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Background and Objectives Significant practice variation exists in managing young infants with fever. Quality improvement strategies can aid in risk stratification and standardization of best care practices, along with a reduction of unnecessary interventions. The aim of this initiative was to safely reduce unnecessary admissions, antibiotics, and lumbar punctures (LPs) by 10% in low-risk, febrile infants aged 29 to 90 days presenting to the emergency department (ED) over a 12-month period. Methods Using the Model for Improvement, a multidisciplinary team developed a multipronged intervention: an updated clinical decision tool (CDT), procalcitonin (PCT) adoption, education, a feedback tool, and best practice advisory (BPA) banner. Outcome measures included the proportion of low-risk infants that were admitted, received antibiotics, and had LPs. Process measures were adherence to the CDT and percentage of PCT ordered. Missed bacterial infections and return visits were balancing measures. The analysis was completed using descriptive statistics and statistical process control methods. Results Five hundred and sixteen patients less than 90 days of age were included in the study, with 403 patients in the 29- to 90-day old subset of primary interest. In the low-risk group, a reduction in hospital admissions from a mean of 24.1% to 12.0% and a reduction in antibiotics from a mean of 15.2% to 1.3% was achieved. The mean proportion of LPs performed decreased in the intervention period from 7.5% to 1.8%, but special cause variation was not detected. Adherence to the CDT increased from 70.4% to 90.9% and PCT was ordered in 92.3% of cases. The proportion of missed bacterial infections was 0.3% at baseline and 0.5% in the intervention period while return visits were 6.7% at baseline and 5.0% in the intervention period. Conclusions The implementation of a quality improvement strategy, including an updated evidence-based CDT for young infant fever incorporating PCT, safely reduced unnecessary care in low-risk, febrile infants aged 29 to 90 days in the ED. Purpose To develop and implement a multipronged improvement strategy including an evidence-based CDT utilizing PCT to maximize value of care delivered to well-appearing, febrile infants presenting to EDs. [ABSTRACT FROM AUTHOR]

Monica Zolezzi,1,* Athar Elhakim,2,* Iman A Qubaiah,1,* Doaa Elsayed Mahmoud,1,* Shorouq Homs,1,* Waad Elamin,1,* Engy Sherif Tawfik,1,* Oraib Abdallah,3,* Yassin Eltorki,3,* Noriya Al-Khuzaei3,* 1College of Pharmacy, QU Health, Qatar University, Doha, Qatar; 2College of Health Sciences, University of Doha for Science and Technology, Doha, Qatar; 3Pharmacy Department, Mental Health Services, Hamad Medical Corporation, Doha, Qatar*These authors contributed equally to this workCorrespondence: Monica Zolezzi, College of Pharmacy, QU Health, Qatar University, Doha, Qatar, Tel +974 4403 5623 (GMT +3hrs), Email mzolezzi@qu.edu.qaBackground: Drug-induced QTc interval prolongation (QTcIP) can lead to serious consequences and is often a concern for mental health practitioners, as access to experts such as cardiologists, for consultation is time-limiting and can delay treatment decisions. This research aimed at validating the content of an algorithm for the assessment, management and monitoring of drug-induced QTcIP in mental health practice.Methods: Following an initial face validity by content experts, a cross-sectional survey of mental health care practitioners with a 4-point Likert-type scale was used to assess the validity of the decision steps on the QTcIP algorithm (QTcIPA) by estimating the content validity index (CVI) and the modified kappa statistic (κ*). Participants’ open-ended comments were also thematically analyzed.Results: Mental health practitioners found the QTcIPA to be appropriate, safe, and evidence-based, as indicated by the high individual item CVI scores ranging from 0.89 to 1 for all of the steps/decision statements in the three domains assessed: appropriateness, safety and reliability of the references used. Five themes emerged from the qualitative analysis of the open-ended comments, of which three were identified as strengths, including practical usability, reliable references and beneficial for pharmacists. Two themes were recognized as limitations, namely, the need for additional clinical content and application barriers.Conclusion: These results suggest that the QTcIPA may be a useful tool for mental health clinicians at the time of prescribing medications with potential risk of QTcIP. Future research will explore the implementation of the QTcIPA into clinical practice using computerized decision support tools through web-based and mobile applications.Keywords: drug-induced arrhythmias, QTc interval prolongation, algorithm, mental health practice, clinical decision tool

Objective: Clinical decision aids (CDAs) can help clinicians with patient risk assessment. However, there is little data on CDA calculation, interpretation and documentation in real‐world ED settings. The ABCD2 score (range 0–7) is a CDA used for patients with transient ischaemic attack (TIA) and assesses risk of stroke, with a score of 0–3 being low risk. The aim of this study was to describe ABCD2 score documentation in patients with an ED diagnosis of TIA. Methods: Retrospective observational study of patients with a working diagnosis of a TIA in two Australian EDs. Data were gathered using routinely collected data from health informatics sources and medical records reviewed by a trained data abstractor. ABCD2 scores were calculated and compared with what was documented by the treating clinician. Data were presented using descriptive analysis and scatter plots. Results: Among the 367 patients with an ED diagnosis of TIA, clinicians documented an ABCD2 score in 45% (95% CI 40–50%, n = 165). Overall, there was very good agreement between calculated and documented scores (Cohen's kappa 0.90). The mean documented and calculated ABCD2 score were similar (3.8, SD = 1.5, n = 165 vs 3.7, SD = 1.8, n = 367). Documented scores on the threshold of low and high risk were more likely to be discordant with calculated scores. Conclusions: The ABCD2 score was documented in less than half of eligible patients. When documented, clinicians were generally accurate with their calculation and application of the ABCD2. No independent predictors of ABCD2 documentation were identified. [ABSTRACT FROM AUTHOR]

