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Record W4387300980 · doi:10.1097/pcc.0000000000003353

Editor’s Choice Articles for October

2023· article· en· W4387300980 on OpenAlexaboutno aff
Robert C. Tasker

Bibliographic record

VenuePediatric Critical Care Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleEncephalopathySepsisSeptic shockContext (archaeology)Intensive care medicineHypoxemiaPediatricsInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

My three Editor’s Choices for the October issue of Pediatric Critical Care Medicine (PCCM) highlight important aspects of what is understood by brain involvement during critical illness. We now use a range in terminologies, but what do they mean and what is their significance? So, my three choices are: first, sepsis and “encephalopathy”; second, sepsis and “acute disorders of consciousness”; and third, outcome after “acquired brain injury.” The PCCM Connections for Readers focuses on team continuity during prolonged PICU admission. WHAT IS THE RELEVANCE OF A SEPSIS-RELATED PHENOTYPE WITH SHOCK, PERSISTENT HYPOXEMIA, AND ENCEPHALOPATHY? Sanchez-Pinto LN, Bennet T, Stroup EK, et al: Derivation, Validation, and Clinical Relevance of a Pediatric Sepsis Phenotype With Persistent Hypoxemia, Encephalopathy, and Shock (1). In my first Editor’s Choice we return to the topic of time course and trajectory in sepsis and septic shock (2–5), but with the added nuance of a phenotype that includes the term “encephalopathy.” However, what is meant by “encephalopathy” in this context? Our authors identified encephalopathy retrospectively using a Glasgow Coma Scale (GCS) score that was most frequently in the category 10 to 12 (1,6), which would be classified as a moderate severity injury in traumatic brain injury (TBI). The 2012–2018 cohort has over 15,000 pediatric patients with sepsis-associated multiple organ dysfunction syndrome (MODS) and the encephalopathy phenotype was present in 1-in-3 cases (1). Please read the report as well because the accompanying editorial which, together, provide important details about the meaning and trajectory of such brain symptomatology during sepsis-associated MODS (7). WHAT IS THE SIGNIFICANCE OF SEPSIS-INDUCED MULTIORGAN FAILURE ASSOCIATED WITH ACUTE DISORDER OF CONSCIOUSNESS? Cheung C, Kernan K, Berg RA, et al; Eunice Kennedy Shriver National Institute of Child Health and Human Development Collaborative Pediatric Critical Care Research Network: Acute Disorders of Consciousness in Pediatric Severe Sepsis and Organ Failure: Secondary Analysis of the Multicenter Phenotyping Sepsis-Induced Multiple Organ Failure Study (8). My next Editor’s Choice article is a secondary analysis of data from the multicenter, prospective PHENOMS (Phenotyping Sepsis-Induced Multiple Organ Failure Study) cohort, 2015–2017 (5,9). The authors defined “acute disorder of consciousness” as a GCS score below 12 in the absence of sedatives on the initial study day of sepsis-induced organ failure; therefore, in essence, a definition like the criterion for encephalopathy used in my first Editor’s Choice (1). In a population of 401 patients, 1-in-5 cases had the depressed GCS phenotype, and the authors go on to describe clinical and laboratory characteristics—another theme that we have followed closely in PCCM (5,9–11). The editorial gives us a broad view of how we can “unravel the intricate relationship between sepsis, organ dysfunction, and neurologic manifestations in pediatric patients” (12). As a reader of PCCM you may also want to review our recent material about timing of acute neurologic dysfunction in relation to sepsis recognition (13,14) and the choice of clinical assessment (15). Finally, also consider the computational phenotype of “acute brain dysfunction” regarding database research—based on using neuroimaging or electroencephalography as part of evaluating neurologic change—which had better diagnostic performance than the GCS in sepsis (16). WHAT IS THE TARGETED APPROACH TO ASSESSING 1-MONTH, POST-PICU, NEUROPSYCHOLOGICAL OUTCOMES IN SCHOOL-AGED CHILDREN WITH ACQUIRED BRAIN INJURY? Williams CN, Hall TA, Baker VA, et al: Follow-up After PICU Discharge for Patients With Acquired Brain Injury: The Role of an Abbreviated Neuropsychological Evaluation and a Return-to-School Program (17). My third Editor’s Choice article about brain health extends the Journal’s theme on follow-up programs and PICU outcomes and is a link between neurology during PICU admission and morbidity at follow-up. For example, in 2021, there was a scoping review of instruments and methods for assessing overall health after PICU admission (18) and, in 2022, there was description of a core outcome measurement set for evaluating PICU survivorship (19,20). The Journal also published three descriptions of structured follow-up by clinical programs in Canada, the United States, and the Netherlands (21–24). There was the most comprehensive and detailed clinical research analysis of physical, emotional/behavioral, and neurocognitive developmental outcomes 2−4 years after PICU admission in over 600 patients from a randomized clinical trial cohort (25,26). Two neurocritical programs in the US describe a multidisciplinary 1-month follow-up of 289 school-aged children at-risk of cognitive impairment, because of “acquired brain injury” most commonly due to TBI with GCS 9 to 13 (17); rather like the GCS of patients in my first two Editor’s Choices (see above). Of note here, the authors describe using an abbreviated battery of neuropsychological tests that proved useful in identifying new impairments and screening for referral to specialist services. There is an accompanying editorial (27). This third Editor’s Choice article (17), when considered in conjunction with the other choices (1,8), made me want to re-read the 1- and 3-month outcomes work of the LAPSE (Life After Pediatric Sepsis Evaluation) investigators in their 2014–2017 sepsis cohort (28,29), and their most recent publications (i.e., one also appearing in this month’s issue (30), and another with 12-month outcomes appearing later this year (31)). There is much to consider. “PCCM CONNECTIONS” FOR READERS This month’s topic for educational review is a Society of Critical Care Medicine (SCCM)-endorsed Special Article from the Lucile Packard Foundation PICU continuity panel (32). Thirty-seven experts have generated 17 consensus statements about continuity strategies for long-stay PICU patients. Please read the article and, as context, see the experts’ previous survey of contemporary practices and perceptions in US PICUs with training fellowship programs (33) and the accompanying editorial published in June 2023 (34). This Special Article adds to the Journal’s compendium on pediatric chronic critical illness. I recommend the scoping review on case definition of pediatric chronic critical illness (35) and the description of prevalence in a single center (36). Next, consider reading about an overlapping entity called pediatric complex chronic condition (or medical complexity); it has variable identification in US PICUs (37), yet accounts for high-frequency PICU utilization (38). Finally, read the qualitative analysis of clinical care strategies that support parents of children with complex chronic conditions, particularly during their child’s end-of-life care in the PICU (39,40).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.160
Threshold uncertainty score0.536

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.073
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0090.006
Open science0.0040.003
Research integrity0.0130.012
Insufficient payload (model declined to judge)0.1600.070

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.097
GPT teacher head0.422
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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