Prediction Rule Research Articles

Development and validation of a clinical prediction rule for walking independence in hospitalized older adults with a vertebral compression fracture.

No reports on factors or Clinical prediction rules (CPRs) associated with walking independence among patients with vertebral compression fractures (VCFs) are available. Evidence regarding epidemiological walking independence rates is also sparse. Here, we sought to (i) obtain epidemiological data on the probability of inpatients with VCFs achieving walking independence, and (ii) develop and validate a CPR to determine walking independence in hospitalized patients with VCFs. We conducted a retrospective cross-sectional observational study of patients aged ≥60years who were hospitalized for VCF at four hospitals in Japan in 2019-2022. The outcome was walking independence at discharge. We performed a binomial logistic regression analysis to assess predictors of walking independence. Five independent variables were entered: age, American Society of Anesthesiologists physical status, cognitive function, Berg Balance Scale (BBS), and 10-m walking test. Among the independent variables that were significant, we converted the continuous variables to binary data by calculating cut-off values and then created the CPR. The area under the curve (AUC) was calculated as the measure of the CPR's diagnostic accuracy, and internal validation was conducted by bootstrapping. Of the 240 patients, 188 (78.3%) achieved walking independence. Cognitive function and the BBS score (with a cut-off of 45 points) were identified as significant predictors. We created a CPR using these two items (0-2 points). The CPR's AUC was 0.92 (0.874-0.967), and internal validation by bootstrapping yielded a mean AUC of 0.919 with a slope of 0.965. The walking independence rate of patients with a VCF during hospitalization was 78.3%, with cognitive function and BBS being predictors. The developed CPR performed well enough to retrospectively predict walking independence in VCF patients. The BBS cut-off value and the CPR may serve as useful indicators for clinicians to predict VCF patients' walking independence.

Hierarchical triply periodic minimal surface shell lattices with superior isotropic elasticity: Design guidelines, fabrication, and validation

Hierarchical triply periodic minimal surface (TPMS) shell lattices exhibit a wide range of tailorable properties that can be fine-tuned by lattice design. Recent advances in additive manufacturing towards high resolution enable the precise fabrication of hierarchical TPMS lattices. However, the isotropic behavior of hierarchical TPMS lattices has received little attention. In this study, we focus on the design of hierarchical TPMS lattices to explore their superior isotropic elasticity. By considering three unique geometric parameters of hierarchical TPMS: cell length ratio, relative density, and order number, multiple representative isotropic hierarchical TPMS lattices can be achieved at the same given relative density, which significantly expands its design space. The resultant lattices retain a minimal mid-surface and exhibit a large range of tailorable stiffness. To validate their isotropic elasticity, high-precision laser powder bed fusion was adopted to fabricate representative isotropic lattices and their anisotropic counterparts. Morphology observation and micro-CT scan show that the fabricated samples are dense, and their geometries are highly consistent with the designed models. Quasi-static compression tests further confirm the isotropic elasticity in the new designs. Moreover, a prediction rule was proposed to assess whether an isotropic hierarchical TPMS lattice can be obtained from two selected single-level lattices, which significantly enhances the design efficiency. As a result, the design method and principles can be summarized in this study to provide effective design guidelines to swiftly create hierarchical shell lattices with superior isotropic elasticity.

On the recent-$k$-record of discrete random variables

Let $X_1,~X_2,\cdots$ be a sequence of independent and identically distributed random variables which are supposed to be observed in sequence. The $n$th value in the sequence is a $k-record~value$ if exactly $k$ of the first $n$ values (including $X_n$) are at least as large as it. Let ${\bf R}_k$ denote the ordered set of $k$-record values. The famous Ignatov's Theorem states that the random sets ${\bf R}_k(k=1,2,\cdots)$ are independent with common distribution. We introduce one new record named $recent-k-record$ in this paper: $X_n$ is a $j$-recent-k-record if there are exactly $j$ values at least as large as $X_n$ in $X_{n-k},~X_{n-k+1},\cdots,~X_{n-1}$. It turns out that recent-k-record brings many interesting problems and some novel properties such as prediction rule and Poisson approximation which are proved in this paper. One application named "No Good Record" via the Lov{\'a}sz Local Lemma is also provided. We conclude this paper with some possible connection with scan statistics.

Clinical prediction model for pediatric lymphadenopathy: enhancing diagnostic precision and treatment decision making.