BACKGROUND: To evaluate the diagnostic accuracy of clinical signs combined with the tongue blade test (TBT) to detect maxillary and mandibular fractures. METHODS: A cross-sectional study enrolled patients with maxillary and mandibular injuries in the emergency department. Physical examination and the TBT were performed, followed by radiological imaging (facial X-ray or computed tomography [CT]). The diagnostic accuracy was calculated for individuals and a combination of clinical findings at predicting maxillary and mandibular fractures. RESULTS: A total of 98 patients were identified, of whom 31.6% had maxillary fractures and 9.2% had mandibular fractures. The combination of malocclusion, tenderness on palpation and swelling with positive TBT had 100% specificity to detect maxillary and mandibular fractures. In the absence of malocclusion, the combination of tenderness on palpation and swelling with positive TBT produced a specificity of 97.8% for maxillary fracture and a specificity of 96.2% for mandibular fracture. A clinical decision tool consisting of malocclusion, tenderness on palpation, swelling and TBT revealed a specificity of 100% and a positive predictive value of 100%. CONCLUSION: The clinical decision tool is potentially useful to rule out mandibular fractures, thus preventing unnecessary radiation exposure. [ABSTRACT FROM AUTHOR]

Introduction Los Angeles Motor Scale (LAMS) is a validated prehospital scoring tool to identify stroke patients with large vessel occlusions (LVOs). While some studies have reported conflicting data in regards to the diagnostic value of LAMS, this systematic review and meta-analysis aims to provide a more concrete evidence for the value of this clinical decision tool in the diagnosis of LVO in suspected stroke patients. Method Online databases of PubMed, Embase, Scopus, and Web of Science were searched until the end of October 2022, for studies evaluating the diagnostic performance of LAMS in the detection of LVOs in suspected stroke patients. Results The results of our analysis demonstrated an AUC of 0.83 (95% CI: 0.79, 0.86), sensitivity of 0.65 (95% CI: 0.54, 0.74), and specificity of 0.83 (95% CI: 0.79, 0.86) for the diagnostic value of LAMS score with a cut-off value of ≥ 4. The diagnostic odds ratio of LAMS score was 8.81 (95% CI: 6.24, 12.45). Sensitivity analyses reveled that diagnostic performance of LAMS improves when utilized for detection of occlusion in the more proximal segments of large vessels, with a sensitivity of 0.75 and specificity of 0.83. Conclusion A high level of evidence showed that LAMS scale does not have a promising diagnostic value in the identification of LVOs in suspected stroke patients. The sensitivity of 0.65 for this tool makes it obsolete as a proper triaging tool. As a suggestion, LAMS could be utilized in conjunction with other additional factors to increase its diagnostic performance.

Background: Head injury is common in children with approximately 700 000 attendances at emergency departments annually; one-third are conveyed by ambulance. However, 75% of them are discharged with no treatment. Most head-injured children could be managed on scene. Aim: This study aimed to investigate paramedic assessment and management of children with minor head injury. Methods: A web-based survey of paramedics at one trust was carried out, and simple descriptive analysis was completed. Findings: Fifty-nine paramedics took part. Parental anxiety, mechanism of injury, presence of red flags, fear of consequences and safeguarding concerns were the most common reasons that paramedics convey children with head injury to the emergency department. Paramedics employ a variety of non-validated tools to help them assess and manage children with head injury, with the head injury guidance by the National Institute for Health and Care Excellence most used. A lack of confidence in wound closure was a key barrier to managing patients on scene, along with a perceived inability to manage children in general, limited GP availability, a lack of training in paediatrics and risk avoidance. Conclusions: Several factors inhibit the ability of paramedics to manage children with minor head injury on scene, leading to avoidable hospital conveyance. Three-quarters of paramedics said they would benefit from a clinical decision tool to support them in the assessment and management of children with minor head injury. [ABSTRACT FROM AUTHOR]

Introduction: Los Angeles Motor Scale (LAMS) is a validated prehospital scoring tool to identify stroke patients with large vessel occlusions (LVOs). While some studies have reported conflicting data in regards to the diagnostic value of LAMS, this systematic review and meta-analysis aims to provide a more concrete evidence for the value of this clinical decision tool in the diagnosis of LVO in suspected stroke patients. Method: Online databases of PubMed, Embase, Scopus, and Web of Science were searched until the end of October 2022, for studies evaluating the diagnostic performance of LAMS in the detection of LVOs in suspected stroke patients. Results: The results of our analysis demonstrated an AUC of 0.83 (95% CI: 0.79, 0.86), sensitivity of 0.65 (95% CI: 0.54, 0.74), and specificity of 0.83 (95% CI: 0.79, 0.86) for the diagnostic value of LAMS score with a cut-off value of = 4. The diagnostic odds ratio of LAMS score was 8.81 (95% CI: 6.24, 12.45). Sensitivity analyses reveled that diagnostic performance of LAMS improves when utilized for detection of occlusion in the more proximal segments of large vessels, with a sensitivity of 0.75 and specificity of 0.83. Conclusion: A high level of evidence showed that LAMS scale does not have a promising diagnostic value in the identification of LVOs in suspected stroke patients. The sensitivity of 0.65 for this tool makes it obsolete as a proper triaging tool. As a suggestion, LAMS could be utilized in conjunction with other additional factors to increase its diagnostic performance. [ABSTRACT FROM AUTHOR]

