Triage Of Patients Research Articles

Cytologic features of differentiated high-grade thyroid carcinoma: A multi-institutional study of 40 cases.

Differentiated high-grade thyroid carcinoma (DHGTC) is recently recognized by the World Health Organization (WHO) as a subgroup of thyroid carcinomas with high-grade features while retaining the architectural and/or cytologic features of well-differentiated follicular-cell-derived tumors. The cytomorphology of DHGTC is not well documented despite potential implications for patient triage and management. The pathology archives of six institutions were searched for cases diagnosed on resection as "high-grade thyroid carcinoma" using WHO criteria. The fine-needle aspiration (FNA) cohort represents a 10-year period (2013-2023); all were reviewed to confirm DHGTC classification. The corresponding FNAs were assessed for 32 cytomorphologic features. Forty cases of DHGTC with prior FNA were identified. The mean patient age was 64.2 years. The average lesion size was 4.9 cm, and the majority demonstrated a TI-RADS score of 4 or 5 (95.2%). Three main high-grade subsets of DHGTC based on corresponding histology included papillary thyroid carcinoma (65%), follicular carcinoma (22.5%), and oncocytic carcinoma (12.5%). Over 97% of FNA cases were classified as Bethesda category IV or above. Approximately 25% of DHGTC showed cytologic features that included marked cytologic atypia, increased anisonucleosis, large oval nuclei, mitotic activity, or necrosis (p<.05); 68% of DHGTC cases were associated with high-risk molecular alterations. TERT mutations occurred in 41%, of which 89% of these were associated with a second mutation, usually RAS or BRAF p.V600E. Cytology has a low sensitivity for DHGTC, although a subset of DHGTCs have cytologic features raising the possibility of a high-grade thyroid carcinoma. Other findings include high-risk molecular changes and clinicopathologic features such as older patient age and larger lesion size.

Unintended effect of reduced patient cost sharing: evidence from China

ABSTRACT In China, hospitals are classified into three tiers based on size and quality to triage patients. Among them, tier-2 and tier-3 hospitals provide similar inpatient services, while tier-3s have higher patient cost sharing due to their ability to provide more sophisticated care. In this study, we exploit a plausibly exogenous change in the financial environment facing tier-2 hospitals: reduced cost sharing in tier-3s. We find that patients are diverted from tier-2s after the reform, and in response to income loss, tier-2s increase the surgical probability and total expense per admission. A 1% decrease in the number of admissions increases the surgical probability by 0.25%, which suggests supplier-induced demand. We also find that tier-2 hospitals induce greater demand from patients with less urgent conditions and more elective procedures. Our analysis suggests that benevolent cost sharing reduction may have unintended consequences beyond the targeted group, and policymakers who neglect these effects would underestimate the costs of such reforms.

Trends in degenerative lumbar spinal surgery during the early COVID-19 pandemic in Republic of Korea: A national study utilizing the national health insurance database.

During the first year of the COVID-19 pandemic, the Republic of Korea (ROK) experienced three epidemic waves in February, August, and November 2020. These waves, combined with the overarching pandemic, significantly influenced trends in spinal surgery. This study aimed to investigate the trends in degenerative lumbar spinal surgery in ROK during the early COVID-19 pandemic, especially in relation to specific epidemic waves. Using the National Health Information Database in ROK, we identified all patients who underwent surgery for degenerative lumbar spinal diseases between January 1, 2019 and December 31, 2020. A joinpoint regression was used to assess temporal trends in spinal surgeries over the first year of the COVID-19 pandemic. The number of surgeries decreased following the first and second epidemic waves (p<0.01 and p = 0.34, respectively), but these were offset by compensatory increases later on (p<0.01 and p = 0.05, respectively). However, the third epidemic wave did not lead to a decrease in surgical volume, and the total number of surgeries remained comparable to the period before the pandemic. When compared to the pre-COVID-19 period, average LOH was reduced by 1 day during the COVID-19 period (p<0.01), while mean hospital costs increased significantly from 3,511 to 4,061 USD (p<0.01). Additionally, the transfer rate and the 30-day readmission rate significantly decreased (both p<0.01), while the reoperation rate remained stable (p = 0.36). Despite the impact of epidemic waves on monthly surgery numbers, a subsequent compensatory increase was observed, indicating that surgical care has adapted to the challenges of the pandemic. This adaptability, along with the stable total number of operations, highlights the potential for healthcare systems to continue elective spine surgery during public health crises with strategic resource allocation and patient triage. Policies should ensure that surgeries for degenerative spinal diseases, particularly those not requiring urgent care but crucial for patient quality of life, are not unnecessarily halted.

