Development of a new definition of maternal near miss based on organ dysfunction in Latin America and the Caribbean: A prospective multicenter cohort study.

BACKGROUND: There has been debate over whether the existing World Health Organization (WHO) criteria accurately represent the severity of maternal near misses. OBJECTIVE: This study assessed the diagnostic accuracy of two WHO clinical and laboratory organ dysfunction markers for determining the best cutoff values in a Latin American setting. METHODS: A prospective multicenter cohort study was conducted in five Latin American countries. Patients with severe maternal complications were followed up from admission to discharge. Organ dysfunction was determined using clinical and laboratory data, and participants were classified according to severe maternal outcomes. This study compares the diagnostic criteria of Latin American Centre for Perinatology, Network for Adverse Maternal Outcomes (CLAP/NAMO) to WHO standards. RESULTS: Of the 698 women studied, 15.2% had severe maternal outcomes. Most measured variables showed significant differences between individuals with and without severe outcomes (all P-values <0.05). Alternative cutoff values suggested by CLAP/NAMOs include pH ≤7.40, lactate ≥2.3 mmol/L, respiratory rate ≥ 24 bpm, oxygen saturation ≤ 96%, PaO2/FiO2 ≤ 342 mmHg, platelet count ≤189 × 109 × mm3, serum creatinine ≥0.8 mg/dL, and total bilirubin ≥0.67 mg/dL. No significant differences were found when comparing the diagnostic performance of the CLAP/NAMO criteria to that of the WHO standards. CONCLUSION: The CLAP/NAMO values were comparable to the WHO maternal near-miss criteria, indicating that the WHO standards might not be superior in this population. These findings suggest that maternal near-miss thresholds can be adapted regionally, improving the identification and management of severe maternal complications in Latin America.

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

OBJECTIVE: 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. PATIENTS AND METHODS: We conducted a retrospective cross-sectional observational study of patients aged ≥60 years 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. RESULTS: 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. CONCLUSION: 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.

Comparing 11 early warning scores and three shock indices in early sepsis prediction in the emergency department.

BACKGROUND: This study aimed to evaluate the discriminatory performance of 11 vital sign-based early warning scores (EWSs) and three shock indices in early sepsis prediction in the emergency department (ED). METHODS: We performed a retrospective study on consecutive adult patients with an infection over 3 months in a public ED in Hong Kong. The primary outcome was sepsis (Sepsis-3 definition) within 48 h of ED presentation. Using c-statistics and the DeLong test, we compared 11 EWSs, including the National Early Warning Score 2 (NEWS2), Modified Early Warning Score, and Worthing Physiological Scoring System (WPS), etc., and three shock indices (the shock index [SI], modified shock index [MSI], and diastolic shock index [DSI]), with Systemic Inflammatory Response Syndrome (SIRS) and quick Sequential Organ Failure Assessment (qSOFA) in predicting the primary outcome, intensive care unit admission, and mortality at different time points. RESULTS: We analyzed 601 patients, of whom 166 (27.6%) developed sepsis. NEWS2 had the highest point estimate (area under the receiver operating characteristic curve [AUROC] 0.75, 95%CI 0.70-0.79) and was significantly better than SIRS, qSOFA, other EWSs and shock indices, except WPS, at predicting the primary outcome. However, the pooled sensitivity and specificity of NEWS2 ≥ 5 for the prediction of sepsis were 0.45 (95%CI 0.37-0.52) and 0.88 (95%CI 0.85-0.91), respectively. The discriminatory performance of all EWSs and shock indices declined when used to predict mortality at a more remote time point. CONCLUSION: NEWS2 compared favorably with other EWSs and shock indices in early sepsis prediction but its low sensitivity at the usual cut-off point requires further modification for sepsis screening.

Framework for personalized prediction of treatment response in relapsing-remitting multiple sclerosis: a replication study in independent data.