Lymph node enlargement is common in children, with 90% of physiologically palpable lymph nodes. This study aimed to develop a predictive model based on clinical characteristics to enhance the diagnosis of pediatric lymphadenopathy and provide insights into biopsy outcomes. A clinical prediction rule was developed using a retrospective, cross-sectional design for patients under 15years who underwent lymph node biopsy from 2012 to 2022. Multivariable risk regression was used to analyze benign and malignant lesions, presenting results through risk difference and AUROC for each group. Predicted probabilities were applied in a logistic regression equation to classify patients' lymphadenopathy as reactive hyperplasia, benign, or malignant. Of 188 children, 70 (37.2%) had benign lymphadenopathy beyond reactive hyperplasia, and 27 (14.4%) had malignant lymphadenopathy. The predictive model included 12 characteristics such as size, location, duration, associated symptoms, and lymph node examination. Predictive accuracy was 92.2% for benign cases (AUROC = 0.92; 95% CI 0.87-0.96) and 98.6% for malignancy (AUROC = 0.98; 95% CI 0.94-0.99). Overall accuracy for predicting both benign and malignant tumors was 68.3%. The model demonstrated reasonably accurate predictions for the clinical characteristics of pediatric lymphadenopathy. It tended to overestimate malignancy but did not miss diagnoses, aiding in reducing unnecessary lymph node biopsies in benign cases.

Housing mice near vs. below thermoneutrality affects drug-induced weight loss but does not improve prediction of efficacy in humans

Evaluation of weight loss drugs is usually performed in diet-induced obese mice housed at ∼22°C. This is a cold stress that increases energy expenditure by ∼35% compared to thermoneutrality (∼30°C), which may overestimate drug-induced weight loss. We investigated five anti-obesity mechanisms that have been in clinical development, comparing weight loss in mice housed at 22°C vs. 30°C. Glucagon-like peptide-1 (GLP-1), human fibroblast growth factor 21 (hFGF21), and melanocortin-4 receptor (MC4R) agonist induced similar weight losses. Peptide YY elicited greater vehicle-subtracted weight loss at 30°C (7.2% vs. 1.4%), whereas growth differentiation factor 15 (GDF15) was more effective at 22°C (13% vs. 6%). Independent of ambient temperature, GLP-1 and hFGF21 prevented the reduction in metabolic rate caused by weight loss. There was no simple rule for a better prediction of human drug efficacy based on ambient temperature, but since humans live at thermoneutrality, drug testing using mice should include experiments near thermoneutrality.

Evaluating some new benzimidazole derivative: Insilico docking studies for anthelmintic drug development

The Heterocyclic compounds used as medicinal agents in the field of study since long time. Benzo-fused heterocyclic nucleus benzimidazole founds significant class for new drug development. Molecular docking study is a technique in Computer Aided Drug Designing for studying ligand and protein interaction. The main motto of this work is to perform Preliminary screening using SAR studies, OSIRIS molecular property explorer, PASS Prediction Activity spectra and Rule of Five and to check the proposed benzimidazole compounds are potentially active as Anthelminthic agent by Docking studies with beta tubulin protein (PDB ID 1OJ0) using Auto dock 1.5.6 and VINA. Among all proposed benzimidazole derivatives, 4-((1H-benzimidazol-1-ylimino) methyl) phenol (5d) is the most effective and showed maximum binding energy (−7.4 K/Cal) when compared with standard drug albendazole (−7.1 K/Cal).

Relationship between the HeartMate Risk Score category on admission and outcome in patients with acute heart failure referred to a cardiac intensive care unit.