Are renal stone protocol computed tomography reports giving us enough information?

Non-contrast computed tomography (CT) is the gold-standard diagnostic test for urolithiasis. Little is published regarding which information needs to be included in the report for it to be most useful to the healthcare team for efficient triage and high-quality patient care. This study aimed to assess the quality and variability of CT scan reporting at a single Canadian tertiary academic medical center. We completed a retrospective review of 100 consecutive renal colic CT scans. Descriptive statistics were used to report the frequency with which specific elements commonly used by urologists to triage and treat patients were included in radiology reports. Our sample had a mean age of 51.4±13.1 years. Stone size was universally reported for obstructing stones but was less frequently reported for non-obstructing stones (100% vs. 86.8%). A similar trend was observed for the exact stone number (100% vs. 93.4%). Non-obstructing stones were more likely than obstructing stones to be reported in one dimension (77.5% vs. 47%). Obstructing stones were reported in three dimensions 27% of the time. CT reports commonly include the presence or absence of hydronephrosis status (98%) but are less likely to include renal size (32%) and periureteral stranding (16%). Hounsfield units (HU) were reported in 3% of the reports, but skin-to-stone distance (SSD) and radiation dose were never reported. Reports routinely included assessments of stone size, location, and number (although not uniformly). HU, SSD, and radiation dose were rarely reported. This provides insight into opportunities for standardized reporting to optimize knowledge transfer that may result in clinical efficiency and improved quality of patient care.

Validation of the Korean Version of the Clinical Frailty Scale-Adjusted Korean Triage and Acuity Scale for Older Patients in the Emergency Department.

Background and Objectives: The Clinical Frailty Scale (CFS), used to screen for prehospital frailty in patients aged >65 years, is simple, time-efficient, and has been validated in emergency departments (EDs). In this study, we analyzed whether the Korean Triage and Acuity Scale (KTAS) classification by level in older patients determined to have frailty based on the Korean version of the CFS increases the triage performance of the current KTAS. Materials and Methods: The primary outcome was 30-day in-hospital mortality, and secondary outcomes were hospital and intensive care unit (ICU) admissions. This study retrospectively analyzed prospectively collected data from three ED centers. Patients with a CFS score ranging from five (mildly frail) to nine (terminally ill) were categorized into the frailty group. We upgraded the KTAS classification of the frailty group by one level of urgency and defined this as the CFS-KTAS. Results: The cutoff values for predicting admission were three and two for the KTAS and CFS-KTAS, respectively. A significant difference was observed in the area under the receiver operating characteristic (AUROC) curve between the KTAS and CFS-KTAS. To predict ICU admission, the cutoff score was two for both scales. A significant difference was observed in the AUROC curve between the KTAS and CFS-KTAS. For predicting in-hospital mortality, the cutoff score was two for both scales. A significant difference was observed in the AUROC curve between the KTAS and CFS-KTAS. Conclusions: This study showed that the CFS-adjusted KTAS has a more useful prognostic value than the KTAS alone for predicting hospital outcomes in older patients.

Machine learning based prediction models for analyzing risk factors in patients with acute abdominal pain: a retrospective study.

Acute abdominal pain (AAP) is a common symptom presented in the emergency department (ED), and it is crucial to have objective and accurate triage. This study aims to develop a machine learning-based prediction model for AAP triage. The goal is to identify triage indicators for critically ill patients and ensure the prompt availability of diagnostic and treatment resources. In this study, we conducted a retrospective analysis of the medical records of patients admitted to the ED of Wuhan Puren Hospital with acute abdominal pain in 2019. To identify high-risk factors, univariate and multivariate logistic regression analyses were used with thirty-one predictor variables. Evaluation of eight machine learning triage prediction models was conducted using both test and validation cohorts to optimize the AAP triage prediction model. Eleven clinical indicators with statistical significance (p < 0.05) were identified, and they were found to be associated with the severity of acute abdominal pain. Among the eight machine learning models constructed from the training and test cohorts, the model based on the artificial neural network (ANN) demonstrated the best performance, achieving an accuracy of 0.9792 and an area under the curve (AUC) of 0.9972. Further optimization results indicate that the AUC value of the ANN model could reach 0.9832 by incorporating only seven variables: history of diabetes, history of stroke, pulse, blood pressure, pale appearance, bowel sounds, and location of the pain. The ANN model is the most effective in predicting the triage of AAP. Furthermore, when only seven variables are considered, including history of diabetes, etc., the model still shows good predictive performance. This is helpful for the rapid clinical triage of AAP patients and the allocation of medical resources.