BACKGROUND: Individualizing and optimizing treatment of relapsing-remitting multiple sclerosis patients is a challenging problem, which would benefit from a clinically valid decision support. Stühler et al. presented black box models for this aim which were developed and internally evaluated in a German registry but lacked external validation. METHODS: In patients from the French OFSEP registry, we independently built and validated models predicting being free of relapse and free of confirmed disability progression (CDP), following the methodological roadmap and predictors reported by Stühler. Hierarchical Bayesian models were fit to predict the outcomes under 6 disease-modifying treatments given the individual disease course up to the moment of treatment change. Data was temporally split on 2017, and models were developed in patients treated earlier (n = 5517). Calibration curves, discrimination, mean squared error (MSE) and relative percentage of root MSE (RMSE%) were assessed by external validation of models in more-recent patients (n = 3768). Non-Bayesian fixed-effects GLMs were also applied and their outcomes were compared to these of the Bayesian ones. For both, we modelled the number of on-therapy relapses with a negative binomial distribution, and CDP occurrence with a binomial distribution. RESULTS: The performance of our temporally-validated relapse model (MSE: 0.326, C-Index: 0.639) is potentially superior to that of Stühler's (MSE: 0.784, C-index: 0.608). Calibration plots revealed miscalibration. Our CDP model (MSE: 0.072, C-Index: 0.777) was also better than its counterpart (MSE: 0.131, C-index: 0.554). Results from non-Bayesian fixed-effects GLM models were similar to the Bayesian ones. CONCLUSIONS: The relapse and CDP models rebuilt and externally validated in independent data could compare and strengthen the credibility of the Stühler models. Their model-building strategy was replicable.

Assessing acutely ill children in general practice using the National PEWS and LqSOFA clinical scores: a retrospective cohort study.

BACKGROUND: Clinical tools are needed in general practice to help identify seriously ill children. The Liverpool quick Sequential Organ Failure Assessment (LqSOFA) was validated in an Emergency Department and performed well. The National Paediatric Early Warning score (PEWS) has been introduced in hospitals throughout England with hopes for implementation in general practice. AIM: To validate the LqSOFA and National PEWS in general practice. DESIGN/SETTING: Secondary analysis of 6,703 children <5 years presenting to 225 general practices in England and Wales with acute illnesses, linked to hospital data. METHOD: Variables from the LqSOFA and National PEWS were mapped onto study data to calculate score totals. A primary outcome of admission within two days of GP consultation was used to calculate sensitivity, specificity, negative predictive values (NPV), positive predictive values (PPV) and area-under-the-curve (AUC). RESULTS: 104/6,703 children were hospitalised within two days (pre-test probability 1.6%). The sensitivity of the LqSOFA was 30.6% (95% confidence interval 21.8% - 41.0%), with a specificity of 84.7% (83.7% - 85.6%), PPV of 3.0% (2.1% - 4.4%), NPV of 98.7% (98.4% - 99.0%), and AUC of 0.58 (0.53 - 0.63). The sensitivity of the National PEWS was 81.0% (71.0% - 88.1%), with a specificity of 32.5% (31.2% - 33.8%); PPV of 1.9% (1.5% - 2.5%); NPV of 99.1% (98.4% - 99.4%) and AUC of 0.66 (0.59 - 0.72). CONCLUSION: Although the NPVs appear useful, due to low pre-test probabilities rather than discriminative ability, neither tool accurately identified hospitalisations. Unconsidered use by GPs could result in unsustainable referrals.

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.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Prospective Validation of a Simple Risk Score to Predict Hospitalization during the Omicron Phase of COVID-19.

INTRODUCTION: We previously developed a simple risk score with 3 items (age, patient report of dyspnea, and any relevant comorbidity), and in this report validate it in a prospective sample of patients, stratified by vaccination status. METHODS: Data were abstracted from a structured electronic health record of primary care and urgent care 8 patients with COVID-19 in the Lehigh Valley Health Network from 11/21/2021 and 10/31/2022 9 (Omicron variant). Our previously derived risk score was calculated for each of 19,456 patients, 10 and the likelihood of hospitalization was determined. Area under the ROC curve was calculated. RESULTS: We were able to place 13,239 patients (68%) in a low-risk group with only a 0.16% risk of 13 hospitalization. The moderate risk group with 5622 patients had a 2.2% risk of hospitalization 14 and might benefit from close outpatient follow-up, whereas the high-risk group with only 574 15 patients (2.9% of all patients) had an 8.9% risk of hospitalization and may require further 16 evaluation. Area under the curve was 0.844. DISCUSSION: We prospectively validated a simple risk score for primary and urgent care patients with COVID1919 that can support outpatient triage decisions around COVID-19.

Temporal validation of a clinical prediction rule for distinguishing locomotive syndromes in community-dwelling older adults: A cross-sectional study from the DETECt-L study.