The HeartMate Risk Score (HMRS), a simple clinical prediction rule based on the patients' age, albumin, creatinine, and the international normalized ratio of the prothrombin time (PT-INR), is correlated with mortality in the cohort of left ventricular assist device (LVAD) recipients. However, in an aging society, an LAVD is indicated for only a small proportion of patients with acute heart failure (AHF), and whether the HMRS has prognostic implications for unselected patients with AHF is unknown. This study aimed to assess the prognostic value of HMRS categories on admission in patients with AHF. We analyzed 339 hospitalized patients with AHF who had albumin, creatinine, and the PT-INR recorded on admission. The patients were categorized as follows: the High group (HMRS > 2.48, n = 131), Mid group (HMRS of 1.58-2.48, n = 97) group, and Low group (HMRS < 1.58, n = 111). The endpoints of this study were all-cause death and readmission for heart failure (HF). During a median follow-up of 247days, 24 (18.3%) patients died in the High group, 7 (7.2%) died in the Mid group, and 8 (7.2%) died in the Low group. In a multivariable analysis adjusted for highly imbalanced baseline variables, a high HMRS was independently associated with survival, with a hazard ratio of 2.90 (95% confidence interval 1.42-5.96, P = 0.004). With regard to the composite endpoint of all-cause death and readmission for HF, the Mid group had a worse prognosis than the Low group, and the High group had the worst prognosis. A high HMRS on admission is associated with all-cause mortality and readmission for HF, and a mid-HMRS is associated with readmission for HF after AHF hospitalization. The HMRS may be a valid clinical tool to stratify the risk of adverse outcomes after hospitalization in unselected patients with AHF.

A Prediction Rule for the Dystonic Spread of Blepharospasm: A 4-Year Prospective Cohort Study.

Blepharospasm (BSP), focal dystonia with the highest risk of spread, lacks clear understanding of early spreading risk factors and objective prognostic indicators. We aimed to identify these risk factors through clinical and electrophysiological assessments, and to establish a predictive model for dystonic spread in BSP. We prospectively followed BSP patients for 4 years, collecting data on dystonic spread, and conducting electrophysiological evaluations. The blink reflex, masseter inhibitory reflex, and trigeminal somatosensory evoked potential were assessed. Univariable and multivariable Cox proportional hazard regression models were used to assess clinical characteristics associated with BSP dystonic spread. A predictive model was constructed using a nomogram, and performance of the model was evaluated using the area under the receiver operating characteristic curve. A total of 136 enrolled participants (mean age 56.34 years) completed a 4-year follow-up. Among them, 62 patients (45.6%) showed spread to other body regions. Multivariable Cox regression analysis showed that a high Hamilton Anxiety Scale score (hazard ratio 1.19, 95% confidence interval 1.13-1.25, p < 0.001), prolonged trigeminal somatosensory evoked potential mandibular branch P1-N2 peak interval (hazard ratio 1.11, 95% confidence interval 1.02-1.21, p = 0.017), and elevated trigeminal somatosensory evoked potential mandibular branch P1-N2 peak amplitude (hazard ratio 1.26, 95% confidence interval 1.12-1.41, p < 0.001) were independent risk factors for BSP dystonic spread within 4 years. Combining these factors, the predictive models demonstrated excellent discriminative ability, with the receiver operating characteristic curve score being 0.797, 0.790, 0.847, and 0.820 at 1, 2, 3 and 4 years after enrollment, respectively. We established a predictive model with significant value for anticipating dystonic spread in BSP, offering crucial evidence. These findings contribute essential insights into the early clinical identification of the development and evolution of BSP diseases. ANN NEUROL 2024.

PECARN prediction rule for cervical spine imaging of children presenting to the emergency department with blunt trauma: a multicentre prospective observational study.

