Identifying critically ill children in Malawi: A modified qSOFA score for low-resource settings

In low-resource settings, a reliable bedside score for timely identification of children at risk of dying, could help focus resources and improve survival. The rapid bedside Liverpool quick Sequential Organ Failure Assessment (LqSOFA) uses clinical parameters only and performed well in United Kingdom cohorts. A similarly quick clinical assessment-only score has however not yet been developed for paediatric populations in sub-Saharan Africa. In a development cohort of critically ill children in Malawi, we calculated the LqSOFA scores using age-adjusted heart rate and respiratory rate, capillary refill time and Blantyre Coma Scale, and evaluated its prognostic performance for mortality. An improved score, the Blantyre qSOFA (BqSOFA), was developed (omitting heart rate, adjusting respiratory rate cut-off values and adding pallor), subsequently validated in a second cohort of Malawian children, and compared with an existing score (FEAST-PET). Prognostic performance for mortality was evaluated using area under the receiver operating characteristic curve (AUC). Mortality was 15.4% in the development (N = 493) and 22.0% in the validation cohort (N = 377). In the development cohort, discriminative ability (AUC) of the LqSOFA to predict mortality was 0.68 (95%-CI: 0.60-0.76). The BqSOFA and FEAST-PET yielded AUCs of 0.84 (95%-CI:0.79-0.89) and 0.83 (95%-CI:0.77-0.89) in the development cohort, and 0.74 (95%-CI:0.68-0.79) and 0.76 (95%-CI:0.70-0.82) in the validation cohort, respectively. We developed a simple prognostic score for Malawian children based on four clinical parameters which performed as well as a more complex score. The BqSOFA might be used to promptly identify critically ill children at risk of dying and prioritize hospital care in low-resource settings.

A Novel Framework for Phenotyping Children With Suspected or Confirmed Infection for Future Biomarker Studies

Background: The limited diagnostic accuracy of biomarkers in children at risk of a serious bacterial infection (SBI) might be due to the imperfect reference standard of SBI. We aimed to evaluate the diagnostic performance of a new classification algorithm for biomarker discovery in children at risk of SBI. Methods: We used data from five previously published, prospective observational biomarker discovery studies, which included patients aged 0- <16 years: the Alder Hey emergency department (n = 1,120), Alder Hey pediatric intensive care unit (n = 355), Erasmus emergency department (n = 1,993), Maasstad emergency department (n = 714) and St. Mary's hospital (n = 200) cohorts. Biomarkers including procalcitonin (PCT) (4 cohorts), neutrophil gelatinase-associated lipocalin-2 (NGAL) (3 cohorts) and resistin (2 cohorts) were compared for their ability to classify patients according to current standards (dichotomous classification of SBI vs. non-SBI), vs. a proposed PERFORM classification algorithm that assign patients to one of eleven categories. These categories were based on clinical phenotype, test outcomes and C-reactive protein level and accounted for the uncertainty of final diagnosis in many febrile children. The success of the biomarkers was measured by the Area under the receiver operating Curves (AUCs) when they were used individually or in combination. Results: Using the new PERFORM classification system, patients with clinically confident bacterial diagnosis ("definite bacterial" category) had significantly higher levels of PCT, NGAL and resistin compared with those with a clinically confident viral diagnosis ("definite viral" category). Patients with diagnostic uncertainty had biomarker concentrations that varied across the spectrum. AUCs were higher for classification of "definite bacterial" vs. "definite viral" following the PERFORM algorithm than using the "SBI" vs. "non-SBI" classification; summary AUC for PCT was 0.77 (95% CI 0.72-0.82) vs. 0.70 (95% CI 0.65-0.75); for NGAL this was 0.80 (95% CI 0.69-0.91) vs. 0.70 (95% CI 0.58-0.81); for resistin this was 0.68 (95% CI 0.61-0.75) vs. 0.64 (0.58-0.69) The three biomarkers combined had summary AUC of 0.83 (0.77-0.89) for "definite bacterial" vs. "definite viral" infections and 0.71 (0.67-0.74) for "SBI" vs. "non-SBI." Conclusion: Biomarkers of bacterial infection were strongly associated with the diagnostic categories using the PERFORM classification system in five independent cohorts. Our proposed algorithm provides a novel framework for phenotyping children with suspected or confirmed infection for future biomarker studies.

Performance of seven different paediatric early warning scores to predict critical care admission in febrile children presenting to the emergency department: a retrospective cohort study

OBJECTIVE

Paediatric Early Warning Scores (PEWS) are widely used in the UK, but the heterogeneity across tools and the limited data on their predictive performance represent obstacles to improving best practice. The standardisation of practice through the proposed National PEWS will rely on robust validation. Therefore, we compared the performance of the National PEWS with six other PEWS currently used in NHS hospitals, for their ability to predict critical care (CC) admission in febrile children attending the emergency department (ED).

DESIGN

Retrospective single-centre cohort study.

SETTING

Tertiary hospital paediatric ED.

