Development and validation of a predictive model for major complications after extracorporeal shockwave lithotripsy in patients with ureteral stones: based on a large prospective cohort

The risk factors of complications after SWL are not well characterized. Therefore, based on a large prospective cohort, we aimed to develop and validate a nomogram for predicting major complications after extracorporeal shockwave lithotripsy (SWL) in patients with ureteral stones. The development cohort included 1522 patients with ureteral stones who underwent SWL between June 2020 and August 2021 in our hospital. Five hundred and fifty-three patients with ureteral stones participated in the validation cohort from September 2020 to April 2022. The data were prospectively recorded. Backward stepwise selection was applied using the likelihood ratio test with Akaike's information criterion as the stopping rule. The efficacy of this predictive model was assessed concerning its clinical usefulness, calibration, and discrimination. Finally, 7.2% (110/1522) of patients in the development cohort and 8.7% (48/553) of those in the validation cohort suffered from major complications. We identified five predictive factors for major complications: age, gender, stone size, Hounsfield unit of stone, and hydronephrosis. This model showed good discrimination with an area under the receiver operating characteristic curves of 0.885 (0.872-0.940) and good calibration (P = 0.139). The decision curve analysis showed that the model was clinically valuable. In this large prospective cohort, we found that older age, female gender, higher Hounsfield unit, size, and grade of hydronephrosis were risk predictors of major complications after SWL. This nomogram will be helpful in preoperative risk stratification to provide individualized treatment recommendations for each patient. Furthermore, early identification and appropriate management of high-risk patients may decrease postoperative morbidity.

Comparing GPs' antibiotic prescribing decisions to a clinical prediction rule: an online vignette study

BACKGROUND

The 'STARWAVe' clinical prediction rule (CPR) uses seven factors to guide risk assessment and antibiotic prescribing in children with cough (Short illness duration, Temperature, Age, Recession, Wheeze, Asthma, Vomiting).

AIM

To assess the influence of STARWAVe factors on GPs' unaided risk assessments and prescribing decisions.

DESIGN AND SETTING

Clinical vignettes administered to 188 UK GPs online.

METHOD

GPs were randomly assigned to view 32 (out of a possible 64) vignettes online depicting children with cough. The vignettes comprised the seven STARWAVe factors, which were varied systematically. For each vignette, GPs assessed risk of deterioration in one of two ways (sliding-scale versus risk-category selection) and indicated whether they would prescribe antibiotics. Finally, GPs saw an additional vignette, suggesting that the parent was concerned. Mixed-effects regressions were used to measure the influence of STARWAVe factors, risk-elicitation method, and parental concern on GPs' assessments and decisions.

RESULTS

Six STARWAVe risk factors correctly increased GPs' risk assessments (bssliding-scale≥0.66, odds ratios [ORs]category-selection≥1.75, Ps≤0.001), whereas one incorrectly reduced them (short illness duration: b sliding-scale -0.30, ORcategory-selection 0.80, P≤0.039). Conversely, one STARWAVe factor increased prescribing odds (temperature: OR 5.22, P<0.001), whereas the rest either reduced them (short illness duration, age, and recession: ORs≤0.70, Ps<0.001) or had no significant impact (wheeze, asthma, and vomiting: Ps≥0.065). Parental concern increased risk assessments (b sliding-scale 1.29, ORcategory-selection 2.82, P≤0.003) but not prescribing odds (P = 0.378).

CONCLUSION

GPs use some, but not all, STARWAVe factors when making unaided risk assessments and prescribing decisions. Such discrepancies must be considered when introducing CPRs to clinical practice.

Derivation and validation of clinical prediction rules for diagnosis of infectious mononucleosis: a prospective cohort study

OBJECTIVES

Infectious mononucleosis (IM) is a clinical syndrome that is characterised by lymphadenopathy, fever and sore throat. Although generally not considered a serious illness, IM can lead to significant loss of time from school or work due to profound fatigue, or the development of chronic illness. This study aimed to derive and externally validate clinical prediction rules (CPRs) for IM caused by Epstein-Barr virus (EBV).

DESIGN

Prospective cohort study.

SETTING AND PARTICIPANTS

328 participants were recruited prospectively for the derivation cohort, from seven university-affiliated student health centres in Ireland. Participants were young adults (17-39 years old, mean age 20.6 years) with sore throat and one other additional symptom suggestive of IM. The validation cohort was a retrospective cohort of 1498 participants from a student health centre at the University of Georgia, USA.

MAIN OUTCOME MEASURES

Regression analyses were used to develop four CPR models, internally validated in the derivation cohort. External validation was carried out in the geographically separate validation cohort.

RESULTS

In the derivation cohort, there were 328 participants, of whom 42 (12.8%) had a positive EBV serology test result. Of 1498 participants in the validation cohort, 243 (16.2%) had positive heterophile antibody tests for IM. Four alternative CPR models were developed and compared. There was moderate discrimination and good calibration for all models. The sparsest CPR included presence of enlarged/tender posterior cervical lymph nodes and presence of exudate on the pharynx. This model had moderate discrimination (area under the receiver operating characteristic curve (AUC): 0.70; 95% CI: 0.62-0.79) and good calibration. On external validation, this model demonstrated reasonable discrimination (AUC: 0.69; 95% CI: 0.67-0.72) and good calibration.

CONCLUSIONS

The alternative CPRs proposed can provide quantitative probability estimates of IM. Used in conjunction with serological testing for atypical lymphocytosis and immunoglobulin testing for viral capsid antigen, CPRs can enhance diagnostic decision-making for IM in community settings.

Comparing blood biomarkers to clinical decision rules to select patients suspected of traumatic brain injury for head computed tomography

INTRODUCTION

Traumatic brain injury (TBI) is a major public health concern in the U.S. Recommendations for patients admitted in the emergency department (ED) to receive head computed tomography (CT) scan are currently guided by various clinical decision rules.