Cervical spine injuries in children are uncommon but potentially devastating; however, indiscriminate neck imaging after trauma unnecessarily exposes children to ionising radiation. The aim of this study was to derive and validate a paediatric clinical prediction rule that can be incorporated into an algorithm to guide radiographic screening for cervical spine injury among children in the emergency department. In this prospective observational cohort study, we screened children aged 0-17 years presenting with known or suspected blunt trauma at 18 specialised children's emergency departments in hospitals in the USA affiliated with the Pediatric Emergency Care Applied Research Network (PECARN). Injured children were eligible for enrolment into derivation or validation cohorts by fulfilling one of the following criteria: transported from the scene of injury to the emergency department by emergency medical services; evaluated by a trauma team; and undergone neck imaging for concern for cervical spine injury either at or before arriving at the PECARN-affiliated emergency department. Children presenting with solely penetrating trauma were excluded. Before viewing an enrolled child's neck imaging results, the attending emergency department clinician completed a clinical examination and prospectively documented cervical spine injury risk factors in an electronic questionnaire. Cervical spine injuries were determined by imaging reports and telephone follow-up with guardians within 21-28 days of the emergency room encounter, and cervical spine injury was confirmed by a paediatric neurosurgeon. Factors associated with a high risk of cervical spine injury (>10%) were identified by bivariable Poisson regression with robust error estimates, and factors associated with non-negligible risk were identified by classification and regression tree (CART) analysis. Variables were combined in the cervical spine injury prediction rule. The primary outcome of interest was cervical spine injury within 28 days of initial trauma warranting inpatient observation or surgical intervention. Rule performance measures were calculated for both derivation and validation cohorts. A clinical care algorithm for determining which risk factors warrant radiographic screening for cervical spine injury after blunt trauma was applied to the study population to estimate the potential effect on reducing CT and x-ray use in the paediatric emergency department. This study is registered with ClinicalTrials.gov, NCT05049330. Nine emergency departments participated in the derivation cohort, and nine participated in the validation cohort. In total, 22 430 children presenting with known or suspected blunt trauma were enrolled (11 857 children in the derivation cohort; 10 573 in the validation cohort). 433 (1·9%) of the total population had confirmed cervical spine injuries. The following factors were associated with a high risk of cervical spine injury: altered mental status (Glasgow Coma Scale [GCS] score of 3-8 or unresponsive on the Alert, Verbal, Pain, Unresponsive scale [AVPU] of consciousness); abnormal airway, breathing, or circulation findings; and focal neurological deficits including paresthesia, numbness, or weakness. Of 928 in the derivation cohort presenting with at least one of these risk factors, 118 (12·7%) had cervical spine injury (risk ratio 8·9 [95% CI 7·1-11·2]). The following factors were associated with non-negligible risk of cervical spine injury by CART analysis: neck pain; altered mental status (GCS score of 9-14; verbal or pain on the AVPU; or other signs of altered mental status); substantial head injury; substantial torso injury; and midline neck tenderness. The high-risk and CART-derived factors combined and applied to the validation cohort performed with 94·3% (95% CI 90·7-97·9) sensitivity, 60·4% (59·4-61·3) specificity, and 99·9% (99·8-100·0) negative predictive value. Had the algorithm been applied to all participants to guide the use of imaging, we estimated the number of children having CT might have decreased from 3856 (17·2%) to 1549 (6·9%) of 22 430 children without increasing the number of children getting plain x-rays. Incorporated into a clinical algorithm, the cervical spine injury prediction rule showed strong potential for aiding clinicians in determining which children arriving in the emergency department after blunt trauma should undergo radiographic neck imaging for potential cervical spine injury. Implementation of the clinical algorithm could decrease use of unnecessary radiographic testing in the emergency department and eliminate high-risk radiation exposure. Future work should validate the prediction rule and care algorithm in more general settings such as community emergency departments. The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Health Resources and Services Administration of the US Department of Health and Human Services in the Maternal and Child Health Bureau under the Emergency Medical Services for Children programme.

An Updated Systematic Review on Prediction Models for Successful External Cephalic Version