Through the lens: A qualitative exploration of nurses' experiences of smart glasses in urgent care.

To investigate the real-world experiences of nurses' using smart glasses to triage patients in an urgent care centre. A parallel convergent mixed-method design. We collected data through twelve in-depth interviews with nurses using the device and a survey. Recruitment continued until no new themes emerged. We coded the data using a deductive-thematic approach. Qualitative and survey data were coded and then mapped to the most dominant dimension of the sociotechnical framework. Both the qualitative and quantitative findings were triangulated within each dimension of the framework to gain a comprehensive understanding of user experiences. Overall, nurses were satisfied with using smart glasses in urgent care and would recommend them to others. Nurses rated the device highly on ease of use, facilitation of training and development, nursing empowerment and communication. Qualitatively, nurses generally felt the device improved workflows and saved staff time. Conversely, technological challenges limited its use, and users questioned its sustainability if inadequate staffing could not be resolved. Smart glasses enhanced urgent care practices by improving workflows, fostering staff communication, and empowering healthcare professionals, notably providing development opportunities for nurses. While smart glasses offered transformative benefits in the urgent care setting, challenges, including technological constraints and insufficient organisational support, were barriers to sustained integration. These real-world insights encompass both the benefits and challenges of smart glass utilisation in the context of urgent care. The findings will help inform greater workflow optimisation and future technological developments. Moreover, by sharing these experiences, other healthcare institutions looking to implement smart glass technology can learn from the successes and barriers encountered, facilitating smoother adoption, and maximising the potential benefits for patient care. COREQ checklist (consolidated criteria for reporting qualitative research). No patient or public contribution.

How Healthcare Providers Decide on a Referral Location in Telephone Triage: A Cross-sectional Study.

Approximately 25% of patients that present to the emergency department (ED) do so after contact with a healthcare professional. Many of these patients could be effectively managed in non-ED ambulatory settings. Aligning patients with safe and appropriate outpatient care has the potential to improve ED overcrowding, patient experience, outcomes, and costs. Little is understood about how healthcare providers approach triage decision-making and what factors influence their choices. To evaluate how providers think about patient triage, and what factors influence their decision-making when triaging patient calls. Cross-sectional survey-based study in which participants make triage decisions for hypothetical clinical scenarios. Healthcare providers in the specialties of internal medicine, family medicine, or emergency medicine within a large integrated healthcare system in the Southeast. Differences in individual training and practice characteristics were used to compare observed differences in triage outcomes. Free-response data were evaluated to identify themes and factors affecting triage decisions. Out of 72 total participants, substantial variability in triage decision-making was observed among all patient cases. Attending physicians triaged 1.4 fewer cases to ED care compared with resident physicians (p < 0.001, 95% CI 0.62-2.1). Academic attendings demonstrated a trend toward fewer cases to ED care compared with community attendings (0.61, p = 0.188, 95% CI - 0.31-1.5). Qualitative data highlighted the complex considerations in provider triage and led to the development of a novel conceptual model to describe the cognitive triage process and the main influencing factors. Triage decision-making for healthcare providers is influenced by many factors related to clinical resources, care coordination, patient factors, and clinician factors. The complex considerations involved yield variability in triage decisions that is largely unexplained by descriptive physician factors.

Training of interns in the system of medical triage of patients on the basis of the Simulation Center of the Kazakh National Medical University

Providing emergency care to patients is a basic skill for doctors of any specialty. Emergency department overcrowding is a pressing public health problem that affects countries around the world. Medical Triage or triage is the process of prioritizing medical care for patients based on the severity of their condition.

AI-enabled digital test to predict disease recurrence for patients with early-stage invasive breast cancer and performance in a MammaPrint low-risk cohort from the Netherlands with a median 6-year follow-up.

