeholder groups. Consequently, the proposed universal system will generate a common communication platform and improve understanding of disaster risk, which aligns with the priority of the Sendai Framework for Disaster Risk Reduction 2015–2030. This research was completed prior to COVID-19, but the pandemic is briefly addressed in the discussion section.

"You Say Severe, I Say Mild": Toward an Empirical Classification of Dysarthria Severity.

The main purpose of this study was to create an empirical classification system for speech severity in patients with dysarthria secondary to amyotrophic lateral sclerosis (ALS) by exploring the reliability and validity of speech-language pathologists' (SLPs') ratings of dysarthric speech. Ten SLPs listened to speech samples from 52 speakers with ALS and 20 healthy control speakers. SLPs were asked to rate the speech severity of the speakers using five response options: normal, mild, moderate, severe, and profound. Four severity-surrogate measures were also calculated: SLPs transcribed the speech samples for the calculation of speech intelligibility and rated the effort it took to understand the speakers on a visual analog scale. In addition, speaking rate and intelligible speaking rate were calculated for each speaker. Intrarater and interrater reliability were calculated for each measure. We explored the validity of clinician-based severity ratings by comparing them to the severity-surrogate measures. Receiver operating characteristic (ROC) curves were conducted to create optimal cutoff points for defining dysarthria severity categories. Intrarater and interrater reliability for the clinician-based severity ratings were excellent and were comparable to reliability for the severity-surrogate measures explored. Clinician severity ratings were strongly associated with all severity-surrogate measures, suggesting strong construct validity. We also provided a range of values for each severity-surrogate measure within each severity category based on the cutoff points obtained from the ROC analyses. Clinician severity ratings of dysarthric speech are reliable and valid. We discuss the underlying challenges that arise when selecting a stratification measure and offer recommendations for a classification scheme when stratifying patients and research participants into speech severity categories.

388 TREATMENT OF ANASTOMOTIC LEAKAGE AFTER ESOPHAGECTOMY (TENTACLE—ESOPHAGUS) STUDY: FACTORS ASSOCIATED WITH ANASTOMOTIC LEAKAGE SEVERITY

Abstract Anastomotic leakage is a common and severe complication after esophagectomy. It is largely unknown which characteristics contribute to leakage severity. We aimed to investigate which factors are associated with leakage severity and to create an anastomotic leakage severity classification. Methods The TENTACLE—Esophagus is a multinational retrospective cohort study in which patients with anastomotic leakage after esophagectomy in the period 2011-2019 were included. Detailed data regarding casemix (e.g. age, sex, physical condition, comorbidity, tumor characteristics), surgical procedure (e.g. McKeown, Ivor Lewis, Orringer, anastomotic technique, omental wrap, pleural flap), leakage characteristics (e.g. contamination, drainage at leakage diagnosis, leak circumference) and treatment were collected. The primary outcome is 90-day mortality. Regression analysis will be used to analyze which leakage characteristics are associated with 90-day mortality and to compose an evidence-based anastomotic leakage severity score. The study protocol is accessible at www.tentaclestudy.com. Results Detailed data of 1407 patients with anastomotic leakage from 70 centers in 20 countries were collected. Anastomotic leakage occurred 0-43 days after surgery and 90-day mortality rate was 11.1%. The TENTACLE—Esophagus study data is currently being validated and it is awaiting full analysis. The results and the evidence based anastomotic leakage severity classification system will be ready for presentation at the ISDE meeting. Conclusion This is the largest study that investigates which factors contribute to anastomotic leakage severity after esophagectomy. The evidence-based anastomotic leakage severity classification system can be used by clinicians to grade severity of a given leak and might aid clinicians in choosing the most appropriate treatment.

Mitral annular calcification and valvular dysfunction: multimodality imaging evaluation, grading, and management.

Mitral annular calcification (MAC) refers to calcium deposition in the fibrous skeleton of the mitral valve. It has many cardiovascular associations, including mitral valve dysfunction, elevated cardiovascular risk, arrhythmias, and endocarditis. Echocardiography conventionally is the first-line imaging modality for anatomic assessment, and evaluation of mitral valve function. Cardiac computed tomography (CT) has demonstrated importance as an imaging modality for the evaluation and planning of related procedures. It also holds promise in quantitative grading of MAC. Currently, there is no universally accepted definition or classification system of MAC severity. We review the multimodality imaging evaluation of MAC and associated valvular dysfunction and propose a novel classification system based on qualitative and quantitative measurements derived from echocardiography and cardiac CT.