• Deep learning (DL) is used to predict the radiotherapy dose in esophageal cancer. • This study elaborates an automated tool combining DL models and NTCP models. • The automated model-based approach redirects esophageal cancer patients to PT. • The automated tool succeeds in predicting which patients should be referred to PT. This study aims to investigate how accurate our deep learning (DL) dose prediction models for intensity modulated radiotherapy (IMRT) and pencil beam scanning (PBS) treatments, when chained with normal tissue complication probability (NTCP) models, are at identifying esophageal cancer patients who are at high risk of toxicity and should be switched to proton therapy (PT). Two U-Net were created, for photon (XT) and proton (PT) plans, respectively. To estimate the dose distribution for each patient, they were trained on a database of 40 uniformly planned patients using cross validation and a circulating test set. These models were combined with a NTCP model for postoperative pulmonary complications. The NTCP model used the mean lung dose, age, histology type, and body mass index as predicting variables. The treatment choice is then done by using a ΔNTCP threshold between XT and PT plans. Patients with ΔNTCP ≥ 10% were referred to PT. Our DL models succeed in predicting dose distributions with a mean error on the mean dose to the lungs (MLD) of 1.14 ± 0.93% for XT and 0.66 ± 0.48% for PT. The complete automated workflow (DL chained with NTCP) achieved 100% accuracy in patient referral. The average residual (ΔNTCP ground truth - ΔNTCP predicted) is 1.43 ± 1.49%. This study evaluates our DL dose prediction models in a broader patient referral context and demonstrates their ability to support clinical decisions. [ABSTRACT FROM AUTHOR]

Introduction: There are established and validated clinical decision tools for cervical spineclearance. Almost all the rules include spinal tenderness on exam as an indication for imaging. Ourgoal was to apply GLASS, a previously derived clinical decision tool for cervical spine clearance, tothoracolumbar injuries. GLass intact Assures Safe Spine (GLASS) is a simple, objective method toevaluate those patients involved in motor vehicle collisions and determine which are at low risk forthoracolumbar injuries.Methods: We performed a retrospective cohort study using the National Accident Sampling System-Crashworthiness Data System (NASS-CDS) over an 11-year period (1998-2008). Sampled occupantcases selected in this study included patients age 16-60 who were belt-restrained, front- seatoccupants involved in a crash with no airbag deployment, and no glass damage prior to the crash.Results: We evaluated 14,191 occupants involved in motor vehicle collisions in this analysis.GLASS had a sensitivity of 94.4% (95% CI [86.3-98.4%]), specificity of 54.1% (95% CI [53.2-54.9%]), and negative predictive value of 99.9% (95% CI [99.8-99.9%]) for thoracic injuries, and asensitivity of 90.3% (95% CI [82.8-95.2%]), specificity of 54.2% (95% CI [53.3-54.9%]), and negativepredictive value of 99.9% (95% CI [99.7-99.9%]) for lumbar injuries.Conclusion: The GLASS rule represents the possibility of a novel, more-objective thoracolumbarspine clearance tool. Prospective evaluation would be required to further evaluate the validity of thisclinical decision rule.

Benjamin D Horne,1,2 Matthew J Hegewald,3 Courtney Crim,4 Susan Rea,5 Tami L Bair,1 Denitza P Blagev3 1Intermountain Medical Center Heart Institute, Salt Lake City, UT, USA; 2Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA; 3Division of Pulmonary Medicine, Department of Internal Medicine, Intermountain Medical Center, Salt Lake City, UT, USA; 4Research and Development, GlaxoSmithKline, Research Triangle Park, NC, USA; 5Care Transformation, Intermountain Healthcare, Salt Lake City, UT, USACorrespondence: Benjamin D HorneIntermountain Medical Center Heart Institute, 5121 S. Cottonwood Street, Salt Lake City, UT 84107, USATel +1801-507-4701Email benjamin.horne@imail.org Twitter@DrBenjaminHorneIntroduction: Tobacco use and other cardiovascular risk factors often accompany chronic obstructive pulmonary disease (COPD). This study derived and validated the Summit Score to predict mortality in people with COPD and cardiovascular risks.Methods: SUMMIT trial subjects (N=16,485) ages 40– 80 years with COPD were randomly assigned 50%/50% to derivation (N=8181) and internal validation (N=8304). Three external COPD validations from Intermountain Healthcare included outpatients with cardiovascular risks (N=9251), outpatients without cardiovascular risks (N=8551), and inpatients (N=26,170). Cox regression evaluated 40 predictors of all-cause mortality. SUMMIT treatments including combined fluticasone furoate (FF) 100μg/vilanterol 25μg (VI) were not included in the score.Results: Mortality predictors were FEV1, heart rate, systolic blood pressure, body mass index, age, smoking pack-years, prior COPD hospitalizations, myocardial infarction, heart failure, diabetes, anti-thrombotics, anti-arrhythmics, and xanthines. Combined in the Summit Score (derivation: c=0.668), quartile 4 vs 1 had HR=4.43 in SUMMIT validation (p< 0.001, 95% CI=3.27, 6.01, c=0.662) and HR=8.15 in Intermountain cardiovascular risk COPD outpatients (p< 0.001, 95% CI=5.86, 11.34, c=0.736), and strongly predicted mortality in the other Intermountain COPD populations. Among all SUMMIT subjects with scores 14– 19, FF 100μg/VI 25μg vs placebo had HR=0.76 (p=0.0158, 95% CI=0.61, 0.95), but FF 100μg/VI 25μg was not different from placebo for scores < 14 or > 19.Conclusion: In this post hoc analysis of SUMMIT trial data, the Summit Score was derived and validated in multiple Intermountain COPD populations. The score was used to identify a subpopulation in which mortality risk was lower for FF 100μg/VI 25μg treatment.Trial Registration: The SUMMIT trial is registered at ClinicalTrials.gov as number NCT01313676.Keywords: clinical decision tool, risk score, randomized controlled trial, Intermountain risk score, IMRS

