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Record W4295539328 · doi:10.5114/ait.2022.118972

Guidelines for treatment of acute pain in children – the consensus statement of the Section of Paediatric Anaesthesiology and Intensive Therapy of the Polish Society of Anaesthesiology and Intensive Therapy

2022· article· en· W4295539328 on OpenAlexaboutno aff
Maciej Cettler, Marzena Zielińska, Jowita Rosada-Kurasińska, Anna Kubica-Cielińska, Konrad Jarosz, Alicja Bartkowska‐Śniatkowska

Bibliographic record

VenueAnaesthesiology Intensive Therapy · 2022
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntensive carePain therapyAnesthesiologyIntensive care medicinePhysical therapyAnesthesia

Abstract

fetched live from OpenAlex

RATIONALE AND SCOPE OF THE GUIDELINES Pain is a subjective unpleasant sensory and emotional experience. Acute pain occurs irrespective of age and has a prevalence of about 5% of the general population. Surgical procedures and painful diagnostic procedures are the main causes of this unpleasant and dangerous phenomenon for hospitalized children. It should be remembered that maintaining homeostasis in a child undergoing surgery is also affected by provision of an adequate level of analgesia and sedation as well as nerve conduction block within the surgical site. Even though both paediatric anaesthesiologists and paediatric surgeons know that the therapeutic activities during the perioperative period should be focused on ensuring sufficient analgesia and haemodynamic stability in surgical patients, as many as 70% of children undergoing surgery may experience moderate to severe pain [1-7]. Moreover, pain management is one of the fundamental human rights, i.e. the right to relief of suffering. According to the declaration of the 13th World Congress on Pain in Montreal (September 2010), this right also includes children [8, 9]. In Poland, the law was amended in 2017, and now each patient is guaranteed the right to relief and treatment of pain (Journal of Laws of 2017, item 836). Unfortunately, this right is not always respected in paediatric patients. Many factors contribute to ineffective analgesia in paediatric patients, mainly insufficient knowledge and lack of experience (concerning the use of opioids in particular), as well as lack of management standards, the negative attitude of the personnel or poor organization [10-13]. In hospitals which, as a result of organizational changes, have implemented analgesic treatment regimens and regularly educate their personnel in these issues, both efficiency and effectiveness of pain relief in children are high [14]. For many years, Polish paediatric anaesthesio-logists have been promoting and streamlining the analgesic management of children, which has led to the development of the present publication. The regimens presented in it are based on both the latest medical reports and many years of the authors' experience. The classes of recommendations and levels of evidence have been prepared (Tables 1 and 2, respectively). The presented recommendations were formulated based on a survey of medical reports published in the last two decades.

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)0.008
metaresearch head score (Gemma)0.021
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: Methods · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0080.007

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 head0.044
GPT teacher head0.318
Teacher spread0.275 · 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
GenreMethods

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

Citations47
Published2022
Admission routes1
Has abstractyes

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