Sistema de clasificación de severidad neurológica (sistema CSN) en adultos con TEC, Hospital Cayetano Heredia, Lima, Perú, 2020. Estudio preliminar

Objectives: Traumatic Brain Injury (TBI) is the disruption of brain function and architecture. The Glasgow Coma Scale (GCS) is the most widely used TBI severity classification; however, it assesses the functional status of the brain resulting from highly heterogeneous lesions and has little accuracy. The Neurological Severity Classification System (NSC System), a clinical-tomographic instrument designed to overcome lesion heterogeneity, assesses brain function and structure in determining the severity of BTI. Methods: Observational, prospective, and cross-sectional study in adults with BTI from the emergency service of the Cayetano Heredia Hospital, April - August 2020. It included patients aged 18 years or older with acute BTI. The NSC system was compared with the GCS in the BTI classification. Results: Of 29 patients, 82.76% were male and 82.76% were between 18 and 64 years old. The severity of the TBI through the NSC System was very mild 6.70%, mild 17.24%, moderate 51.72%, severe 17.24%, and critical 6.70%. There was an association between the NSC System and the Rotterdam Computed Tomographic Score (RCTS) (p = 0.005), a moderate positive correlation of the NSC System with the RCTS (Rho 0.6773, p = 0.0001), an association between the NSC System and the indication for neurosurgical intervention (p = 0.002), as well as high sensitivity-specificity in the distinction of severity categories with the NSC System, and lower GCS performance. Conclusions: The NSC clinical-tomographic system improves the determination of the severity of BTI in comparison with GCS and provides an excellent relationship with the indication for neurosurgical intervention. Keywords: Brain Injuries, Traumatic, Brain, Glasgow Coma Scale, Functional Status (Source: MeSH NLM)

The impact of idiopathic pulmonary fibrosis on health state utility values: evidence from Australia.

Idiopathic pulmonary fibrosis (IPF) is a progressive and universally fatal lung disease, characterised by increasing fibrosis of the lung parenchyma. In this study, we aimed to quantify the health state utility values (HSUVs) for Australians with IPF and to identify the factors affecting these HSUVs. Participants of the Australian IPF Registry (AIPFR), with data on EuroQoL five dimension-five level (EQ-5D-5L) profiles were included. Pulmonary function tests (PFTs) were used to assess disease severity using three IPF -based classification systems. Stepwise multivariable linear regression models assessed the relationship between HSUVs and important demographic and clinical parameters.Query RESULTS: A total of 155 participants provided data for the analysis of HSUVs. For our base case, HSUVs ranged from -0.57 to 1.00. Mean HSUVs for all participants was 0.65 (95% CI 0.61-0.70). In general, HSUVs decreased with increasing disease severity under all disease severity classification systems. Multivariable linear regression demonstrated a negative association between HSUVs, disease severity and having more than 2 comorbidities. Our study has shown that EQ-5D-5L has exhibited discriminatory sensitivity for the study population. We have demonstrated that disease severity and having more than two comorbidities was associated with lower HSUVs in Australians with IPF. Our findings support early diagnosis and appropriate evidence-based treatment to slow or prevent IPF progression; and identification and treatment of associated comorbidities to potentially improve health-related quality of life in people with IPF.

Mortality in acute pancreatitis with persistent organ failure is determined by the number, type, and sequence of organ systems affected

BackgroundPersistent organ failure (POF) is the strongest determinant of mortality in acute pancreatitis (AP). There is a paucity of data regarding the impact of different POF attributes on mortality and the role of different characteristics of systemic inflammatory response syndrome (SIRS) in the risk of developing POF.ObjectiveWe aimed to assess the association of POF dynamic features with mortality and SIRS characteristics with POF.MethodsWe studied 1544 AP subjects prospectively enrolled at 22 international centers (APPRENTICE consortium). First, we estimated the association of onset, duration, and maximal score of SIRS with POF. Then, we evaluated the risk of mortality based on POF onset, duration, number, type, and sequence of organs affected. Analyses were adjusted for potential confounders.Results58% had SIRS, 11% developed POF, and 2.5% died. Early SIRS, persistent SIRS, and maximal SIRS score ≥ 3 were independently associated with higher risk of POF (p < 0.05). Mortality risk in POF was higher with two (33%, odds ratio [OR] = 10.8, 3.3–34.9) and three (48%, OR = 20.2, 5.9–68.6) organs failing, in comparison to single POF (4%). In subjects with multiple POF, mortality was higher when the cardiovascular and respiratory systems failed first or concurrently as compared to when the renal system failed first or concurrently with other organ (p < 0.05). In multivariate regression model, the number and sequence of organs affected in POF were associated with mortality (p < 0.05). Onset and duration of POF had no impact mortality.ConclusionIn AP patients with POF, the risk of mortality is influenced by the number, type, and sequence of organs affected. These results are useful for future revisions of AP severity classification systems.