Abstract Background Satisfactory tools to preclude low-risk patients from intensive diagnostic testing for primary aldosteronism (PA) are lacking. Therefore, we aimed to develop a decision tool to determine which patients with difficult-to-control hypertension have a low probability of PA, thereby limiting the exposure to invasive testing while at the same time increasing the efficiency of testing in the remaining patients. Methods Data from consecutive patients with difficult-to-control hypertension, analysed through a standardized diagnostic protocol between January 2010 and October 2017 (n = 824), were included in this cross-sectional study. PA was diagnosed by a combined approach: 1) elevated aldosterone-to-renin ratio (> 5.0 pmol/fmol/s), confirmed with 2) non-suppressible aldosterone after standardized saline infusion (≥280 pmol/L). Multivariable logistic regression analyses including seven pre-specified clinical variables (age, systolic blood pressure, serum potassium, potassium supplementation, serum sodium, eGFR and HbA1c) was performed. After correction for optimism, test reliability, discriminative performance and test characteristics were determined. Results PA was diagnosed in 40 (4.9%) of 824 patients. Predicted probabilities of PA agreed well with observed frequencies and the c-statistic was 0.77 (95% confidence interval (95%CI) 0.70–0.83). Predicted probability cut-off values of 1.0–2.5% prevented unnecessary testing in 8–32% of the patients with difficult-to-control hypertension, carrying sensitivities of 0.98 (95%CI 0.96–0.99) and 0.92 (0.83–0.97), and negative predictive values of 0.99 (0.98–1.00) and 0.99 (0.97–0.99). Conclusions With a decision tool, based on seven easy-to-measure clinical variables, patients with a low probability of PA can be reliably selected and a considerable proportion of patients with difficult-to-control hypertension can be spared intensive diagnostic testing.

The timely and appropriate IV to Oral Switch (IVOS) of antibiotics is beneficial to patient care and AMR strategies. However, a lack of prescriber confidence in deciding to switch often prolongs IV antibiotic use. The creation of a bite-size educational video and a smartphone application clinical decision tool, has brought the learning process closer to everyday practice, in an easy to access and understandable manner. Both have been very well received and shared with many acute NHS Trusts. The implementation was correlated with an improvement in audit findings. The multidisciplinary and collaborative approach in developing these tools has been the key to success.

Antimicrobial audits on A&E and acute admissions wards have highlighted deficiencies in prescribing practices, particularly the inappropriate use of broad-spectrum agents. A clinical decision-making tool was created to expedite and facilitate the process of selecting correct antimicrobial treatments based on the site and severity of an infection, and also included the consideration of penicillin allergy. Simple, efficient, and effective, this tool has already been shared with many NHS Trusts nationally. Further audits, after this tool was introduced, show improvements in some aspects of antimicrobial prescribing, despite limited opportunities to deliver an awareness campaign of this resource. Such action will be needed to drive further improvements in antimicrobial prescribing choices in sepsis.

Introduction: The cause of constipation is multifactorial and common problem for patients on hemodialysis. A lack of strong evidence on suitable treatment strategies means there is an unorganized approach to selecting therapies, which can exacerbate constipation or worsen symptoms. Clinicians and patients would benefit from a content and face validated treatment algorithm for treating constipation. In this study, our objective was to develop and content and face validate a constipation treatment toolkit for patients on hemodialysis, consisting of treatment algorithm, and patient information tools (pamphlet and video). Methods: Literature searches were performed to develop an initial toolkit using Lynn's method for developing content‐valid clinical tools. Content and face validity were evaluated as per Lynn's method for determining content validity; the algorithm was evaluated by Canadian nephrology clinicians, while patient information tools were evaluated by clinicians and patients. Components were rated on a Likert scale for content relevance and on a 5‐point scale for face validity. After each round, the content validity index (CVI) score was calculated and revisions were made based on feedback. Findings: A total of 23 clinicians and 15 patients were interviewed across three validation rounds. After three rounds, the treatment algorithm achieved content (overall CVI = 0.93) and face (91% agreement) validity. Our patient information tools achieved content and face validity (pamphlet overall CVI = 0.99, 85.5% agreement; video overall CVI = 0.99, 90.5% agreement). Discussion: A treatment algorithm and patient information toolkit for the treatment of constipation in patients on hemodialysis were content and face validated via expert review. Further research will be needed to ascertain the effectiveness and implementation of this toolkit. [ABSTRACT FROM AUTHOR]

The Ottawa subarachnoid haemorrhage (SAH) rule and the Emerald SAH rule are clinical decision tools to aid in the decision for computed tomography (CT) of the head in patients attending an emergency department (ED) with acute non-traumatic headache. The objective of this study was to analyse the performance of these rules in a contemporary UK cohort. Methods We performed a retrospective external validation study. Patients undergoing CT of the head for the evaluation and treatment of non-traumatic headaches over a 6-month period in the ED at two tertiary centres were assessed. Each patient's Ottawa rule and Emerald rule were calculated and compared with their final diagnosis. Results The cohort consisted of 366 patients and there were 16 cases of SAH (based on CT findings or the presence of xanthochromia in cerebrospinal fluid). The Ottawa rule identified 288 patients requiring CT of the head. The sensitivity of the Ottawa rule was 100% (95% confidence interval (CI) 71--100%) and the specificity was 22% (95% CI 18--27%). The Emerald rule identified 267 patients who required CT, and achieved a sensitivity of 81% (95% CI 54--96%) and a specificity of 27% (95% CI 23--32%). Conclusions The Ottawa SAH rule correctly identified all patients with SAH in this contemporary cohort. The Emerald rule did not perform as well in this cohort and is unsuitable for clinical use. The Ottawa rule is a useful tool to aid in the decision for CT of the head in patients presenting with acute non-traumatic headache to the ED. [ABSTRACT FROM AUTHOR]