1569 Background: Traditional invasive breast cancer (IBC) grading, although useful, remains limited due to diagnostic subjectivity and absence of phenotypic diversity including the recently observed importance of tumor epithelial – stromal interactions and lymphocyte content-distribution. We developed and validated a clinical grade digital test (PreciseDx Breast, PDxBr) which combines image-derived Artificial Intelligent (AI)-grading features and clinical data (i.e. age, stage, tumor size, LN status) to predict recurrence in early-stage IBC and sought to understand performance in a MammaPrint cohort with outcome data. Methods: A MammaPrint cohort with median 6-year follow-up was identified at the Laboratory of Pathology, Dordrecht, the Netherlands (NTH). H&amp;E stained images (digitized at Philips, Eindhoven, NTH) with clinical data (from the pathology and Dutch cancer registries) including demographics, pathology results, MammaPrint risk classification, treatment type and recurrence events were obtained. Performance of the PDxBr validated model (AI-grade + clinical) on the MammaPrint cohort was evaluated using the AUC/concordance index, along with NPV, PPV, Hazards ratio (HR), sensitivity, and specificity. Results: 250 patients, median age 57 years, majority stage 1-IIIa, 100% HR+ve, Her2-ve, 84% LN-ve, 67% grade 2 and 66% MammaPrint low risk. There were 15 events (6%: 7 deaths, 3 second primaries,4 metastases and 1 local regional). PDxBR model classified 134 patients as high risk and 116 as low with 10 of 15 (67%) events identified as high risk. The NPV for PDxBr was 96% with a HR 1.63, Se 70%, Sp 46% vs. MammaPrint with an NPV of 94%, HR of 0.96, Se 40%, Sp 66%; identifying only 5 of the 15 events (33%) as high risk while missing 10. Of note, the AI- grade/imaging model (without clinical features) yielded an NPV of 95% with a HR of 1.46, Se 70%, Sp 42% and correctly identified 10 of 15 events. Conclusions: The results from this observational study suggest that triaging patients with the PDxBr test could potentially be adjunctive to the management decision process of patients with early-stage IBC including the use and subsequent interpretation of genomic tests such as MammaPrint. Additional studies are underway to confirm these initial findings.

Therapeutic Potential of Lipoprotein(a) Inhibitors.

Increasing evidence has implicated lipoprotein(a) [Lp(a)] in the causality of atherosclerosis and calcific aortic stenosis. This has stimulated immense interest in developing novel approaches to integrating Lp(a) into the setting of cardiovascular prevention. Current guidelines advocate universal measurement of Lp(a) levels, with the potential to influence cardiovascular risk assessment and triage of higher-risk patients to use of more intensive preventive therapies. In parallel, considerable activity has been undertaken to develop novel therapeutics with the potential to achieve selective and substantial reductions in Lp(a) levels. Early studies of antisense oligonucleotides (e.g., mipomersen, pelacarsen), RNA interference (e.g., olpasiran, zerlasiran, lepodisiran) and small molecule inhibitors (e.g., muvalaplin) have demonstrated effective Lp(a) lowering and good tolerability. These agents are moving forward in clinical development, in order to determine whether Lp(a) lowering reduces cardiovascular risk. The results of these studies have the potential to transform our approach to the prevention of cardiovascular disease.

Diagnosis of acute aortic syndromes with ultrasound and d-dimer: the PROFUNDUS study

BackgroundIn patients complaining common symptoms such as chest/abdominal/back pain or syncope, acute aortic syndromes (AAS) are rare underlying causes. AAS diagnosis requires urgent advanced aortic imaging (AAI), mostly computed tomography angiography. However, patient selection for AAI poses conflicting risks of misdiagnosis and overtesting. ObjectivesWe assessed the safety and efficiency of a diagnostic protocol integrating clinical data with point-of-care ultrasound (POCUS) and d-dimer (single/age-adjusted cutoff), to select patients for AAI. MethodsThis prospective study involved 12 Emergency Departments from 5 countries. POCUS findings were integrated with a guideline-compliant clinical score, to define the integrated pre-test probability (iPTP) of AAS. If iPTP was high, urgent AAI was requested. If iPTP was low and d-dimer was negative, AAS was ruled out. Patients were followed for 30 days, to adjudicate outcomes. ResultsWithin 1979 enrolled patients, 176 (9 %) had an AAS. POCUS led to net reclassification improvement of 20 % (24 %/-4 % for events/non-events, P < 0.001) over clinical score alone. Median time to AAS diagnosis was 60 min if POCUS was positive vs 118 if negative (P = 0.042). Within 941 patients satisfying rule-out criteria, the 30-day incidence of AAS was 0 % (95 % CI, 0–0.41 %); without POCUS, 2 AAS were potentially missed. Protocol rule-out efficiency was 48 % (95 % CI, 46–50 %) and AAI was averted in 41 % of patients. Using age-adjusted d-dimer, rule-out efficiency was 54 % (difference 6 %, 95 % CI, 4–9 %, vs standard cutoff). ConclusionsThe integrated algorithm allowed rapid triage of high-probability patients, while providing safe and efficient rule-out of AAS. Age-adjusted d-dimer maximized efficiency.CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov, NCT04430400