PARTICIPANTS

A total of 11 449 eligible febrile ED attendances were identified from the electronic patient record over a 2-year period. Seven PEWS scores were calculated (Alder Hey, Bedside, Bristol, National, Newcastle and Scotland PEWS, and the Paediatric Observation Priority Score, using the worst observations recorded during their ED stay.

OUTCOMES

The primary outcome was CC admission within 48 hours, the secondary outcomes were hospital length of stay (LOS) >48 hours and sepsis-related mortality.

RESULTS

Of 11 449 febrile children, 134 (1.2%) were admitted to CC within 48 hours of ED presentation, 606 (5.3%) had a hospital LOS >48 hours. 10 (0.09%) children died, 5 (0.04%) were sepsis-related. All seven PEWS demonstrated excellent discrimination for CC admission (range area under the receiver operating characteristic curves (AUC) 0.91-0.95) and sepsis-related mortality (range AUC 0.95-0.99), most demonstrated moderate discrimination for hospital LOS (range AUC 0.69-0.75). In CC admission threshold analyses, bedside PEWS (AUC 0.90; 95% CI 0.86 to 0.93) and National PEWS (AUC 0.90; 0.87-0.93) were the most discriminative, both at a threshold of ≥6.

CONCLUSIONS

Our results support the use of the proposed National PEWS in the paediatric ED for the recognition of suspected sepsis to improve outcomes, but further validation is required in other settings and presentations.

Accuracy of a Modified qSOFA Score for Predicting Critical Care Admission in Febrile Children

BACKGROUND AND OBJECTIVES

The identification of life-threatening infection in febrile children presenting to the emergency department (ED) remains difficult. The quick Sequential Organ Failure Assessment (qSOFA) was only derived for adult populations, implying an urgent need for pediatric scores. We developed and validated a novel, adapted qSOFA score (Liverpool quick Sequential Organ Failure Assessment [LqSOFA]) and compared its performance with qSOFA, Pediatric Early Warning Score (PEWS), and National Institute for Health and Care Excellence (NICE) high-risk criteria in predicting critical care (CC) admission in febrile children presenting to the ED.

METHODS

The LqSOFA (range, 0-4) incorporates age-adjusted heart rate, respiratory rate, capillary refill, and consciousness level on the Alert, Voice, Pain, Unresponsive scale. The primary outcome was CC admission within 48 hours of ED presentation, and the secondary outcome was sepsis-related mortality. LqSOFA, qSOFA, PEWS, and NICE high-risk criteria scores were calculated, and performance characteristics, including area under the receiver operating characteristic curve, were calculated for each score.

RESULTS

In the initial (n = 1121) cohort, 47 CC admissions (4.2%) occurred, and in the validation (n = 12 241) cohort, 135 CC admissions (1.1%) occurred, and there were 5 sepsis-related deaths. In the validation cohort, LqSOFA predicted CC admission with an area under the receiver operating characteristic curve of 0.81 (95% confidence interval [CI], 0.76 to 0.86), versus qSOFA (0.66; 95% CI, 0.60 to 0.71), PEWS (0.93; 95% CI, 0.90 to 0.95), and NICE high-risk criteria (0.81; 95% CI, 0.78 to 0.85). For predicting CC admission, the LqSOFA outperformed the qSOFA, with a net reclassification index of 10.4% (95% CI, 1.0% to 19.9%).

CONCLUSIONS

In this large study, we demonstrate improved performance of the LqSOFA over qSOFA in identifying febrile children at risk for CC admission and sepsis-related mortality. Further validation is required in other settings.

A small multimarker panel using simple immunohistochemistry methods is an adjunct to stage for cutaneous melanoma prognosis

Melanoma is an aggressive cancer. Outcomes can vary significantly for lesions within the same pathological stage - a problem of increasing relevance with the promise of adjuvant treatments on the basis of immune checkpoint modulators and targeted therapies. The use of a panel of prognostic molecular biomarkers as an adjunct to stage represents a possible solution. Immunohistochemistry-based biomarkers offer greater potential for translation into clinical practice than biomarkers utilizing more complex methods. Many immunohistochemistry-based biomarkers have been identified through discovery studies, but rigorous validation of these is scarce. We take the first steps towards validating a combination of three such biomarkers in a prognostic panel - 5hmC, ki-67 and p16. Immunohistochemistry was performed on a cohort of 50 melanomas to determine the expression of 5hmC, ki-67 and p16. 5hmC and p16 showed statistically significant differences in metastasis-free survival between low-score and high-score groups, whereas the use of all three biomarkers together with stage could predict the 5-year metastasis risk more accurately than stage alone. Our results suggest that the use of multimarker panels to improve the accuracy of prognostic predictions is feasible and worthy of further study. We have shown that a small immunohistochemistry-based panel utilizing simple, inexpensive, reproducible methods can be an effective adjunct to stage in prognostic prediction. A follow-up study consisting of a large cohort of melanomas is now indicated to continue the development of the prognostic panel.