Background: Despite national guidelines recommending naloxone co-prescription with high-risk medications, rates remain low nationally. This was reflected at our institution with remarkably low naloxone prescribing rates. We sought to determine if a clinical decision support (CDS) tool could increase rates of naloxone co-prescribing with high-risk prescriptions., Methods:  An alert in the electronic health record was triggered upon signing an order for a high-risk opioid medication without a naloxone co-prescription. We examined all opioid prescriptions written by family and general internal medicine practitioners at the University of Iowa Hospitals and Clinics in outpatient encounters between November 30, 2020, and February 28, 2022. Once triggered by a high-risk prescription, the CDS tool had the option to choose an order set with an automatically selected co-prescription for naloxone along with patient instructions automatically added to the patient's after-visit summary (AVS). We examined the monthly percentage of patients receiving Schedule II opioid prescriptions ≥90 morphine milliequivalents (MME)/day who received concurrent naloxone prescriptions in the 12 months before the CDS went live and the three months following go-live., Results:  Concurrent naloxone prescriptions increased from 1.1% in the 12 months prior to implementation in November 2021 to 9.4% (p<0.001) during the post-intervention period across eight family medicine and internal medicine clinics., Discussion:  This single-center quality improvement project with retrospective analysis demonstrates the potential efficacy of a single CDS tool in increasing the rate of naloxone prescription. The impact of such prescribing on overall mortality requires further research., Conclusions: The CDS tool was easy to implement and improved rates of appropriate naloxone co-prescribing., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Cramer et al.)

• ICHRON predicted a 3-year chronic disease among an Australian validation cohort. • ICHRON is valuable for primary care patients in distinct locales. • ICHRON was found to be more predictive among Aboriginal and Torres Islanders. • ICHRON can be calculated within the EHR using standardized laboratory parameters. The Intermountain Chronic Disease Risk Score (ICHRON) is a primary prevention risk prediction tool that uses commonly ordered blood tests and is designed to be calculated by the electronic health record. ICHRON was highly predictive of 3-year chronic disease (ChrD) diagnosis in an internal validation; however, external validation is needed. ICHRON was calculated among patients from a region of Australia using sex-specific weightings of age and components of the comprehensive metabolic panel and the complete blood count. Original ICHRON weightings and risk stratification thresholds from the US-based derivation at Intermountain Healthcare were used. ICHRON was evaluated as a predictor of an incident 3-year ChrD diagnosis (coronary artery disease, myocardial infarction, heart failure, atrial fibrillation, stroke, dementia, diabetes, renal failure, chronic obstructive pulmonary disease, and peripheral vascular disease). A total 5,512 females (49.6 ± 19.2) and 3,461 males (53.0 ± 18.6) were studied. Among females, 50.3%, 33.7% and 16.0% were low, moderate, and high-risk, respectively; and for males, 39.6%, 35.0%, and 25.4%. Frequency of a 3-year ChrD diagnosis among females was 2.2%, 8.5%, and 15.9% for low, moderate, and high-risk groups, respectively, and 4.7%, 9.7%, and 20.0% among males. C-statistics were 0.726 (0.700, 0.752) for females and 0.694 (0.665, 0.724) for males. ICHRON predicted ChrD diagnosis at 3-years among an external, geographically distant validation cohort. These findings show the value of ICHRON for primary care patients in distinct locales. Additionally, electronic calculation of ICHRON empowers the clinical use of this tool to identify and differentially manage and treat high-risk patients. [ABSTRACT FROM AUTHOR]

Background: Satisfactory tools to preclude low-risk patients from intensive diagnostic testing for primary aldosteronism (PA) are lacking. Therefore, we aimed to develop a decision tool to determine which patients with difficult-to-control hypertension have a low probability of PA, thereby limiting the exposure to invasive testing while at the same time increasing the efficiency of testing in the remaining patients. Methods: Data from consecutive patients with difficult-to-control hypertension, analysed through a standardized diagnostic protocol between January 2010 and October 2017 (n = 824), were included in this cross-sectional study. PA was diagnosed by a combined approach: 1) elevated aldosterone-to-renin ratio (> 5.0 pmol/fmol/s), confirmed with 2) non-suppressible aldosterone after standardized saline infusion (≥280 pmol/L). Multivariable logistic regression analyses including seven pre-specified clinical variables (age, systolic blood pressure, serum potassium, potassium supplementation, serum sodium, eGFR and HbA1c) was performed. After correction for optimism, test reliability, discriminative performance and test characteristics were determined. Results: PA was diagnosed in 40 (4.9%) of 824 patients. Predicted probabilities of PA agreed well with observed frequencies and the c-statistic was 0.77 (95% confidence interval (95%CI) 0.70–0.83). Predicted probability cut-off values of 1.0–2.5% prevented unnecessary testing in 8–32% of the patients with difficult-to-control hypertension, carrying sensitivities of 0.98 (95%CI 0.96–0.99) and 0.92 (0.83–0.97), and negative predictive values of 0.99 (0.98–1.00) and 0.99 (0.97–0.99). Conclusions: With a decision tool, based on seven easy-to-measure clinical variables, patients with a low probability of PA can be reliably selected and a considerable proportion of patients with difficult-to-control hypertension can be spared intensive diagnostic testing. [ABSTRACT FROM AUTHOR]

Introduction: CHA2DS2‐VASc and CHADS2 are computationally simple risk prediction tools used to guide anticoagulation decisions for stroke prophylaxis, but they have modest risk discrimination ability and use static dichotomous variables. The Intermountain Mortality Risk Scores (IMRS) are dynamic decision tools using standard clinical laboratory tests. This study derived new stroke prediction scores using variables from both CHA2DS2‐VASc and IMRS. Methods and Results: In outpatients with first atrial fibrillation (AF) diagnosis at the Intermountain Healthcare (females, n = 26 063 males, n = 29 807), sex‐specific "IMRS‐VASc" scores were derived using variables from CHA2DS2‐VASc, warfarin use, the complete blood count, and the comprehensive metabolic profile. Validation was performed in an independent Intermountain outpatient AF cohort (females, n = 11 021; males, n = 12 641). Stroke occurred among 3.1% and 3.1% of females and 2.3% and 2.5% of males in derivation and validation groups, respectively. IMRS‐VASc stratified stroke with similar ability in derivation (c‐statistics, females: c = 0.703, males: c = 0.697) and validation groups (females: c = 0.681, males: c = 0.685). CHA2DS2‐VASc (females: c = 0.581 and c = 0.605; males: c = 0.616 and c = 0.613 in derivation and validation, respectively) and CHADS2 (females: c = 0.581 and c = 0.608; males: c = 0.620 and c = 0.621 in derivation and validation, respectively) were substantially weaker stroke predictors. IMRS was the strongest mortality predictor (females: c = 0.783 and c = 0.782; males: c = 0.796 and c = 0.794 in derivation and validation, respectively) and all scores were poor at predicting bleeding risk. Conclusions: A temporally dynamic risk score, IMRS‐VASc was derived and validated as a predictor of stroke in outpatients with AF. IMRS‐VASc requires further validation and the evaluation of its use in guiding care and treatment decisions for patients with AF. [ABSTRACT FROM AUTHOR]