OBJECTIVE

To compare how a blood biomarker approach compares with clinical decision rules in terms of predicting a positive head CT in adult patients suspected of TBI.

METHODS

We retrospectively identified patients transported to our emergency department and underwent a noncontrast head CT due to suspicion of TBI and who had blood samples available. Published thresholds for serum and plasma glial fibrillary acidic protein (GFAP), ubiquitin carboxyl-terminal hydrolase-L1 (UCH-L1), and serum S100β were used to make CT recommendations. These blood biomarker-based recommendations were compared to those achieved under widely used clinical head CT decision rules (Canadian, New Orleans, NEXUS II, and ACEP Clinical Policy).

RESULTS

Our study included 463 patients, of which 122 (26.3%) had one or more abnormalities presenting on head CT. Individual blood biomarkers achieved high negative predictive value (NPV) for abnormal head CT findings (88%-98%), although positive predictive value (PPV) was consistently low (25%-42%). A composite biomarker-based decision rule (GFAP+UCH-L1)'s NPV of 100% and PPV of 29% were comparable or better than those achieved under the clinical decision rules.

CONCLUSION

Blood biomarkers perform at least as well as clinical rules in terms of selecting TBI patients for head CT and may be easier to implement in the clinical setting. A prospective study is necessary to validate this approach.

Development of clinical prediction rule for the requirement of endoscopic papillary large balloon dilation (EPLBD) on endoscopic CBD stone clearance

INTRODUCTION

To develop a simplified scoring system for clinical prediction of difficulty in CBD stone removal to assist endoscopists working in resource-limited settings in deciding whether to proceed with an intervention or refer patients to a center capable of performing additional procedures and interventions.

METHODS

This study included patients with CBD stones who underwent ERCP at Pattani Hospital between August 2017 and December 2021. Retrospective cohort data was collected and patients were categorized into two groups: bile duct stones successfully treated by endoscopic biliary sphincterotomy and extraction compared to the former method combined with EPLBD. We explored potential predictors using multivariable logistic regression. The chosen logistic coefficients were transformed into a scoring system based on risk with internal validation via bootstrapping procedure.

RESULTS

Among the 155 patients who had successful endoscopic therapy for bile duct stones, there were 79 (50.97%) cases of endoscopic biliary sphincterotomy, EPLBD and extraction versus 76 (49.03%) cases without EPLBD. The factors used to derive a scoring system included the size of CBD stones >15 mm, the difference between the stone and distal CBD diameter >2mm, distal CBD arm length <36 mm and stone shape. The score-based model's area under ROC was 0.88 (95% CI: 0.83, 0.93). For clinical use, the range of scores from 0 to 16, was divided into two subcategories based on CBD stone removal difficulty requiring EPLBD to derive the PPV. For scores <5 and ≥ 5, the PPV was 23.40 (p <0.001) and 93.44 (p <0.001) respectively. The Bootstrap sampling method indicated a prediction ability of 0.88 (AuROC, 95% CI: 0.83, 0.94).

CONCLUSION

This scoring system has acceptable prediction performance in assisting endoscopists in their choice of stone removal procedure.

Derivation and Validation of a Clinical Prediction Rule for Upper Limb Functional Outcomes After Traumatic Cervical Spinal Cord Injury

IMPORTANCE

Traumatic cervical spinal cord injury (SCI) can result in debilitating paralysis. Following cervical SCI, accurate early prediction of upper limb recovery can serve an important role in guiding the appropriateness and timing of reconstructive therapies.

OBJECTIVE

To develop a clinical prediction rule to prognosticate upper limb functional recovery after cervical SCI.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study was a retrospective review of a longitudinal cohort study including patients enrolled in the National SCI model systems (SCIMS) database in US. Eligible patients were 15 years or older with tetraplegia (neurological level of injury C1-C8, American Spinal Cord Injury Association [ASIA] impairment scale [AIS] A-D), with early (within 1 month of SCI) and late (1-year follow-up) clinical examinations from 2011 to 2016. The data analysis was conducted from September 2021 to June 2022.

MAIN OUTCOMES AND MEASURES

The primary outcome was a composite of dependency in eating, bladder management, transfers, and locomotion domains of functional independence measure at 1-year follow-up. Each domain ranges from 1 to 7 with a lower score indicating greater functional dependence. Composite dependency was defined as a score of 4 or higher in at least 3 chosen domains. Multivariable logistic regression was used to predict the outcome based on early neurological variables. Discrimination was quantified using C statistics, and model performance was internally validated with bootstrapping and 10-fold cross-validation. The performance of the prediction score was compared with AIS grading. Data were split into derivation (2011-2014) and temporal-validation (2015-2016) cohorts.

RESULTS

Among 2373 patients with traumatic cervical SCI, 940 had complete 1-year outcome data (237 patients [25%] aged 60 years or older; 753 men [80%]). The primary outcome was present in 118 patients (13%), which included 92 men (78%), 83 (70%) patients who were younger than 60 years, and 73 (62%) patients experiencing AIS grade A SCI. The variables significantly associated with the outcome were age (age 60 years or older: OR, 2.31; 95% CI, 1.26-4.19), sex (men: OR, 0.60; 95% CI, 0.31-1.17), light-touch sensation at C5 (OR, 0.44; 95% CI, 0.44-1.01) and C8 (OR, 036; 95% CI, 0.24-0.53) dermatomes, and motor scores of the elbow flexors (C5) (OR, 0.74; 95% CI, 0.60-0.89) and wrist extensors (C6) (OR, 0.61; 95% CI, 0.49-0.75). A multivariable model including these variables had excellent discrimination in distinguishing dependent from independent patients in the temporal-validation cohort (C statistic, 0.90; 95% CI, 0.88-0.93). A clinical prediction score (range, 0 to 45 points) was developed based on these measures, with higher scores increasing the probability of dependency. The discrimination of the prediction score was significantly higher than from AIS grading (change in AUC, 0.14; 95% CI, 0.10-0.18; P < .001).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that this prediction rule may help prognosticate upper limb function following cervical SCI. This tool can be used to set patient expectations, rehabilitation goals, and aid decision-making regarding the appropriateness and timing for upper limb reconstructive surgeries.