Assessment of Barriers, Supports, and Context to Implement Best Practice Pain Management in the Emergency Department: The IMPAINED Study

AimTo assess the emergency department practice context and identify strategies to improve outcomes of patients with acute pain. BackgroundEffective treatment of acute pain in the emergency department depends upon clinicians adopting pain interventions into practice. However, it is well-recognized that acute pain is often undertreated. The local practice context strongly influences clinicians’ adoption of interventions into their clinical practice. An assessment of this practice context can inform implementation interventions and strategies to improve outcomes for patients with acute pain. MethodsChart audit, staff survey, and staff working groups were conducted from June 2020 to May 2021 Data were analyzed and synthesized across sources informed by assessment elements of the Ottawa model of research use (OMRU) implementation model and expert recommendations for implementing change strategies. ResultsThe OMRU facilitated contextual assessment of pain treatment practice in the emergency department and the development of implementation strategies. Adoption of evidence-based pain interventions was low in the sample studied. Workflow and workload were the primary barriers to evidence-based pain practices by potential adopters, while positive beliefs and high awareness of evidence-based pain interventions were supportive factors. Implementation strategies were informed by assessment findings and mapped to the Ottawa model and expert recommendations for implementing change elements. ConclusionThe adoption of evidence into practice in the emergency department relies upon a comprehensive assessment of the local context. The use of the OMRU assessment process resulted in meaningful engagement with staff and a deeper understanding of local pain management practices. Clinicians view evidence-based pain management as important, however, there are competing priorities within the emergency department, such as patient flow and triage. This study provides an exemplar of utilizing an implementation framework to identify pain practices within the emergency department. Clinical ImplicationsAchieving impactful change in clinical practice to improve patient outcomes should start with the application of implementation methods that enable comprehensive analysis of the local practice context. The assessment should begin with collaboration with local clinicians that persist throughout the life of the study to ensure change is sustainable.

Deep neural networks detect regional wall motion abnormalities and preclinical cardiovascular disease from 12-lead ECGs.

Identifying regional wall motion abnormalities (RWMAs) is critical for diagnosing and risk stratifying patients with cardiovascular disease, particularly ischemic heart disease. We hypothesized that a deep neural network could accurately identify patients with regional wall motion abnormalities from a readily available standard 12-lead electrocardiogram (ECG). This observational, retrospective study included patients who were treated at Beth Israel Deaconess Medical Center and had an ECG and echocardiogram performed within 14 days of each other between 2008 and 2019. We trained a convolutional neural network to detect the presence of RWMAs, qualitative global right ventricular (RV) hypokinesis, and varying degrees of left ventricular dysfunction (left ventricular ejection fraction [LVEF] ≤50%, LVEF ≤40%, and LVEF ≤35%) identified by echocardiography, using ECG data alone. Patients were randomly split into development (80%) and test sets (20%). Model performance was assessed using area under the receiver operating characteristic curve (AUC). Cox proportional hazard models adjusted for age and sex were performed to estimate the risk of future acute coronary events. The development set consisted of 19,837 patients (mean age 66.7±16.4; 46.7% female) and the test set comprised of 4,953 patients (mean age 67.5±15.8 years; 46.5% female). On the test dataset, the model accurately identified the presence of RWMA, RV hypokinesis, LVEF ≤50%, LVEF ≤40%, and LVEF ≤35% with AUCs of 0.87 (95% CI 0.858-0.882), 0.888 (95% CI 0.878-0.899), 0.923 (95% CI 0.914-0.933), 0.93 (95% CI 0.921-0.939), and 0.876 (95% CI 0.858-0.896), respectively. Among patients with normal biventricular function at the time of the index ECG, those classified as having RMWA by the model were 3 times the risk (age- and sex-adjusted hazard ratio, 2.8; 95% CI 1.9-3.9) for future acute coronary events compared to those classified as negative. We demonstrate that a deep neural network can help identify regional wall motion abnormalities and reduced LV function from a 12-lead ECG and could potentially be used as a screening tool for triaging patients who need either initial or repeat echocardiographic imaging.