Background: We recently introduced a clinical practice pathway for the management of asthma that uses the Pediatric Respiratory Assessment Measure (PRAM) to guide emergency department (ED) treatment and disposition. The pathway recommends discharge for patients who achieve improvement to PRAM <4 at 1 hour after the last bronchodilator. We evaluated practice variation and patient outcomes associated with PRAM-directed disposition recommendations. Methods: We conducted a retrospective cohort study of children aged 2 to 17 years treated for moderate asthma (PRAM score 4–7) using our asthma clinical pathway. We measured 1) the proportion of children discharged per pathway criteria who returned to our ED within 24 hours and 2) the proportion of children observed beyond the pathway discharge criteria who deteriorated (PRAM =4). Results: We analyzed 385 patient records from September 2013 to February 2015. Among 145 (37.7%) patients discharged per pathway criteria, 4 (4/145; 2.8%) returned within 24 hours. The remaining 240 (62.2%) were observed beyond the pathway discharge criteria; 76/240 (31.7%) had a subsequent deterioration (PRAM score = 4) and 25/240 (10.4%) were hospitalized. Of those who deteriorated, 46/76 (60.5%) worsened within the first additional hour of observation. Conclusion: We observed significant deviation from our PRAM-directed pathway discharge criteria and that a significant proportion of observed patients experienced clinical deterioration beyond the first hour of observation. We recommend observing children with moderate asthma for 2 or 3 hours from last bronchodilator therapy if PRAM < 4 is maintained, to capture the majority (97.7% or 99.7%) of patients who require further intervention and hospitalization. [ABSTRACT FROM AUTHOR]

Despite the understanding that wounds are a common problem affecting the individual, the health service and society as a whole, there continues to be a lack of a systematic, structured, evidence-based approach to wound management. The TIME principle was first published in 2003,1 and has since been integrated by many into clinical practice and research. However, this tool has been criticised for its tendency to focus mainly on the wound rather than on the wider issues that the patient is presenting with. At an expert meeting held in London in 2018, this conundrum was addressed and the TIME clinical decision support tool (CDST) was elaborated upon. This article introduces the TIME CDST, explains why it is required and describes how its use is likely to benefit patients, clinicians and health-service organisations. It also explores the framework in detail, and shows why this simple and accessible framework is robust enough to facilitate consistency in the delivery of wound care and better patient outcomes. Finally, it outlines the next steps for the rollout, use and evaluation of the impact of the TIME CDST. [ABSTRACT FROM AUTHOR]

The timely and accurate adverse drug reactions (ADR) assessment is vital for effective patient management and healthcare delivery. The Naranjo Algorithm is a widely recognized tool for determining the probability that a drug induces a given ADR. However, the process can be time-consuming and susceptible to human error. This study introduces a Python-based console application (Python Software Foundation, Wilmington, Delaware, United States) designed to automate the Naranjo Algorithm for ADR causality assessment. The application was developed using Python 3.11.4 on a Windows 11 system (Microsoft Corporation, Redmond, Washington, United States) and compiled in Notepad (Microsoft Corporation), a basic text editor, highlighting its accessibility and ease of use in various settings. User input is solicited for each question in the Naranjo Algorithm, validated for acceptable entries, and subsequently scored. The final score categorizes the reaction into Doubtful, Possible, Probable, or Definite ADR, facilitating rapid clinical decision-making. Preliminary validation shows promising reliability and effectiveness, making it a valuable asset in research and clinical settings for assessment., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Kumar et al.)

While most children with mild traumatic brain injury (mTBI) without intracranial injury (ICI) can be safely discharged home from the emergency department, many are admitted to the hospital. To support evidence-based practice, we developed a decision tool to help guide hospital admission decisions. This study was a secondary analysis of a prospective study conducted in 25 emergency departments. We included children under 18 years who had Glasgow Coma Scale score 13–15 head injuries and normal computed tomography scans or skull fractures without significant depression. We developed a multi-variable model that identified risk factors for extended inpatient management (EIM; defined as hospitalization for 2 or more nights) for TBI, and used this model to create a clinical risk score. Among 14,323 children with mTBI without ICI, 20% were admitted to the hospital but only 0.76% required EIM for TBI. Key risk factors for EIM included Glasgow Coma Scale score less than 15 (odds ratio [OR] = 8.1; 95% confidence interval [CI] 4.0–16.4 for 13 vs. 15), drug/alcohol Intoxication (OR = 5.1; 95% CI 2.4–10.7), neurological Deficit (OR = 3.1; 95% CI 1.4–6.9), Seizure (OR = 3.7; 95% CI 1.8–7.8), and Skull fracture (odds ratio [OR] 24.5; 95% CI 16.0–37.3). Based on these results, the CIDSS2 risk score was created. The model C-statistic was 0.86 and performed similarly in children less than (C = 0.86) and greater than or equal to 2 years (C = 0.86). The CIDSS2 score is a novel tool to help physicians identify the minority of children with mTBI without ICI at increased risk for EIM, thereby potentially aiding hospital admission decisions. [ABSTRACT FROM AUTHOR]