Canadian infants presenting with Brief Resolved Unexplained Events (BRUEs) and validation of clinical prediction rules for risk stratification: a protocol for a multicentre, retrospective cohort study

INTRODUCTION

Brief Resolved Unexplained Events (BRUEs) are a common presentation among infants. While most of these events are benign and self-limited, guidelines published by the American Academy of Pediatrics inaccurately identify many patients as higher-risk of a serious underlying aetiology (positive predictive value 5%). Recently, new clinical prediction rules have been derived to more accurately stratify patients. This data were however geographically limited to the USA, with no large studies to date assessing the BRUE population in a different healthcare setting. The study's aim is to describe the clinical management and outcomes of infants presenting to Canadian hospitals with BRUEs and to externally validate the BRUE clinical prediction rules in identified cases.

METHODS AND ANALYSIS

This is a multicentre retrospective study, conducted within the Canadian Paediatric Inpatient Research Network (PIRN). Infants (<1 year) presenting with a BRUE at one of 11 Canadian paediatric centres between 1 January 2017 and 31 December 2021 will be included. Eligible patients will be identified using diagnostic codes.The primary outcome will be the presence of a serious underlying illness. Secondary outcomes will include BRUE recurrence and length of hospital stay. We will describe the rates of hospital admissions and whether hospitalisation was associated with an earlier diagnosis or treatment. Variation across Canadian hospitals will be assessed using intraclass correlation coefficient. To validate the newly developed clinical prediction rule, measures of goodness of fit will be evaluated. For this validation, a sample size of 1182 is required to provide a power of 80% to detect patients with a serious underlying illness with a significance level of 5%.

ETHICS AND DISSEMINATION

Ethics approval has been granted by the UBC Children's and Women's Research Board (H21-02357). The results of this study will be disseminated as peer-reviewed manuscripts and presentations at national and international conferences.

Post-Concussion Symptoms Rule: Derivation and Validation of a Clinical Decision Rule for Early Prediction of Persistent Symptoms after a Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is a common problem. Depending on diagnostic criteria, 13 to 62% of those patients develop persistent post-concussion symptoms (PPCS). The main objective of this prospective multi-center study is to derive and validate a clinical decision rule (CDR) for the early prediction of PPCS. Patients aged ≥14 years were included if they presented to one of our seven participating emergency departments (EDs) within 24 h of an mTBI. Clinical data were collected in the ED, and symptom evolution was assessed at 7, 30 and 90 days post-injury using the Rivermead Post-Concussion Questionnaire (RPQ). The primary outcome was PPCS at 90 days after mTBI. A predictive model called the Post-Concussion Symptoms Rule (PoCS Rule) was developed using the methodological standards for CDR. Of the 1083 analyzed patients (471 and 612 for the derivation and validation cohorts, respectively), 15.6% had PPCS. The final model included the following factors assessed in the ED: age, sex, history of prior TBI or mental health disorder, headache in ED, cervical sprain and hemorrhage on computed tomography. The 7-day follow-up identified additional risk factors: headaches, sleep disturbance, fatigue, sensitivity to light, and RPQ ≥21. The PoCS Rule had a sensitivity of 91.4% and 89.6%, a specificity of 53.8% and 44.7% and a negative predictive value of 97.2% and 95.8% in the derivation and validation cohorts, respectively. The PoCS Rule will help emergency physicians quickly stratify the risk of PPCS in mTBI patients and better plan post-discharge resources.

Use of a penicillin allergy clinical decision rule to enable direct oral penicillin provocation: an international multicentre randomised control trial in an adult population (PALACE): study protocol

INTRODUCTION

Penicillin allergies are highly prevalent in the healthcare setting and associated with the prescription of second-line inferior antibiotics. More than 85% of all penicillin allergy labels can be removed by skin testing and 96%-99% of low-risk penicillin allergy labels can be removed by direct oral challenge. An internally and externally validated clinical assessment tool for penicillin allergy, PEN-FAST, can identify a low-risk penicillin allergy without the need for skin testing; a score of less than 3 has a negative predictive value of 96.3% (95% CI, 94.1 to 97.8) for the presence of a penicillin allergy. It is hypothesised that PEN-FAST is a safe and effective tool for assessing penicillin allergy in an outpatient clinic setting.

METHODS AND ANALYSIS

This is an international, multicentre randomised control trial using the PEN-FAST tool to risk-stratify penicillin allergy labels in adult outpatients. The study's primary objective is to evaluate the non-inferiority of using PEN-FAST score-guided management with direct oral challenge compared with standard care (defined as prick and intradermal skin testing followed by oral penicillin challenge). Participants will be randomised 1:1 to the intervention arm (direct oral penicillin challenge) or standard of care arm (skin testing followed by oral penicillin challenge, if skin testing is negative). The sample size of 380 randomised patients (190 per treatment arm) is required to demonstrate non-inferiority.

ETHICS AND DISSEMINATION

The study will be performed according to the guidelines of the Helsinki Declaration and is approved by the Austin Health Human Research Ethics Committee (HREC/62425/Austin-2020) in Melbourne Australia, Vanderbilt University Institutional Review Board (IRB #202174) in Tennessee, USA, Duke University Institutional Review Board (IRB #Pro00108461) in North Carolina, USA and McGill University Health Centre Research Ethics Board in Canada (PALACE/2022-7605). The results of this study will be published and presented in various scientific forums.