Triage of advanced cervical cancer through immunotherapy induction (TRACTION).

TPS5622 Background: In advanced/recurrent cervical cancer, immune checkpoint inhibitors have emerged as an attractive alternative and have demonstrated impressive therapeutic responses. As a result, the combination of pembrolizumab with platinum/taxane chemotherapy with or without bevacizumab received FDA approval for first-line systemic therapy in persistent, recurrent, or metastatic PD-L1+ cervical cancer. However, this regimen demonstrates the greatest impact on survival when all four drugs are utilized and are not without the potential for significant toxicity. CheckMate-358 utilized two dosing regimens of ipilimumab and nivolumab in advanced/recurrent cervical cancer. In the preliminary results, the utilization of either dosing regimen resulted in remarkable, durable responses in chemo-naïve patients with the median overall survival not reached. Given the potential benefit of CTLA-4/PD-1 blockade in the upfront setting, we propose a phase II trial examining the strategy of induction immunotherapy with lorigerlimab (bispecific antibody targeting CTLA-4 and PD-1) in chemo-naïve cervical cancer patients not amenable to curative treatment. Methods: The study is a phase II, multi-site clinical trial conducted at MD Anderson Cancer Center and Lyndon B. Johnson General Hospital. In the induction phase, patients will receive intravenous (IV) lorigerlimab at the recommended phase II dose (6 mg/kg) for three 21-day cycles with a repeat CT scan performed at week 9 of treatment. Tumor response (by RECIST v1.1) to induction immunotherapy will be used to triage patients to either continuation of lorigerlimab (if at least stable disease) or standard of care treatment (if disease progression) in the triaged treatment phase. Lorigerlimab will be continued until progression or intolerable toxicity, for a maximum of 35 cycles. At any time point, all patients at first disease progression will subsequently receive physician’s choice standard of care systemic therapy with carboplatin/paclitaxel +/- pembrolizumab +/- bevacizumab and will be followed for survival. The primary objective is to estimate disease control rate. Secondary objectives are to determine objective response rate, duration of response, overall survival, progression-free survival, and safety (by CTCAE v5.0). Key eligibility criteria include 1) recurrent, metastatic, or persistent cervical cancer 2) squamous cell carcinoma, adenosquamous, or adenocarcinoma histologic subtype 3) not amenable to curative surgery or radiation. The trial is open with 14 of planned 40 patients enrolled at the time of submission. Clinical trial information: NCT05475171 .

Value of multi-modality small fiber assessments in a genotypically diverse cohort of transthyretin-related amyloidosis in the early stages of disease

IntroductionTransthyretin-related amyloidosis (ATTRv) is a progressive multisystem disorder, predominantly involving the peripheral nerve system (PNS) and heart. Quantification of small fiber damage may help guide treatment decisions, as amyloid deposits frequently affect those fibers early in disease course. Corneal confocal microscopy (CCM) is a promising method to monitor patients with ATTRv, due to similarities between corneal nerves and PNS, as the cornea is innervated by Aδ and C fibers. MethodsWe compared CCM measures from ATTRv patients to a group of healthy individuals, matched by age and gender. We then investigated the correlations between small fiber tests (SFT): CCM, LDI-Flare and CDT, COMPASS-31 and disability scales (RODS and ONLS) in patients. ResultsOf 20 patients (6 with V30M), mean age 50.3±15.3Y, 7 female (35%), six (30%) had polyneuropathy and 10 (50%) carpal tunnel syndrome. CDT was abnormal in 9 and LDI-flare in 6 patients. CCM was abnormal in 19 tested patients and significantly reduced when compared to controls (CNFL: 6.31±0.31 vs. 15.21±1.02mm/mm2, p<0.001). Mean COMPASS-31-scores were 22.27±22.84; RODS and ONLS were 38.15±12.33 and 2.05±2.3, with no significant differences between sub-group scores. Disease duration was significantly correlated with ONLS (0.43, p=0.05) and RODS (0.46, p=0.03). There were no significant correlations between measures of disability and SFT. ConclusionsIn a diverse cohort of ATTRv patients, CCM was the most frequent abnormal measurement. CCM can be a useful test to triage patients in the early disease stages and with few or equivocal symptoms.