Background: Early-onset sepsis (EOS) is a potentially fatal condition that affects about 0.3–0.8/1,000 infants born at ≥35 weeks’ gestation in developed countries. Current EOS management algorithms result in 8–15% of infants receiving antibiotics for suspected sepsis. The Neonatal Sepsis Calculator provides evidence-based estimates of individual sepsis risk, but data on its clinical application is limited. Objectives: To evaluate the feasibility, safety, and effect on the newborn infants that were investigated and that received antibiotic treatment for suspected EOS following the introduction of the Neonatal Sepsis Calculator. Methods: This was a prospective, observational, single-centre cohort study comparing the rates of newborn infants born at ≥35 weeks’ gestation requiring evaluation and/or treatment for suspected EOS in a large tertiary perinatal centre before versus after the prospective introduction of the Neonatal Sepsis Calculator (Epoch 1: October 2014 to January 2015 vs. Epoch 2: July to December 2016). Results: There were 1,732 and 2,502 eligible infants born during Epochs 1 and 2, respectively. Of these, 425 (24.2%) and 530 (21.2%), respectively, were admitted to the neonatal unit. The proportion of infants investigated for sepsis decreased from 15.2 to 11.1%, and that of infants treated with antibiotics from 12.0 to 7.6%. One case of EOS occurred during each Epoch. Conclusions: The implementation of the Neonatal Sepsis Calculator was feasible and safe in our unit. Application of this clinical decision support tool may reduce the number of infants undergoing investigations and empirical treatment for suspected EOS. [ABSTRACT FROM AUTHOR]

Background: Lung cancer is the leading cause of cancer deaths. Around 70% of patients first presenting to specialist care have advanced disease, at which point current treatments have little effect on survival. The issue for primary care is how to recognise patients earlier and investigate appropriately. This requires an assessment of the risk of lung cancer.Aim: The aim of this study was to systematically review the existing risk prediction tools for patients presenting in primary care with symptoms that may indicate lung cancer DESIGN AND SETTING: Systematic review of primary care data.Method: Medline, PreMedline, Embase, the Cochrane Library, Web of Science, and ISI Proceedings (1980 to March 2016) were searched. The final list of included studies was agreed between two of the authors, who also appraised and summarised them.Results: Seven studies with between 1482 and 2 406 127 patients were included. The tools were all based on UK primary care data, but differed in complexity of development, number/type of variables examined/included, and outcome time frame. There were four multivariable tools with internal validation area under the curves between 0.88 and 0.92. The tools all had a number of limitations, and none have been externally validated, or had their clinical and cost impact examined.Conclusion: There is insufficient evidence for the recommendation of any one of the available risk prediction tools. However, some multivariable tools showed promising discrimination. What is needed to guide clinical practice is both external validation of the existing tools and a comparative study, so that the best tools can be incorporated into clinical decision tools used in primary care. [ABSTRACT FROM AUTHOR]

Introduction This case study aimed to enhance the traceability and retrieval accuracy of ChatGPT-4 in medical text by employing a step-by-step systematic approach. The focus was on retrieving clinical answers from three international guidelines on diabetic ketoacidosis (DKA). Methods A systematic methodology was developed to guide the retrieval process. One question was asked per guideline to ensure accuracy and maintain referencing. ChatGPT-4 was utilized to retrieve answers, and the 'Link Reader' plug-in was integrated to facilitate direct access to webpages containing the guidelines. Subsequently, ChatGPT-4 was employed to compile answers while providing citations to the sources. This process was iterated 30 times per question to ensure consistency. In this report, we present our observations regarding the retrieval accuracy, consistency of responses, and the challenges encountered during the process. Results Integrating ChatGPT-4 with the 'Link Reader' plug-in demonstrated notable traceability and retrieval accuracy benefits. The AI model successfully provided relevant and accurate clinical answers based on the analyzed guidelines. Despite occasional challenges with webpage access and minor memory drift, the overall performance of the integrated system was promising. The compilation of the answers was also impressive and held significant promise for further trials. Conclusion The findings of this case study contribute to the utilization of AI text-generation models as valuable tools for medical professionals and researchers. The systematic approach employed in this case study and the integration of the 'Link Reader' plug-in offer a framework for automating medical text synthesis, asking one question at a time before compilation from different sources, which has led to improving AI models' traceability and retrieval accuracy. Further advancements and refinement of AI models and integration with other software utilities hold promise for enhancing the utility and applicability of AI-generated recommendations in medicine and scientific academia. These advancements have the potential to drive significant improvements in everyday medical practice., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Hamed et al.)

Background: This study aimed to develop a novel clinical approach to predict intensive care unit (ICU) admission and mortality among coronavirus disease 2019 (COVID-19) patients in the emergency department (ED)., Methods: A retrospective cohort study was conducted including adults ≥ 18 years diagnosed with COVID-19 in the emergency department and admitted to the ICU between March and July 2020 in an academic hospital. The outcome variables were mortality and ICU admission. Additional variables that were collected included sex, age, comorbidities, symptom phenotype, and laboratory (lymphopenia) and imaging findings. A logistic regression model was used to construct and validate the risk models., Results: A total of 808 patients were included in the study; 61.9% were men. The mean age was 57.8 ± 15.9 years, and high blood pressure (HBP) was the most prevalent comorbidity (31.8%). Seventy-six (9.4%) patients were admitted to the ICU. Age ≥ 60 years, chronic obstructive pulmonary disease (COPD), lymphopenia, and imaging findings correlated with mortality. Age ≥ 60 years, lymphopenia (<1,000 cells per microliter), and hypothyroidism correlated with ICU admission. These variables were incorporated into a scoring system (Comorbidities, Radiographic findings, Age, and Lymphopenia (CORAL) tool) to predict mortality and ICU admission., Conclusions: Our Comorbidities, Radiographic findings, Age, and Lymphopenia (CORAL) tool is a practical tool for different clinical settings independent of access to advanced medical resources or technologies. CORAL is suitable for emergency physicians in low- and middle-income countries., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Castro-Vásquez et al.)