Purpose: Current practice guidelines recommend offering patients an external cephalic version (ECV) when a fetus is found to be in breech position. If successful, vaginal delivery can then safely follow an ECV. ECV for a term breech presentation varies widely in success but is a well-studied topic, with many variables identified which relate to its success. This has led to a multitude of predictor models for ECV success. A systematic review by Velzel et al. published in 2015 examined prior predictor models for ECV success; however, many models have since been published. We aim to update this systematic review with the new predictive models published in the last seven years and thus review the decision aids currently available or being developed to predict a patients’ odds that their external cephalic version (ECV) will be successful. Methods: We searched PubMed/MEDLINE, Cochrane Central, and ClinicalTrials.gov from 2015-2022. Articles from a pre-2015 systematic review were also included. A clinical librarian helped with conducting a thorough search strategy. We selected English-language articles describing or evaluating models (prediction rules) designed to predict an outcome of ECV for an individual patient. Acceptable model outcomes included cephalic presentation after the ECV attempt and whether the ECV ultimately resulted in a vaginal delivery. Two authors independently performed article selection following PRISMA 2020 guidelines. Since 2015, 380 unique records underwent title and abstract screening, and 49 reports underwent full-text review. Ultimately, 17 new articles and 8 from the prior review were included. Of the 25 articles, 22 proposed 1-2 models each for a total of 25 models, while the remaining 3 articles validated prior models without proposing new ones. The studies were then analyzed for quality and risk of bias using a customized framework which analyzed four main domains: participants, predictors, outcome, and analysis. Ultimately, the largest factor considered when assessing study quality was whether the outcome was likely to be different amongst groups within a similar population. We then assessed the model’s calibration and discrimination metrics (if reported) to evaluate their overall model performance. Results: Of the 17 new articles, 10 were low, 6 moderate, and 1 high risk of bias. Studies were considered to have moderate risk of bias and quality if model-building strategies were not described, as it introduces concerns regarding consistency in applying the models to a similar population. Almost all articles were from Europe (11/25) or Asia (10/25); only one study in the last 20 years was from the USA. Four of the 17 new articles had some form of overlap with articles from the prior systematic reviews. The remaining 13 new articles used datasets, proposed models, and were performed by researchers that were entirely distinct from the 8 original articles The most included characteristics were parity (19/25), placental location (12/25), and breech engagement or station (10/25). Although many studies included BMI (8/25), only a few indicated whether this was to be pregravid, peri-ECV, or peripartum BMI. Some metrics for model discrimination (e.g., sensitivity, AUC, accuracy, PPV) was displayed in 17 of the 25 models. The models found had diverse presentations including score charts, decision trees (flowcharts), and equations. The majority (13/25) had no form of validation and only 5/25 reached external validation. Only the Newman-Peacock model (USA, 1993) was repeatedly externally validated (Pakistan, 2012 and Portugal, 2018). Most models (14/25) were published in the last 5 years. In general, newer models were designed more robustly, used larger sample sizes, and were more mathematically rigorous. Thus, although they await further validation, there is great potential for these models to be more predictive than the Newman-Peacock model. Based on the findings in this review, the Newman-Peacock model to predict ECV success (odds of cephalic presentation after the ECV procedure) is currently the most clinically useful model. Even though it is the oldest model in the review, it includes three of the most widely included prediction features: parity, placental location, and station. Furthermore, it is the only model that has been externally validated in a significantly different population and by a different investigational team than what was used to create the model. Conclusion: Only the Newman-Peacock model is ready for regular clinical use in predicting ECV success. Many newer models are promising but require further validation.

Clinical Prediction Rules for In-Hospital Mortality Outcome in Melioidosis Patients.

Melioidosis, a disease induced by Burkholderia pseudomallei, poses a significant health threat in tropical areas where it is endemic. Despite the availability of effective treatments, mortality rates remain notably elevated. Many risk factors are associated with mortality. This study aims to develop a scoring system for predicting the in-hospital mortality from melioidosis using readily available clinical data. The data were collected from Surin Hospital, Surin, Thailand, during the period from April 2014 to March 2017. We included patients aged 15 years and above who had cultures that tested positive for Burkholderia pseudomallei. The clinical prediction rules were developed using significant risk factors from the multivariable analysis. A total of 282 patients with melioidosis were included in this study. In the final analysis model, 251 patients were used for identifying the significant risk factors of in-hospital fatal melioidosis. Five factors were identified and used for developing the clinical prediction rules, and the factors were as follows: qSOFA ≥ 2 (odds ratio [OR] = 2.39, p= 0.025), abnormal chest X-ray findings (OR = 5.86, p < 0.001), creatinine ≥ 1.5 mg/dL (OR = 2.80, p = 0.004), aspartate aminotransferase ≥50 U/L (OR = 4.032, p < 0.001), and bicarbonate ≤ 20 mEq/L (OR = 2.96, p = 0.002). The prediction scores ranged from 0 to 7. Patients with high scores (4-7) exhibited a significantly elevated mortality rate exceeding 65.0% (likelihood ratio [LR+] 2.18, p < 0.001) compared to the low-risk group (scores 0-3) with a lower mortality rate (LR + 0.18, p < 0.001). The area under the receiver operating characteristic curve (AUC) was 0.84, indicating good model performance. This study presents a simple scoring system based on easily obtainable clinical parameters to predict in-hospital mortality in melioidosis patients. This tool may facilitate the early identification of high-risk patients who could benefit from more aggressive treatment strategies, potentially improving clinical decision-making and patient outcomes.

Receiver Operating Characteristic (ROC) Curves: The Basics and Beyond.