TRIAL REGISTRATION NUMBER

NCT04454229.

Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation

(1) Background: There is currently a global consensus that the quality of comprehensive care for acutely hospitalised elderly people should include addressing functionality and mobility, cognitive status, prevention of pressure ulcers, urinary incontinence, falls and delirium, as well as pain control and medication-related problems. The aim of this study is to develop and validate a clinical prediction rule for multimorbid patients admitted to an acute care hospital unit for any of the five adverse events included in our vulnerability pentad: falls, pressure ulcers, urinary incontinence, pain and delirium. (2) Methods: Longitudinal analytical clinimetric study, with two cohorts. The study population will consist of multimorbid patients hospitalised for acute care, referred from the Emergency Room. A clinical prediction rule will be proposed, incorporating predictive factors of these five adverse outcomes described. This study has received funding, awarded in November 2020 (PI-0107-2020), and was approved in October 2019 by the Research Ethics Committee ″Costa del Sol″. (3) Conclusions: Preventing adverse events in hospitalised patients is particularly important for those with multimorbidity. By applying a clinical prediction rule to detect specific risks, an estimate can be obtained of their probability of occurrence.

Derivation of clinical prediction rules for identifying patients with non-acute low back pain who respond best to a lumbar stabilization exercise program at post-treatment and six-month follow-up

Low back pain (LBP) remains one of the most common and incapacitating health conditions worldwide. Clinical guidelines recommend exercise programs after the acute phase, but clinical effects are modest when assessed at a population level. Research needs to determine who is likely to benefit from specific exercise interventions, based on clinical presentation. This study aimed to derive clinical prediction rules (CPRs) for treatment success, using a lumbar stabilization exercise program (LSEP), at the end of treatment and at six-month follow-up. The eight-week LSEP, including clinical sessions and home exercises, was completed by 110 participants with non-acute LBP, with 100 retained at the six-month follow-up. Physical (lumbar segmental instability, motor control impairments, posture and range of motion, trunk muscle endurance and physical performance tests) and psychological (related to fear-avoidance and home-exercise adherence) measures were collected at a baseline clinical exam. Multivariate logistic regression models were used to predict clinical success, as defined by ≥50% decrease in the Oswestry Disability Index. CPRs were derived for success at program completion (T8) and six-month follow-up (T34), negotiating between predictive ability and clinical usability. The chosen CPRs contained four (T8) and three (T34) clinical tests, all theoretically related to spinal instability, making these CPRs specific to the treatment provided (LSEP). The chosen CPRs provided a positive likelihood ratio of 17.9 (T8) and 8.2 (T34), when two or more tests were positive. When applying these CPRs, the probability of treatment success rose from 49% to 96% at T8 and from 53% to 92% at T34. These results support the further development of these CPRs by proceeding to the validation stage.

Comparison of PECARN clinical decision rule and clinician suspicion in predicting intra-abdominal injury in children with blunt torso trauma in the emergency department

BACKGROUND

The Pediatric Emergency Care Applied Research Network (PECARN) developed a clinical decision rule to identify children at low risk for intra-abdominal injury requiring acute intervention (IAI-I) for reducing unnecessary radiation exposure of ab-dominal computed tomography (CT) after blunt torso trauma. This study aimed to compare the PECARN decision rule with clinician suspicion in identifying children at low risk of intra-abdominal injuries that an abdominal CT scan can be safely avoided.

METHODS

This study is a retrospective review of children with blunt torso trauma in an academic emergency department (ED) between 2011 and 2019. Patients were considered positive for the PECARN rule if they exhibited any of the variables. Clinician suspi-cion was defined as actual CT ordering of the treating physician. The primary outcome was IAI-I detected by imaging or surgery within 1 month after the trauma, and the secondary outcome was any intra-abdominal injury (IAI) presence.

RESULTS

Among the 768 children included, 48 (6.25%) had intra-abdominal injuries and 21 (2.73%) of whom underwent acute in-tervention. Four hundred and fifty-three (59%) children underwent abdominal CT scanning. If the PECARN rule had been applied, 232 patients would have undergone abdominal CT. The rule revealed 90.48% (95% CI=68.17-98.33%) sensitivity for IAI-I and 81.25% (95% CI=66.9-90.56%) for IAI. Clinician suspicion revealed sensitivities of 100% (95% CI=80.76-00%) and 93.75% (95% CI=81.79-98.37%) for IAI-I and IAI, respectively. Sensitivities of the rule and clinician suspicion were statistically similar for both IAI-I (p=0.5) and IAI (p=0.146).

CONCLUSION

In this study, the PECARN abdominal rule and clinician suspicion performed similarly in identifying intra-abdominal injuries in children with blunt torso trauma. However, our study supports the use of PECARN abdominal rule in addition to clinical judgment to limit unnecessary abdominal CT use in pediatric patients with blunt torso trauma in the ED.

Decision-tree derivation and external validation of a new clinical decision rule (DISCERN-FN) to predict the risk of severe infection during febrile neutropenia in children treated for cancer

BACKGROUND

In 2017, international guidelines proposed new management of febrile neutropenia in children with cancer, adapted to the risk of severe infection by clinical decision rules (CDRs). Until now, none of the proposed CDRs has performed well enough in high-income countries for use in clinical practice. Our study aimed to build and validate a new CDR (DISCERN-FN) to predict the risk of severe infection in children with febrile neutropenia.