Introduction: Vedolizumab clinical decision support tool (VDZ-CDST) predicts response to vedolizumab, but whether this tool also predicts efficacy of other drugs in Crohn's disease (CD) is unknown. This study aimed to assess the value of VDZ-CDST to predict vedolizumab and ustekinumab efficacy in patients with CD., Patients and Methods: We included consecutive CD patients refractory or intolerant to anti-TNF who started either vedolizumab or ustekinumab in 5 university hospitals between May 2014 and August 2018. The main end points were the rates of clinical remission and steroid-free clinical remission (SFCR) in each group of VDZ-CDST at week 48., Results: One hundred eighty patients were included; 94 received vedolizumab (VDZ-CDST ≤13: 32; VDZ-CDST >13 and ≤19: 52; VDZ-CDST >19: 10), and 86 received ustekinumab (VDZ-CDST ≤13: 16; VDZ-CDST >13 and ≤19: 60; VDZ-CDST >19: 10). At week 48 in the vedolizumab group, clinical remission and SFCR were reached in 9.4% with a VDZ-CDST ≤13, in 38.5% and 28.8% with a VDZ-CDST >13 and ≤19, respectively, and in 80.0% with a VDZ-CDST >19 (P < 0.0001 and P < 0.0001, respectively). In the ustekinumab cohort, clinical remission and SFCR were reached in 43.8% and 37.5% with a VDZ-CDST ≤13, in 55.0% and 50.0% with a VDZ-CDST >13 and ≤19, and 50.0% with a VDZ-CDST >19, respectively (P = 0.65 and P = 0.46, respectively). VDZ-CDST identified SFCR with an area under the curve of 0.69 (95% CI, 0.57-0.82) for vedolizumab and 0.52 (95% CI, 0.40-0.65) for ustekinumab., Conclusion: The VDZ-CDST predicts clinical remission and SFCR at week 48 for vedolizumab but not for ustekinumab in CD patients refractory or intolerant to anti-TNF., (© 2021 Crohn’s & Colitis Foundation. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Total knee arthroplasty is the standard surgical treatment for end-stage osteoarthritis. Although widely accepted as a successful procedure, approximately 30% of patients are not satisfied due to non-optimal postoperative outcomes. Clinical decision support tools that are able to accurately predict post-surgery outcomes would assist in providing individualized advice or services to help alleviate possible issues, resulting in significant benefits to both the healthcare system and individuals.Methods: Five databases (Ovid Medline, Ovid EMBASE, CINAHL complete, Cochrane Library, and Scopus) were searched for the key phrases "knee replacement" or "knee arthroplasty" and "decision support tool," "decision tool," "predict∗ tool," "predict∗ model," "algorithm" or "nomogram." Searches were limited to peer-reviewed journal articles published between January 2000 and June 2019. Reference lists of included articles were examined. Authors came to a consensus on the final list of included articles.Results: Eighteen articles were included for review. Most models reported low predictive success and inability to externally validate. Both candidate and final predictor variables were inconsistent between studies. Only 1 model was considered strongly predictive (AUROC >0.8), and only 2 studies were able to externally validate their developed model. In general, models that performed well used large patient numbers, were tested on similar demographics, and used either nonlinear input transformations or a completely nonlinear model.Conclusion: Some models do show promise; however, there remains the question of whether the reported predictive success can continue to be replicated. Furthermore, clinical applicability and interpretation of predictive tools should be considered during development. [ABSTRACT FROM AUTHOR]

Objective: Post-myocardial infarction (MI) care is crucial to preventing recurrent major adverse cardiovascular events (MACE), but can be complicated to personalise. A tool is needed that effectively stratifies risk of cardiovascular (CV) events 1-3 years after MI but is also clinically usable., Methods: Patients surviving ≥1 year after an index MI with ≥1 risk factor for recurrent MI (ie, age ≥65 years, prior MI, multivessel coronary disease, diabetes, glomerular filtration rate <60 mL/min/1.73 m 2 ) were studied. Cox regression derived sex-specific Intermountain Major Adverse Cardiovascular Events (IMACE) risk scores for the composite of 1-year to 3-year MACE (CV death, MI or stroke). Derivation was performed in 70% of subjects (n=1342 women; 3047 men), with validation in the other 30% (n=576 women; 1290 men). Secondary validations were also performed., Results: In women, predictors of CV events were glucose, creatinine, haemoglobin, platelet count, red cell distribution width (RDW), age and B-type natriuretic peptide (BNP); among men, they were potassium, glucose, blood urea nitrogen, haematocrit, white blood cell count, RDW, mean platelet volume, age and BNP. In the primary validation, in women, IMACE ranged from 0 to 11 (maximum possible: 12) and had HR=1.44 per +1 score (95% CI 1.29 to 1.61; P<0.001); men had IMACE range 0-14 (maximum: 16) and HR=1.29 per +1 score (95% CI 1.20 to 1.38; P<0.001). IMACE ≥5 in women (≥6 in men) showed strikingly higher MACE risk., Conclusions: Sex-specific risk scores strongly stratified 1-year to 3-year post-MI MACE risk. IMACE is an inexpensive, dynamic, electronically delivered tool for evaluating and better managing post-MI patient care., Competing Interests: Competing interests: BDH is an inventor of IMRS and two readmission risk scores that are licensed to CareCentra for integration into their products. BDH is PI of grants funded by Intermountain Healthcare’s Foundry Innovation Program, the Intermountain Research and Medical Foundation, CareCentra, AstraZeneca and GlaxoSmithKline for the development and/or implementation of clinical risk scores. DB, GLH and NDK are employees of AstraZeneca.