Objectives: Clinical prediction rules are used to discriminate patients with locomotive syndrome and may enable early detection. This study aimed to validate the clinical predictive rules for locomotive syndrome in community-dwelling older adults. Methods: We assessed the clinical prediction rules for locomotive syndrome in a cross-sectional setting. The age, sex, and body mass index of participants were recorded. Five physical function tests-grip strength, single-leg standing time, timed up-and-go test, and preferred and maximum walking speeds-were measured as predictive factors. Three previously developed clinical prediction models for determining the severity of locomotive syndrome were assessed using a decision tree analysis. To assess validity, the sensitivity, specificity, likelihood ratio, and post-test probability of the clinical prediction rules were calculated using receiver operating characteristic curve analysis for each model. Results: Overall, 280 older adults were included (240 women; mean age, 74.8 ± 5.2 years), and 232 (82.9%), 68 (24.3%), and 28 (10.0%) participants had locomotive syndrome stages ≥ 1, ≥ 2, and = 3, respectively. The areas under the receiver operating characteristics curves were 0.701, 0.709, and 0.603, in models 1, 2, and 3, respectively. The accuracies of models 1 and 2 were moderate. Conclusions: These findings indicate that the models are reliable for community-dwelling older adults.

Validation of the PediBIRN-7 clinical prediction rule for pediatric abusive head trauma.

BACKGROUND: The PediBIRN-7 clinical prediction rule incorporates the (positive or negative) predictive contributions of completed abuse evaluations to estimate abusive head trauma (AHT) probability after abuse evaluation. Applying definitional criteria as proxies for AHT and non-AHT ground truth, it performed with sensitivity 0.73 (95 % CI: 0.66-0.79), specificity 0.87 (95 % CI: 0.82-0.90), and ROC-AUC 0.88 (95 % CI: 0.85-0.92) in its derivation study. OBJECTIVE: To validate the PediBIRN-7's AHT prediction performance in a novel, equivalent, patient population. PARTICIPANTS AND SETTINGS: Consecutive, acutely head-injured children <3 years hospitalized for intensive care across eight sites between 2017 and 2020 with completed skeletal surveys and retinal exams (N = 342). METHODS: Secondary analysis of an existing, cross-sectional, prospective dataset, including assignment of patient-specific estimates of AHT probability, calculation of AHT prediction performance measures (ROC-AUC, sensitivity, specificity, predictive values), and completion of sensitivity analyses to estimate best- and worst-case prediction performances. RESULTS: Applying the same definitional criteria, the PediBIRN-7 performed with sensitivity 0.74 (95 % CI: 0.66-0.81), specificity 0.77 (95 % CI: 0.70-0.83), and ROC-AUC 0.83 (95 % CI: 0.78-0.88). The reduction in ROC-AUC was statistically insignificant (p = .07). Applying physicians' final consensus diagnoses as proxies for AHT and non-AHT ground truth, the PediBIRN-7 performed with sensitivity 0.73 (95 % CI: 0.66-0.79), specificity 0.87 (95 % CI: 0.82-0.90), and ROC-AUC 0.90 (95 % CI: 0.87-0.94). Sensitivity analyses demonstrated minimal changes in rule performance. CONCLUSION: The PediBIRN-7's overall AHT prediction performance has been validated in a novel, equivalent, patient population. Its patient-specific estimates of AHT probability can inform physicians' AHT-related diagnostic reasoning after abuse evaluation.

The role of echocardiography in pulmonary embolism for the prediction of in-hospital mortality: a retrospective study.

PURPOSE: Pulmonary Embolism (PE) is the third leading cause of cardiovascular death, following myocardial infarction and stroke. The latest European Society of Cardiology (ESC) guidelines on PE recommend short-term prognostic stratification based on right ventricular (RV) overload detected by transthoracic echocardiography (TTE) or contrast-enhanced chest CT. The aim of the study is to find out which of the signs of right ventricular dysfunction best predicts in-hospital mortality (IHM). METHODS: This is a monocentric, retrospective study including adult patients admitted from the emergency department with a c-e cCT confirmed diagnosis of PE between January 2018 and December 2022 who underwent a TTE within 48 h. RESULTS: 509 patients (median age 76 years [IQR 67-84]) were included, with 7.1% IHM. At univariate analysis, RV/LV ratio > 1 (OR 2.23, 95% CI 1.1-4.5), TAPSE < 17 mm (OR 4.73, 95% CI 2.3-9.8), the D-shape (OR 3.73, 95% CI 1.71-8.14), and LVEF < 35% (OR 5.78, 95% CI 1.72-19.47) resulted significantly correlated with IHM. However, at multivariate analysis including also haemodynamic instability, PESI class > II, and abnormal hs-cTnI levels, only LVEF < 35% (OR 5.46, 95% CI 1.32-22.61) resulted an independent predictor of IHM. CONCLUSION: Despite the recognised role of TTE in the early management of patients with circulatory shock and suspected PE, signs of RV dysfunction have been shown to be poor predictors of IHM, whereas severely reduced LVEF is an independent risk factor for in-hospital death.