Low acuity paediatric emergency visits under single-payer universal health insurance in Taiwan, 2000–2015: a population-based repeated cross-sectional design

ObjectivesEmergency services utilisation is a critical policy concern. The paediatric population is the main user of emergency department (ED) services, and the main contributor to low acuity (LA) ED visits....

Association of Optical Coherence Tomography With Longitudinal Neurodegeneration in Veterans With Chronic Mild Traumatic Brain Injury

Mild traumatic brain injury (TBI) may predispose individuals to progressive neurodegeneration. To identify evidence of neurodegeneration through longitudinal evaluation of changes in retinal layer thickness using optical coherence tomography in veterans with a history of mild TBI. This longitudinal cohort study evaluated veterans who were receiving services at the Minneapolis Veterans Affairs Health Care System. Symptomatic or mild TBI was diagnosed according to the Mayo TBI Severity Classification System. Participants in the age-matched control group had no history of TBI. Participants with any history or evidence of retinal or optic nerve disease that could affect retinal thickness were excluded. Data analysis was performed from July 2019 to February 2020. The presence and severity of mild TBI were determined through consensus review of self-report responses during the Minnesota Blast Exposure Screening Tool semistructured interview. Change over time of retinal nerve fiber layer (RNFL) thickness. A total of 139 veterans (117 men [84%]; mean [SD] age, 49.9 [11.1] years) were included in the study, 69 in the TBI group and 70 in the control group. Veterans with mild TBI showed significantly greater RNFL thinning compared with controls (mean [SE] RNFL slope, -1.47 [0.24] μm/y vs -0.31 [0.32] μm/y; F1,122 = 8.42; P = .004; Cohen d = 0.52). Functionally, veterans with mild TBI showed greater declines in visual field mean deviation (mean [SE] slope, -0.09 [0.14] dB/y vs 0.46 [0.23] dB/y; F1,122 = 4.08; P = .046; Cohen d = 0.36) and pattern standard deviation (mean [SE] slope, 0.09 [0.06] dB/y vs -0.10 [0.07] dB/y; F1,122 = 4.78; P = .03; Cohen d = 0.39) and high spatial frequency (12 cycles/degree) contrast sensitivity compared with controls. Cognitively, there was a significantly greater decrease in the number of errors over time during the Groton Maze Learning Test (GMLT) in controls compared with veterans with mild TBI (mean [SE] slope, -9.30 [1.48] errors/y vs -5.23 [1.24] errors/y; F1,127 = 4.43; P = .04; Cohen d = 0.37). RNFL tissue loss was significantly correlated with both worsening performance on the GMLT over time (Spearman ρ = -0.20; P = .03) and mild TBI severity (Spearman ρ = -0.25; P = .006). The more severe the mild TBI (larger Minnesota Blast Exposure Screening Tool severity score), the faster the reduction in RNFL thickness (ie, the more negative the slope) across time. This cohort study found longitudinal evidence for significant, progressive neural degeneration over time in veterans with mild TBI, as indicated by greater RNFL tissue loss in patients with mild TBI vs controls, as well as measures of function. These results suggest that these longitudinal measures may be useful biomarkers of neurodegeneration. Changes in this biomarker may provide early detection of subsequent cognitive and functional deficits that may impact veterans' independence and need for care.

The Subaxial Cervical AO Spine Injury Score.