Diagnostic tests and clinical prediction rules are frequently used to help estimate the probability of a disease or outcome. How well a test or rule distinguishes between disease or no disease (discrimination) can be measured by plotting a receiver operating characteristic (ROC) curve and calculating the area under it (AUROC). In this paper, we review the features of ROC curves and interpretation of ROC curves and AUROC values. We highlight 5 underappreciated features of ROC curves: (1) the slope of the ROC curve over a test result interval is the likelihood ratio for that interval; (2) the optimal cutoff for calling a test positive depends not only on the shape of the ROC curve, but also on the pretest probability of disease and relative harms of false-positive and false-negative results; (3) the AUROC measures discrimination only, not the accuracy of the predicted probabilities; (4) the AUROC is not a good measure of discrimination if the slope of the ROC curve is not consistently decreasing; and (5) the AUROC can be increased by including a large number of people correctly identified as being at very low risk for the outcome of interest. We illustrate this last concept using 3 published studies.

Post-fire behavior of double-sided stainless-clad bimetallic steels

This paper presents an experimental investigation of the post-fire behavior of double-sided stainless-clad bimetallic steels (DSSCBS), which is a new type of high-efficiency material and is promising to be used in cold-formed structures. A total of 48 tensile coupon specimens were extracted from two types of DSSCBS plates, with 316L stainless steel as the cladding material and Q235 or Q345 carbon steel as the substrate material. The specimens were heated up to various temperatures up to 1000 °C and subsequently cooled down to ambient temperature via air-cooling or water-cooling methods, to evaluate the effect of different cooling approaches. Additionally, the influence of in-fire stresses, which reflects the load ratios of structural members in fire hazards, was also examined. Stress-strain curves as well as key mechanical properties including the elastic modulus, yield strength, ultimate strength, ultimate strain and fracture strain were obtained and fully reported. Moreover, the measured post-fire retention factors were compared with existing prediction equations for carbon steel and stainless steel, as well as the prediction curves for single-sided stainless-clad bimetallic steel to assess their applicability to this novel material. New predictive rules for retention factors of DSSCBS in post-fire conditions were proposed with stress-strain models advanced to offer a reference for future numerical simulation and assessment of the post-fire behavior of members and structures of DSSCBS.

Understanding the Thermodynamics of Magnesium Binding to RNA Structural Motifs.

Divalent magnesium ions (Mg2+) serve a vital role in defining the structural and catalytic chemistry of a wide array of RNA molecules. The body of structural information on RNA motifs continues to expand and, in turn, the functional importance of Mg2+ is revealed. A combination of prior work on the structural characterization of magnesium binding ligands with inner- and outer-sphere coordination modes, with recorded experimental binding energies for inner- and outer-sphere contacts, demonstrates the relative affinity and thermodynamic hierarchy for these sites. In turn, these can be correlated with cellular concentrations of free available magnesium ions, allowing the prioritization of populating important functional sites and a correlation with physiological function. This paper summarizes some of the key results of that analysis and provides predictive rules for the affinity and role of newly identified Mg binding sites on complex RNA structures. The influence of crystal packing on magnesium binding to RNA motifs, relative to their solution form, is addressed and caveats made.

Identification of severely injured children at very low risk of emergent surgery: A national trauma registry study

ObjectiveThe number of pediatric trauma patients requiring surgical interventions has been steadily decreasing allowing for a judicious approach to immediately available resources. This study aimed to derive and validate a prediction rule that reliably identifies injured children who are at very low risk for requiring emergency surgery upon emergency department (ED) arrival. MethodsA retrospective cohort study of data included in the Israeli National Trauma Registry from January 1, 2011, through December 31, 2020, was conducted. We included children aged 0–14 years who presented to EDs from the scene of injury and were hospitalized. We excluded patients transferred between facilities or with isolated burns. The primary outcome was emergency operative intervention (EOI) performed within one hour of ED arrival. We tested mechanism, GCS, heart rate, and blood pressure as candidate predictors. We then randomized patients to two cohorts, derived and internally validated a prediction rule. ResultsDuring the study period, 83,859 children met enrollment criteria. The median age was 6 years (IQR 2–10) and 56,867 (67.8 %) were male; 75,450 (90.0 %) sustained blunt trauma. One hundred sixty-nine (0.20 %) children underwent EOI. In the derivation and validation cohorts, 34,138 (81.4 %) and 34,271 (81.7 %) patients, were classified as low risk based on blunt trauma mechanism, normal GCS (15), and low-risk heart rate (according to age). Of those, 8 (0.02 %) and 13 (0.04 %) required an EOI, respectively. In the validation cohort, the prediction rule for EOI had a sensitivity of 84 % (95 % CI 75–91), a specificity of 82 % (95 % CI 81–82), and a negative predictive value of 99.96 % (95 % CI 99.94–99.98). Among children with an Injury Severity Score>15, the sensitivity was 87 % (95 % CI 77–94), the specificity of 57 % (95 % CI 54–59), and the negative predictive value was 98.97 % (95 % CI 98.13–99.44). ConclusionsA limited set of physiologic parameters, readily available at hospital admission can effectively identify injured children at very low risk for emergent surgery. For these children, immediate deployment of surgical resources may not be necessary.