Leveraging graph neural networks for supporting automatic triage of patients

Patient triage is crucial in emergency departments, ensuring timely and appropriate care based on correctly evaluating the emergency grade of patient conditions. Triage methods are generally performed by human operator based on her own experience and information that are gathered from the patient management process. Thus, it is a process that can generate errors in emergency-level associations. Recently, Traditional triage methods heavily rely on human decisions, which can be subjective and prone to errors. A growing interest has recently been focused on leveraging artificial intelligence (AI) to develop algorithms to maximize information gathering and minimize errors in patient triage processing. We define and implement an AI-based module to manage patients’ emergency code assignments in emergency departments. It uses historical data from the emergency department to train the medical decision-making process. Data containing relevant patient information, such as vital signs, symptoms, and medical history, accurately classify patients into triage categories. Experimental results demonstrate that the proposed algorithm achieved high accuracy outperforming traditional triage methods. By using the proposed method, we claim that healthcare professionals can predict severity index to guide patient management processing and resource allocation.

Feasibility, Reliability, and Effectiveness of Oral cancer screening in South Asia and Southeast Asian countries: A systematic review and Meta-analysis.

The incidence of oral cancer is significantly high in South Asia and Southeast Asia. Organized screening is an effective approach to early detection. The aim of this systematic review and meta-analysis was to evaluate the reliability, diagnostic accuracy, and effectiveness of visual oral screening by community health workers (CHWs) in identifying oral cancer/oral potentially malignant disorders (OPMDs) in this region. We conducted a bibliographic search in PubMed, Scopus, the gray literature of Google Scholar, ProQuest dissertations, and additional manual searches. Twelve articles were included for qualitative synthesis and six for meta-analysis. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), and forest plot analysis were performed. Meta-analysis showed CHWs identified 8% (n = 6365) as suspicious and 92% (n = 74,140) as normal. The diagnostic accuracy of visual oral screening by CHWs showed a sensitivity of 75% (CI: 74-76) and specificity of 97% (CI: 97-97) in the detection of OPMDs/oral cancer. Forest plots were obtained using a random effects model (DOR: 24.52 (CI: 22.65-26.55)) and SAUC: 0.96 (SE = 0.05). Oral visual examination by trained CHWs can be utilized for community screenings to detect oral cancer early. This approach can be used in primary healthcare to triage patients for further referral and management.

Understanding the accuracy of body temperature measurements in patient triage during cancer treatment: a retrospective audit

Understanding the accuracy of body temperature measurements in patient triage during cancer treatment: a retrospective audit

P.149 Saskatchewan spine pathway classification is associated with post-operative outcome and improved quality-adjusted life years following lumbosacral fusion

Background: Low back pain (LBP) is a common cause of disability and decreased quality of life. The Saskatchewan Spine Pathway classification (SSPc) is a method for triaging patients who are candidates for surgery. Methods: Consecutive patients who underwent lumbosacral instrumented fusion for degenerative spinal pathology from Jan 1, 2012, to Sept 20, 2018, by a single surgeon at our institution were retrospectively reviewed. Patients were stratified by SSPc into 4 groups based on pain pattern. Demographic and clinical data were collected. Outcomes were compared between cohorts both for absolute values and achieving MCID. Results: 169 consecutive patients were included in our study. After stratifying by SSPc grouping, there were 61 SSPc I patients, 45 SSPc III patients, and 63 SSPc IV patients. Patients in all groups had clinical improvement following surgery. Patients classified as SSPc III had superior outcomes in ODI, EQ-5D and EQ-VAS, and were more likely to achieve the MCID for ED-5D. Multivariate analysis demonstrated that SSPc grouping is an independent predictor of final VAS back, ODI, EQ-5D, and EQ-VAS as well as achieving the MCID for EQ-5D. Conclusions: The SSPc classification is associated with outcomes following lumbosacral fusion. In particular, patients with SSPc pattern 3 had better outcomes and improved QALY.