Study Design:Global cross-sectional survey.Objective:To develop an injury score for the AO Spine Subaxial Cervical Spine Injury Classification System.Methods:Respondents numerically graded each variable within the classification system for severity. Based on the results, and with input from the AO Spine Trauma Knowledge Forum, the Subaxial Cervical AO Spine Injury Score was developed.Results:An A0 injury was assigned an injury score of 0, A1 a score of 1, and A2 a score of 2. Given the significant increase in severity, A3 was given a score of 4. Based on equal severity assessment, A4 and B1 were both assigned a score of 5. B2 and B3 injuries were assigned a score of 6. Unstable C-type injuries were given a score of 7. Stable F1 injuries were assigned a score of 2, with a 2-point increase for F2 injuries. Likewise, F3 injuries received a score of 5, whereas more unstable F4 injuries a score of 7. Neurologic status severity rating scores increased stepwise, with scores of 0 for N0, 1 for N1, and 2 for N2. Consistent with the Thoracolumbar AO Spine Injury Score, N3 (incomplete) and N4 (complete) injuries were given a score of 4. Finally, case-specific modifiers M1 (PLC injury) received a score of 1, while M2 (critical disc herniation) and M3 (spine stiffening disease) received a score of 4.Conclusions:The Subaxial Cervical AO Spine Injury Score is an easy-to-use metric that can help develop a surgical algorithm to supplement the AO Spine Subaxial Cervical Spine Injury Classification System.

The 2020 Australian guideline for prevention, diagnosis and management of acute rheumatic fever and rheumatic heart disease.

Acute rheumatic fever (ARF) and rheumatic heart disease (RHD) cause significant morbidity and premature mortality among Australian Aboriginal and Torres Strait Islander peoples. RHDAustralia has produced a fully updated clinical guideline in response to new knowledge gained since the 2012 edition. The guideline aligns with major international ARF and RHD practice guidelines from the American Heart Association and World Heart Federation to ensure best practice. The GRADE system was used to assess the quality and strength of evidence where appropriate. The 2020 Australian guideline details best practice care for people with or at risk of ARF and RHD. It provides up-to-date guidance on primordial, primary and secondary prevention, diagnosis and management, preconception and perinatal management of women with RHD, culturally safe practice, provision of a trained and supported Aboriginal and Torres Strait Islander workforce, disease burden, RHD screening, control programs and new technologies. Key changes include updating of ARF and RHD diagnostic criteria; change in secondary prophylaxis duration; improved pain management for intramuscular injections; and changes to antibiotic regimens for primary prevention. Other changes include an emphasis on provision of culturally appropriate care; updated burden of disease data using linked register and hospitalisations data; primordial prevention strategies to reduce streptococcal infection addressing household overcrowding and personal hygiene; recommendations for population-based echocardiographic screening for RHD in select populations; expanded management guidance for women with RHD or ARF to cover contraception, antenatal, delivery and postnatal care, and to stratify pregnancy risks according to RHD severity; and a priority classification system for presence and severity of RHD to align with appropriate timing of follow-up.

Development of a Severity Classification System for Sickle Cell Disease.

PurposeThere is no well-accepted classification system of overall sickle cell disease (SCD) severity. We sought to develop a system that could be tested as a clinical outcome predictor.Patients and MethodsUsing validated methodology (RAND/UCLA modified Delphi panel), 10 multi-disciplinary expert clinicians collaboratively developed 180 simplified patient histories and rated each on multiple axes (estimated clinician follow-up frequency, risk of complications or death, quality of life, overall disease severity). Using ratings on overall disease severity, we developed a 3-level severity classification system ranging from Class I (least severe) to Class III (most severe).ResultsThe system defines patients as Class I who are 8–40 years with no end organ damage, no chronic pain, and ≤4 unscheduled acute care visits due to vaso-occlusive crises (VOC) in the last year. Patients <8 or >40 years with no end organ damage, no chronic pain, and <2 unscheduled acute care visits are also considered Class I. Patients any age with ≥5 unscheduled acute care visits and/or with severe damage to bone, retina, heart, lung, kidney, or brain are classified as Class III (except patients ≥25 years with severe retinopathy, no chronic pain, and 0–1 unscheduled acute care visits, who are considered Class II). Patients not meeting these Class I or III definitions are classified as Class II.ConclusionThis system consolidates patient characteristics into homogenous groups with respect to disease state to support clinical decision-making. The system is consistent with existing literature that increased unscheduled acute care visits and organ damage translate into clinically significant patient morbidity. Studies to further validate this system are planned.