Comparison of physician prediction with 2 prognostic scoring systems in predicting 2-year mortality after intensive care admission: A linked-data cohort study

Litton, Edward; Ho, Kwok M.; Webb, Steven A R

doi:10.1016/j.jcrc.2011.11.013

Cited by 15 publications

(9 citation statements)

References 26 publications

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“…By contrast, in 5% of surveys, clinicians failed to predict NP-MODS that occurred (ie, false negative prediction). These findings are consistent with prior studies showing that false positive predictions of pediatric( 16) and adult (13,17,28) mortality are more common than false negative predictions. Clinicians may have overestimated the development of NP-MODs for several reasons.…”

Section: Discussionsupporting

confidence: 92%

“…The better clinicians can anticipate the development of new organ failure, the better they can weigh the risks/benefits of diagnostic or therapeutic interventions and decide the optimal management plan for an individual patient. Previous studies comparing clinician intuition to prediction models for mortality have shown clinicians perform better (34,35), or equally as well (28,36). However, clinician predictions may still be improved when combined with a prediction model (36).…”

Section: Discussionmentioning

confidence: 99%

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Clinician Accuracy in Identifying and Predicting Organ Dysfunction in Critically Ill Children

Carlton

Paice

et al. 2020

Critical Care Medicine

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Clinician Accuracy in Identifying and Predicting Organ Dysfunction in Critically Ill Children

Carlton

Paice

et al. 2020

Critical Care Medicine

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“…However, in clinical practice, these scoring systems have important limitations. Data collection requires multiple laboratory measurements and the computation of multiple variables and is labor intensive and expensive [ 45 – 47 ]. Therefore, the application of these scoring systems may be limited, particularly when health care is subject to financial constraint.…”

Section: Discussionmentioning

confidence: 99%

Pentraxin 3 as a Prognostic Biomarker in Patients with Systemic Inflammation or Infection

Liu

et al. 2014

Mediators of Inflammation

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Purpose. The long pentraxin 3 (PTX3) is a key component of the humoral arm of the innate immune system. PTX3 is produced locally in response to proinflammatory stimuli. We reviewed the usefulness of systemic levels of PTX3 in critically ill patients with systemic inflammatory response syndrome (SIRS), sepsis, and bacteremia, focusing on its diagnostic and prognostic value. Methods. A PubMed search on PTX3 was conducted. The list of papers was narrowed to original studies of critically ill patients. Eleven papers on original studies of critically ill patients that report on PTX3 in SIRS, sepsis, or bacteremia were identified. Results. Systematic levels of PTX3 have little diagnostic value in critically ill patients with SIRS, sepsis, or bacteremia. Systemic levels of PTX3, however, have superior prognostic power over other commonly used biological markers in these patients. Systemic levels of PTX3 correlate positively with markers of organ dysfunction and severity-of-disease classification system scores. Finally, systemic levels of PTX3 remain elevated in the acute phase and decreased on recovery. Notably, the age of the patients and underlying disease affect systemic levels of PTX3. Conclusions. The diagnostic value of PTX3 is low in patients with sepsis. Systemic levels of PTX3 have prognostic value and may add to prognostication of patients with SIRS or sepsis, complementing severity-of-disease classification systems and other biological markers.

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“…2-4 Poses and colleagues showed that critical care clinicians have excellent overall discriminating ability concerning survival (separating patients into those who survive and those who die) and that attending physicians’ predictions were better calibrated (how well predicted probabilities agreed with actual observed risk) than those of house-officers. 5 Elsewhere, Poses and colleagues point out that accurate prognostic calibration can be an important determinant of quality of care.…”

mentioning

confidence: 99%

Differences Between Attendings’ and Fellows’ Perceptions of Futile Treatment in the Intensive Care Unit at One Academic Health Center

et al. 2015

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Purpose Knowing when patients are too ill to benefit from intensive care is essential for clinicians to recommend aggressive or palliative care as appropriate. To explore prognostic ability among critical care fellows, the authors compared fellows’ and attendings’ assessments of futile critical care and evaluated factors associated with assessments. Method Thirty-six attendings and 14 fellows in intensive care units at the University of California, Los Angeles, were surveyed daily for 3 months (December 2011–March 2012) to identify patients perceived as receiving futile treatment. Frequencies of futile treatment assessments and reasons listed by attendings versus fellows were compared. Predictors of futile treatment assessments by provider type were assessed using multivariate probit models. Results Attendings made 6,897 assessments on 1,125 patients; fellows made 4,407 assessments on 773 patients. Fellows assessed 161 (20.8%) patients as receiving futile treatment, compared to attendings (123 [10.9%] patients, P < .001), and listed fewer reasons that treatment was futile (P < .001). Fellows were more likely to assess a patient as receiving futile treatment by the second day, whereas attendings took four days. Patients assessed as receiving futile treatment by fellows were less likely than patients so assessed by attendings to die in the hospital (51% vs. 68%, P = .003) and within 6 months (62% vs. 85%, P < .001). Conclusions Fellows made earlier assessments and judged more patients to be receiving futile treatment than attendings, and their assessments were less predictive of mortality, suggesting that assessment of treatment appropriateness develops with experience.

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Comparison of physician prediction with 2 prognostic scoring systems in predicting 2-year mortality after intensive care admission: A linked-data cohort study

Cited by 15 publications

References 26 publications

Clinician Accuracy in Identifying and Predicting Organ Dysfunction in Critically Ill Children

Clinician Accuracy in Identifying and Predicting Organ Dysfunction in Critically Ill Children

Pentraxin 3 as a Prognostic Biomarker in Patients with Systemic Inflammation or Infection

Differences Between Attendings’ and Fellows’ Perceptions of Futile Treatment in the Intensive Care Unit at One Academic Health Center

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