METHODS

We did two prospective studies. First, a prospective derivation study included all episodes of febrile neutropenia in children (aged <18 years) with a cancer diagnosis and receiving treatment for it who were admitted for an episode of febrile neutropenia, excluding patients already treated with antibiotics for this episode, febrile neutropenia not induced by chemotherapy, those receiving palliative care, and those with a stem cell allograft for less than 1 year, from April 1, 2007, to Dec 31, 2011 from two paediatric cancer centres in France. We collected the children's medical history, and clinical and laboratory data, and analysed their associations with severe infection. Sipina software was used to derive the CDR as a decision tree. Second, a prospective, national, external validation study was done in 23 centres from Jan 1, 2012, to May 31, 2016. The primary outcome was severe infection, defined by bacteraemia, a positive bacterial culture from a usually sterile site, a local infection with a high potential for extension, or an invasive fungal infection. The CDR was applied a posteriori to all episodes to evaluate its sensitivity, specificity, and negative likelihood ratio.

FINDINGS

The derivation set included 539 febrile neutropenia episodes (270 episodes in patients with blood cancer [median age 7·5 years, IQR 3·7-11·2; 158 (59 %) boys and 112 (41%) girls] and 269 in patients with solid tumours [median age 6·6 years, IQR 2·9-14·2; 140 (52 %) boys and 129 (48%) girls]). Significant variables introduced into the decision tree were cancer type (solid tumour vs blood cancer), age, high-risk chemotherapy, level of fever, C-reactive protein concentration (at 24-48 h after admission), and leucocyte and platelet counts and procalcitonin (at admission and at 24-48 h after admission). For the derivation set, the CDR sensitivity was 98% (95% CI 93-100), its specificity 56% (51-61), and the negative likelihood ratio 0·04 (0·01-0·15). 1806 febrile neutropenia episodes were analysed in the validation set (mean age 8·1 years [SD 4·8], 1014 (56%) boys and 792 (44%) girls), of which 332 (18%, 95% CI 17-20) were linked with severe infection. For the validation set, the CDR had a sensitivity of 95% (95% CI 91-97), a specificity of 38% (36-41), and a negative likelihood ratio of 0·13 (0·08-0·21). Our CDR reduced the risk of severe infection to a post-test probability of 0·8% (95% CI 0·2-2·9) in the derivation set and 2·4% (1·5-3·9) in the validation set. The validation study is registered at ClinicalTrials.gov, NCT03434795.

INTERPRETATION

The use of our CDR substantially reduced the risk of severe infection after testing in both the derivation and validation groups, which suggests that this CDR would improve clinical practice enough to be introduced in appropriate settings.

FUNDING

Ligue Nationale Contre le Cancer.

Evaluation of Glial and Neuronal Blood Biomarkers Compared With Clinical Decision Rules in Assessing the Need for Computed Tomography in Patients With Mild Traumatic Brain Injury

IMPORTANCE

In 2018, the combination of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase (UCH-L1) levels became the first US Food and Drug Administration-approved blood test to detect intracranial lesions after mild to moderate traumatic brain injury (MTBI). How this blood test compares with validated clinical decision rules remains unknown.

OBJECTIVES

To compare the performance of GFAP and UCH-L1 levels vs 3 validated clinical decision rules for detecting traumatic intracranial lesions on computed tomography (CT) in patients with MTBI and to evaluate combining biomarkers with clinical decision rules.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study from a level I trauma center enrolled adults with suspected MTBI presenting within 4 hours of injury. The clinical decision rules included the Canadian CT Head Rule (CCHR), New Orleans Criteria (NOC), and National Emergency X-Radiography Utilization Study II (NEXUS II) criteria. Emergency physicians prospectively completed data forms for each clinical decision rule before the patients' CT scans. Blood samples for measuring GFAP and UCH-L1 levels were drawn, but laboratory personnel were blinded to clinical results. Of 2274 potential patients screened, 697 met eligibility criteria, 320 declined to participate, and 377 were enrolled. Data were collected from March 16, 2010, to March 5, 2014, and analyzed on August 11, 2021.

MAIN OUTCOMES AND MEASURES

The presence of acute traumatic intracranial lesions on head CT scan (positive CT finding).

RESULTS

Among enrolled patients, 349 (93%) had a CT scan performed and were included in the analysis. The mean (SD) age was 40 (16) years; 230 patients (66%) were men, 314 (90%) had a Glasgow Coma Scale score of 15, and 23 (7%) had positive CT findings. For the CCHR, sensitivity was 100% (95% CI, 82%-100%), specificity was 33% (95% CI, 28%-39%), and negative predictive value (NPV) was 100% (95% CI, 96%-100%). For the NOC, sensitivity was 100% (95% CI, 82%-100%), specificity was 16% (95% CI, 12%-20%), and NPV was 100% (95% CI, 91%-100%). For NEXUS II, sensitivity was 83% (95% CI, 60%-94%), specificity was 52% (95% CI, 47%-58%), and NPV was 98% (95% CI, 94%-99%). For GFAP and UCH-L1 levels combined with cutoffs at 67 and 189 pg/mL, respectively, sensitivity was 100% (95% CI, 82%-100%), specificity was 25% (95% CI, 20%-30%), and NPV was 100%; with cutoffs at 30 and 327 pg/mL, respectively, sensitivity was 91% (95% CI, 70%-98%), specificity was 20% (95% CI, 16%-24%), and NPV was 97%. The area under the receiver operating characteristic curve (AUROC) for GFAP alone was 0.83; for GFAP plus NEXUS II, 0.83; for GFAP plus NOC, 0.85; and for GFAP plus CCHR, 0.88. The AUROC for UCH-L1 alone was 0.72; for UCH-L1 plus NEXUS II, 0.77; for UCH-L1 plus NOC, 0.77; and for UCH-L1 plus CCHR, 0.79. The GFAP biomarker alone (without UCH-L1) contributed the most improvement to the clinical decision rules.

CONCLUSIONS AND RELEVANCE

In this cohort study, the CCHR, the NOC, and GFAP plus UCH-L1 biomarkers had equally high sensitivities, and the CCHR had the highest specificity. However, using different cutoff values reduced both sensitivity and specificity of GFAP plus UCH-L1. Use of GFAP significantly improved the performance of the clinical decision rules, independently of UCH-L1. Together, the CCHR and GFAP had the highest diagnostic performance.

Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study

OBJECTIVE

To create and validate a simple and transferable machine learning model from electronic health record data to accurately predict clinical deterioration in patients with covid-19 across institutions, through use of a novel paradigm for model development and code sharing.

DESIGN

Retrospective cohort study.

SETTING

One US hospital during 2015-21 was used for model training and internal validation. External validation was conducted on patients admitted to hospital with covid-19 at 12 other US medical centers during 2020-21.

PARTICIPANTS

33 119 adults (≥18 years) admitted to hospital with respiratory distress or covid-19.

MAIN OUTCOME MEASURES

An ensemble of linear models was trained on the development cohort to predict a composite outcome of clinical deterioration within the first five days of hospital admission, defined as in-hospital mortality or any of three treatments indicating severe illness: mechanical ventilation, heated high flow nasal cannula, or intravenous vasopressors. The model was based on nine clinical and personal characteristic variables selected from 2686 variables available in the electronic health record. Internal and external validation performance was measured using the area under the receiver operating characteristic curve (AUROC) and the expected calibration error-the difference between predicted risk and actual risk. Potential bed day savings were estimated by calculating how many bed days hospitals could save per patient if low risk patients identified by the model were discharged early.

RESULTS

9291 covid-19 related hospital admissions at 13 medical centers were used for model validation, of which 1510 (16.3%) were related to the primary outcome. When the model was applied to the internal validation cohort, it achieved an AUROC of 0.80 (95% confidence interval 0.77 to 0.84) and an expected calibration error of 0.01 (95% confidence interval 0.00 to 0.02). Performance was consistent when validated in the 12 external medical centers (AUROC range 0.77-0.84), across subgroups of sex, age, race, and ethnicity (AUROC range 0.78-0.84), and across quarters (AUROC range 0.73-0.83). Using the model to triage low risk patients could potentially save up to 7.8 bed days per patient resulting from early discharge.

CONCLUSION

A model to predict clinical deterioration was developed rapidly in response to the covid-19 pandemic at a single hospital, was applied externally without the sharing of data, and performed well across multiple medical centers, patient subgroups, and time periods, showing its potential as a tool for use in optimizing healthcare resources.

Atypical lymphoid cells circulating in blood in COVID-19 infection: morphology, immunophenotype and prognosis value

AIMS

Atypical lymphocytes circulating in blood have been reported in COVID-19 patients. This study aims to (1) analyse if patients with reactive lymphocytes (COVID-19 RL) show clinical or biological characteristics related to outcome; (2) develop an automatic system to recognise them in an objective way and (3) study their immunophenotype.

METHODS

Clinical and laboratory findings in 36 COVID-19 patients were compared between those showing COVID-19 RL in blood (18) and those without (18). Blood samples were analysed in Advia2120i and stained with May Grünwald-Giemsa. Digital images were acquired in CellaVisionDM96. Convolutional neural networks (CNNs) were used to accurately recognise COVID-19 RL. Immunophenotypic study was performed throughflow cytometry.

RESULTS

Neutrophils, D-dimer, procalcitonin, glomerular filtration rate and total protein values were higher in patients without COVID-19 RL (p<0.05) and four of these patients died. Haemoglobin and lymphocyte counts were higher (p<0.02) and no patients died in the group showing COVID-19 RL. COVID-19 RL showed a distinct deep blue cytoplasm with nucleus mostly in eccentric position. Through two sequential CNNs, they were automatically distinguished from normal lymphocytes and classical RL with sensitivity, specificity and overall accuracy values of 90.5%, 99.4% and 98.7%, respectively. Immunophenotypic analysis revealed COVID-19 RL are mostly activated effector memory CD4 and CD8 T cells.

CONCLUSION

We found that COVID-19 RL are related to a better evolution and prognosis. They can be detected by morphology in the smear review, being the computerised approach proposed useful to enhance a more objective recognition. Their presence suggests an abundant production of virus-specific T cells, thus explaining the better outcome of patients showing these cells circulating in blood.

Polygenic Score for Physical Activity Is Associated with Multiple Common Diseases

INTRODUCTION

Genetic pleiotropy, in which the same genes affect two or more traits, may partially explain the frequently observed associations between high physical activity (PA) and later reduced morbidity or mortality. This study investigated associations between PA polygenic risk scores (PRS) and cardiometabolic diseases among the Finnish population.

METHODS

PRS for device-measured overall PA were adapted to a FinnGen study cohort of 218,792 individuals with genomewide genotyping and extensive digital longitudinal health register data. Associations between PA PRS and body mass index, diseases, and mortality were analyzed with linear and logistic regression models.

RESULTS

A high PA PRS predicted a lower body mass index (β = -0.025 kg·m-2 per one SD change in PA PRS, SE = 0.013, P = 1.87 × 10-80). The PA PRS also predicted a lower risk for diseases that typically develop later in life or not at all among highly active individuals. A lower disease risk was systematically observed for cardiovascular diseases (odds ratio [OR] per 1 SD change in PA PRS = 0.95, P = 9.5 × 10-19) and, for example, hypertension [OR = 0.93, P = 2.7 × 10-44), type 2 diabetes (OR = 0.91, P = 4.1 × 10-42), and coronary heart disease (OR = 0.95, P = 1.2 × 10-9). Participants with high PA PRS had also lower mortality risk (OR = 0.97, P = 0.0003).

CONCLUSIONS

Genetically less active persons are at a higher risk of developing cardiometabolic diseases, which may partly explain the previously observed associations between low PA and higher disease and mortality risk. The same inherited physical fitness and metabolism-related mechanisms may be associated both with PA levels and with cardiometabolic disease risk.