Polygenic and socioeconomic contributions to nicotine use and cardiometabolic health in early mid-life.

Early mid-life is marked by accumulating risks for cardiometabolic illness linked to health-risk behaviors like nicotine use. Identifying polygenic indices (PGI) has enriched scientific understanding of the cumulative genetic contributions to behavioral and cardiometabolic health, though few studies have assessed these associations alongside socioeconomic (SES) and lifestyle factors. Drawing on data from 2,337 individuals from the United States participating in the National Longitudinal Study of Adolescent to Adult Health, the current study assesses the fraction of variance in five related outcomes - use of conventional and electronic cigarettes, body mass index (BMI), waist circumference, and glycosylated hemoglobin (A1c) - explained by PGI, SES, and lifestyle. Regression models on African ancestry (AA) and European ancestry (EA) subsamples reveal that the fraction of variance explained by PGI ranges across outcomes. While adjusting for sex and age, PGI explained 3.5%, 2.2%, and 0% in the AA subsample of variability in BMI, waist circumference, and A1c, respectively (in the EA subsample these figures were 7.7%, 9.4%, and 1.3%). The proportion of variance explained by PGI in nicotine-use outcomes is also variable. Results further indicate that PGI and SES are generally complementary, accounting for more variance in the outcomes when modeled together versus separately. PGI are gaining attention in population health surveillance, but polygenic variability might not align clearly with health differences in populations or surpass SES as a fundamental cause of health disparities. We discuss future steps in integrating PGI and SES to refine population health prediction rules. Study findings point to the complementary relationship of polygenic indices (PGI) and socioeconomic indicators in explaining population variance in nicotine outcomes and cardiometabolic wellness. Population health surveillance and prediction rules would benefit from the combination of information from both polygenic and socioeconomic risks. Additionally, the risk for electronic cigarette use among users of conventional cigarettes may have a genetic component tied to the cumulative genetic propensity for heavy smoking. Further research on PGI for vaping is needed.

Early stages of covalent organic framework formation imaged in operando

Covalent organic frameworks (COFs) are a functional material class able to harness, convert and store energy. However, after almost 20 years of research, there are no coherent prediction rules for their synthesis conditions. This is partly because of an incomplete picture of nucleation and growth at the early stages of formation. Here we use the optical technique interferometric scattering microscopy (iSCAT)1–3 for in operando studies of COF polymerization and framework formation. We observe liquid–liquid phase separation, pointing to the existence of structured solvents in the form of surfactant-free (micro)emulsions in conventional COF synthesis. Our findings show that the role of solvents extends beyond solubility to being kinetic modulators by compartmentation of reactants and catalyst. Taking advantage of these observations, we develop a synthesis protocol for COFs using room temperature instead of elevated temperatures. This work connects framework synthesis with liquid phase diagrams and thereby enables an active design of the reaction environment, emphasizing that visualization of chemical reactions by means of light-scattering-based techniques can be a powerful approach for advancing rational materials synthesis.

Telephone triage of chest pain in out-of-hours primary care: external validation of a symptom-based prediction rule to rule out acute coronary syndromes.