Predicting Upper Quadrant Musculoskeletal Injuries in the Military: A Cohort Study

PURPOSE

This study aimed to identify characteristics and movement-based tests that predict upper quadrant musculoskeletal injury (UQI) in military personnel over a 12-month follow-up.

METHODS

A prospective observational cohort study of military members (n = 494; 91.9% male) was conducted. Baseline predictors associated with UQI were gathered through surveys and movement-based tests. Survey data included demographic information, injury history, and biosocial factors. Movement-based tests include the following: Y Balance Tests (YBT), Functional Movement Screen, Selective Functional Movement Assessment lumbar multisegmental mobility, modified-modified Schober, side bridge, ankle mobility, modified Sorensen, and passive lumbar extension. Self-reported UQI was collected through monthly online surveys, and 87% completed the follow-up. Univariate associations were determined between potential predictors and UQI. A forward, stepwise logistic regression model was used to identify the best combination of predictors for UQI.

RESULTS

Twenty-seven had UQI. Univariate associations existed with three demographic (smoking, >1 previous UQI, baseline upper quadrant function ≤90%), three pain-related (Selective Functional Movement Assessment rotation, side bridge, hurdle step), and six movement-based variables (YBT upper quarter (UQ) superolateral worst score ≤57.75 cm, YBT-UQ composite worst score ≤81.1%, failed shoulder clearance, Sorenson <72.14 s, in-line lunge total score <15, and in-line lunge asymmetry >1). Smoking, baseline upper quadrant function ≤90%, and YBT-UQ composite score ≤81.1% predicted UQI in the logistic regression while controlling for age and sex. Presenting two or more predictors resulted in good specificity (85.6%; odds ratio, 4.8; 95% confidence interval, 2.2-10.8), and at least one predictor resulted in 81.5% sensitivity (odds ratio, 3.2; 95% confidence interval, 1.2-8.7).

CONCLUSIONS

A modifiable movement-based test (YBT-UQ), perceived upper limb function, and smoking predicted UQI. A specific (two or more) and sensitive (at least one predictor) model could identify persons at higher risk.

Screening Hamstring Injury Risk Factors Multiple Times in a Season Does Not Improve the Identification of Future Injury Risk

PURPOSE

To determine if eccentric knee flexor strength and biceps femoris long head (BFlh) fascicle length were associated with prospective hamstring strain injury (HSI) in professional Australian Football players, and if more frequent assessments of these variables altered the association with injury risk.

METHODS

Across two competitive seasons, 311 Australian Football players (455 player seasons) had their eccentric knee flexor strength during the Nordic hamstring exercise and BFlh architecture assessed at the start and end of preseason and in the middle of the competitive season. Player age and injury history were also collected in preseason. Prospective HSIs were recorded by team medical staff.

RESULTS

Seventy-four player seasons (16%) sustained an index HSI. Shorter BFlh fascicles (<10.42 cm) increased HSI risk when assessed at multiple time points only (relative risk [RR], 1.9; 95% confidence interval [CI], 1.2-3.0). Neither absolute (N) nor relative (N·kg-1) eccentric knee flexor strength was associated with HSI risk, regardless of measurement frequency (RR range, 1.0-1.1); however, between-limb imbalance (>9%), when measured at multiple time points, was (RR, 1.8; 95% CI, 1.1-3.1). Prior HSI had the strongest univariable association with prospective HSI (RR, 2.9; 95% CI, 1.9-4.3). Multivariable logistic regression models identified a combination of prior HSI, BFlh architectural variables and between-limb imbalance in eccentric knee flexor strength as optimal input variables; however, their predictive performance did not improve with increased measurement frequency (area under the curve, 0.681-0.726).

CONCLUSIONS

More frequent measures of eccentric knee flexor strength and BFlh architecture across a season did not improve the ability to identify which players would sustain an HSI.

A risk scoring system to predict the individual incidence of early-onset colorectal cancer

BACKGROUND

The incidence of early-onset colorectal cancer (EOCRC) is increasing at an alarming rate and further studies are needed to identify risk factors and to develop prevention strategies.

METHODS

Risk factors significantly associated with EOCRC were identified using meta-analysis. An individual risk appraisal model was constructed using the Rothman-Keller model. Next, a group of random data sets was generated using the binomial distribution function method, to determine nodes of risk assessment levels and to identify low, medium, and high risk populations.

RESULTS

A total of 32,843 EOCRC patients were identified in this study, and nine significant risk factors were identified using meta-analysis, including male sex, Caucasian ethnicity, sedentary lifestyle, inflammatory bowel disease, and high intake of red meat and processed meat. After simulating the risk assessment data of 10,000 subjects, scores of 0 to 0.0018, 0.0018 to 0.0036, and 0.0036 or more were respectively considered as low-, moderate-, and high-risk populations for the EOCRC population based on risk trends from the Rothman-Keller model.

CONCLUSION

This model can be used for screening of young adults to predict high risk of EOCRC and will contribute to the primary prevention strategies and the reduction of risk of developing EOCRC.

Validation of Pediatric Emergency Care Applied Research Network (PECARN) rule in children with minor head trauma

The Pediatric Emergency Care Applied Research Network (PECARN) rule is commonly used for predicting the need for computed tomography (CT) scans in children with mild head trauma. The objective of this study was to validate the PECARN rule in Korean children presenting to the pediatric emergency department (PED) with head trauma. This study was a multicenter, retrospective, observational cohort study in two teaching PEDs in Korea between August 2015 and August 2016. In this observational study, 448 patients who visited PEDs were included in the final analysis. Risk stratification was performed with clinical decision support software based on the PECARN rule, and decisions to perform CT scans were subsequently made. Patients were followed-up by phone call between 7 days and 90 days after discharge from the PED. The sensitivity and specificity were analyzed. The sensitivity was 100% for all age groups, and no cases of clinically important traumatic brain injury (ciTBI) were identified in the very-low-risk group. CT scans were performed for 14.7% of patients in this study and for 33.8% in the original PECARN study. The PECARN rule successfully identified low-risk patients, and no cases of ciTBI were missed despite the reduced proportion of patients undergoing CT scans.