Telephone triage is pivotal for evaluating the urgency of patient care, and in the Netherlands, the Netherlands Triage Standard (NTS) demonstrates moderate discrimination for chest pain. To address this, the Safety First Prediction Rule (SFPR) was developed to improve the safety of ruling out acute coronary syndrome (ACS) during telephone triage. We conducted an external validation of the SFPR using data from the TRACE study, a retrospective cohort study in out-of-hours primary care. We evaluated the diagnostic accuracy assessment for ACS, major adverse cardiovascular events (MACE), and major events within 6 weeks. Moreover, we compared its performance with that of the NTS algorithm. Among 1404 included patients (57.3% female, 6.8% ACS, 8.6% MACE), the SFPR demonstrated good discrimination for ACS (C-statistic: 0.79; 95%-CI: 0.75-0.83) and MACE (C-statistic: 0.79; 95%-CI: 0.0.76-0.82). Calibration was satisfactory, with overestimation observed in high-risk patients for ACS. The SFPR (risk threshold 2.5%) trended toward higher sensitivity (95.8% vs. 86.3%) and negative predictive value (99.3% vs. 97.6%) with a lower negative likelihood ratio (0.10 vs. 0.34) than the NTS algorithm. The SFPR proved robust for risk stratification in patients with acute chest pain seeking out-of-hours primary care in the Netherlands. Further prospective validation and implementation are warranted to refine and establish the rule's clinical utility.

PECARN prediction rules for CT imaging of children presenting to the emergency department with blunt abdominal or minor head trauma: a multicentre prospective validation study

The intra-abdominal injury and traumatic brain injury prediction rules derived by the Pediatric Emergency Care Applied Research Network (PECARN) were designed to reduce inappropriate use of CT in children with abdominal and head trauma, respectively. We aimed to validate these prediction rules for children presenting to emergency departments with blunt abdominal or minor head trauma. For this prospective validation study, we enrolled children and adolescents younger than 18 years presenting to six emergency departments in Sacramento (CA), Dallas (TX), Houston (TX), San Diego (CA), Los Angeles (CA), and Oakland (CA), USA between Dec 27, 2016, and Sept 1, 2021. We excluded patients who were pregnant or had pre-existing neurological disorders preventing examination, penetrating trauma, injuries more than 24 h before arrival, CT or MRI before transfer, or high suspicion of non-accidental trauma. Children presenting with blunt abdominal trauma were enrolled into an abdominal trauma cohort, and children with minor head trauma were enrolled into one of two age-segregated minor head trauma cohorts (younger than 2 years vs aged 2 years and older). Enrolled children were clinically examined in the emergency department, and CT scans were obtained at the attending clinician's discretion. All enrolled children were evaluated against the variables of the pertinent PECARN prediction rule before CT results were seen. The primary outcome of interest in the abdominal trauma cohort was intra-abdominal injury undergoing acute intervention (therapeutic laparotomy, angiographic embolisation, blood transfusion, intravenous fluid for ≥2 days for pancreatic or gastrointestinal injuries, or death from intra-abdominal injury). In the age-segregated minor head trauma cohorts, the primary outcome of interest was clinically important traumatic brain injury (neurosurgery, intubation for >24 h for traumatic brain injury, or hospital admission ≥2 nights for ongoing symptoms and CT-confirmed traumatic brain injury; or death from traumatic brain injury). 7542 children with blunt abdominal trauma and 19 999 children with minor head trauma were enrolled. The intra-abdominal injury rule had a sensitivity of 100·0% (95% CI 98·0-100·0; correct test for 145 of 145 patients with intra-abdominal injury undergoing acute intervention) and a negative predictive value (NPV) of 100·0% (95% CI 99·9-100·0; correct test for 3488 of 3488 patients without intra-abdominal injuries undergoing acute intervention). The traumatic brain injury rule for children younger than 2 years had a sensitivity of 100·0% (93·1-100·0; 42 of 42) for clinically important traumatic brain injuries and an NPV of 100·0%; 99·9-100·0; 2940 of 2940), whereas the traumatic brain injury rule for children aged 2 years and older had a sensitivity of 98·8% (95·8-99·9; 168 of 170) and an NPV of 100·0% (99·9-100·0; 6015 of 6017). The two children who were misclassified by the traumatic brain injury rule were admitted to hospital for observation but did not need neurosurgery. The PECARN intra-abdominal injury and traumatic brain injury rules were validated with a high degree of accuracy. Their implementation in paediatric emergency departments can therefore be considered a safe strategy to minimise inappropriate CT use in children needing high-quality care for abdominal or head trauma. The Eunice Kennedy Shriver National Institute of Child Health and Human Development.

Extracting predictive rules from time series of model outputs of continuous clinical predictive models

Extracting predictive rules from time series of model outputs of continuous clinical predictive models