Polygenic risk prediction models for colorectal cancer: a systematic review

BACKGROUND

Risk prediction models incorporating single nucleotide polymorphisms (SNPs) could lead to individualized prevention of colorectal cancer (CRC). However, the added value of incorporating SNPs into models with only traditional risk factors is still not clear. Hence, our primary aim was to summarize literature on risk prediction models including genetic variants for CRC, while our secondary aim was to evaluate the improvement of discriminatory accuracy when adding SNPs to a prediction model with only traditional risk factors.

METHODS

We conducted a systematic review on prediction models incorporating multiple SNPs for CRC risk prediction. We tested whether a significant trend in the increase of Area Under Curve (AUC) according to the number of SNPs could be observed, and estimated the correlation between AUC improvement and number of SNPs. We estimated pooled AUC improvement for SNP-enhanced models compared with non-SNP-enhanced models using random effects meta-analysis, and conducted meta-regression to investigate the association of specific factors with AUC improvement.

RESULTS

We included 33 studies, 78.79% using genetic risk scores to combine genetic data. We found no significant trend in AUC improvement according to the number of SNPs (p for trend = 0.774), and no correlation between the number of SNPs and AUC improvement (p = 0.695). Pooled AUC improvement was 0.040 (95% CI: 0.035, 0.045), and the number of cases in the study and the AUC of the starting model were inversely associated with AUC improvement obtained when adding SNPs to a prediction model. In addition, models constructed in Asian individuals achieved better AUC improvement with the incorporation of SNPs compared with those developed among individuals of European ancestry.

CONCLUSIONS

Though not conclusive, our results provide insights on factors influencing discriminatory accuracy of SNP-enhanced models. Genetic variants might be useful to inform stratified CRC screening in the future, but further research is needed.

Development and Validation of a Nomogram for Predicting the Long-Term Survival in Patients With Chronic Thromboembolic Pulmonary Hypertension

There remains a lack of prognosis models for patients with chronic thromboembolic pulmonary hypertension (CTEPH). This study aims to develop a nomogram predicting 3-, 5-, and 7-year survival in patients with CTEPH and verify the prognostic model. Patients with CTEPH diagnosed in Fuwai Hospital were enrolled consecutively between May 2013 and May 2019. Among them, 70% were randomly split into a training set and the other 30% as a validation set for external validation. Cox proportional hazards model was used to identify the potential survival-related factors which were candidate variables for the establishment of nomogram and the final model was internally validated by the bootstrap method. A total of 350 patients were included in the final analysis and the median follow-up period of the whole cohort was 51.2 months. Multivariate analysis of Cox proportional hazards regression showed body mass index, mean right atrial pressure, N-terminal pro-brain natriuretic peptide (per 500 ng/ml increase in concentration), presence of anemia, and main treatment choice were the independent risk factors of mortality. The nomogram demonstrated good discrimination with the corrected C-index of 0.82 in the training set, and the C-index of 0.80 (95% CI: 0.70 to 0.91) in the external validation set. The calibration plots also showed a good agreement between predicted and actual survival in both training and validation sets. In conclusion, we developed an easy-to-use nomogram with good apparent performance using 5 readily available variables, which may help physicians to identify CTEPH patients at high risk for poor prognosis and implement medical interventions.

Evaluation and management of traumatic pneumothorax: A Western Trauma Association critical decisions algorithm

ABSTRACT

This is a recommended algorithm of the Western Trauma Association for the management of a traumatic pneumothorax. The current algorithm and recommendations are based on available published prospective cohort, observational, and retrospective studies and the expert opinion of the Western Trauma Association members. The algorithm and accompanying text represents a safe and reasonable approach to this common problem. We recognize that there may be variability in decision making, local resources, institutional consensus, and patient-specific factors that may require deviation from the algorithm presented. This annotated algorithm is meant to serve as a basis from which protocols at individual institutions can be developed or serve as a quick bedside reference for clinicians.

LEVEL OF EVIDENCE

Consensus algorithm from the Western Trauma Association, Level V.

The Usefulness of the Rapid Shallow Breathing Index in Predicting Successful Extubation: A Systematic Review and Meta-analysis

BACKGROUND

Clinicians use several measures to ascertain whether individual patients will tolerate liberation from mechanical ventilation, including the rapid shallow breathing index (RSBI).

RESEARCH QUESTION

Given varied use of different thresholds, patient populations, and measurement characteristics, how well does RSBI predict successful extubation?

STUDY DESIGN AND METHODS

We searched six databases from inception through September 2019 and selected studies reporting the accuracy of RSBI in the prediction of successful extubation. We extracted study data and assessed quality independently and in duplicate.

RESULTS

We included 48 studies involving RSBI measurements of 10,946 patients. Pooled sensitivity for RSBI of < 105 in predicting extubation success was moderate (0.83 [95% CI, 0.78-0.87], moderate certainty), whereas specificity was poor (0.58 [95% CI, 0.49-0.66], moderate certainty) with diagnostic ORs (DORs) of 5.91 (95% CI, 4.09-8.52). RSBI thresholds of < 80 or 80 to 105 yielded similar sensitivity, specificity, and DOR. These findings were consistent across multiple subgroup analyses reflecting different patient characteristics and operational differences in RSBI measurement.

INTERPRETATION

As a stand-alone test, the RSBI has moderate sensitivity and poor specificity for predicting extubation success. Future research should evaluate its role as a permissive criterion to undergo a spontaneous breathing trial (SBT) for patients who are at intermediate pretest probability of passing an SBT.

TRIAL REGISTRY

PROSPERO; No.: CRD42020149196; URL: www.crd.york.ac.uk/prospero/.