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

Progress in the study of pentraxin-3(PTX-3) as a biomarker for sepsis

Sepsis is a intricate pathological process characterized by life-threatening organ dysfunction resulting from a dysregulated host response to infection. It stands as a prominent cause of mortality among critically ill patients globally. The pivotal focus in sepsis management lies in the early identification and prompt administration of antimicrobial agents. Owing to the constraints of current diagnostic methodologies, marked by insufficient sensitivity and delayed outcomes, extensive research has been undertaken to ascertain novel biomarkers for sepsis. In this review, we provide an overview discussing the latest advancements in the study of PTX-3 as a biomarker for sepsis. We acknowledge pivotal discoveries from preceding research and engage in discourse regarding the challenges and limitations confronted by PTX-3 as a sepsis biomarker.

Application of the Geriatric Trauma Outcome Score in a Rural Setting

OBJECTIVE

To retrospectively apply the Geriatric Trauma Outcome (GTO) score to the patient population of a rural South Central Appalachian level 1 trauma center and identify the potential utility of the GTO score in guiding goals of care discussions.

METHODS

Trauma registry data was extracted for 5,627 patients aged 65+ from 2017 to 2021. GTO score was calculated for each patient. Descriptive statistics were calculated for age, Injury Severity Score (ISS), GTO score, receipt of red blood cells, discharge status, and code status. A simple logistic regression model was used to determine the relationship between GTO score and discharge status. The probability of mortality was then calculated using GTO score, and the distribution of code status among patients with ≤50, 51-75%, and >75% probability of mortality was examined.

RESULTS

For every 10-point increase in GTO score, odds of mortality increased by 79% (OR = 1.79; P < .001). Patients had an estimated 50% probability of mortality with a GTO score of 156, 75% with 174, and 99% with a score of 234, respectively. Seventeen patients had a GTO score associated with >75% probability of mortality. Of those 17 patients, four retained a full code status.

CONCLUSIONS

Our analysis demonstrates that the GTO score is a validated measure in a rural setting and can be an easily calculated metric to help determine a geriatric patient's probability of mortality following a trauma. The results of our study also found that GTO score can be used to inform goals of care discussions with patients.

Futility in acute care surgery: first do no harm

The consequences of the delivery of futile or potentially ineffective medical care and interventions are devastating on the healthcare system, our patients and their families, and healthcare providers. In emergency situations in particular, determining if escalating invasive interventions will benefit a frail and/or severely critically ill patient can be exceedingly difficult. In this review, our objective is to define the problem of potentially ineffective care within the specialty of acute care surgery and describe strategies for improving the care of our patients in these difficult situations.

Mortality prediction upon hospital admission - the value of clinical assessment: A retrospective, matched cohort study

Accurate prediction of mortality upon hospital admission is of great value, both for the sake of patients and appropriate resources' allocation. A myriad of assessment tools exists for this purpose. The evidence relating to the comparative value of clinical assessment versus established indexes are scarce. We analyzed the accuracy of a senior physician's clinical assessment in a retrospective cohort of patients in a crude, general patients' population and later on a propensity matched patients' population. In one department of internal medicine in a tertiary hospital, of 9891 admitted patients, 973 (10%) were categorized as prone to death in a 6-months' duration by a senior physician. The risk of death was significantly higher for these patients [73.1% vs 14.1% mortality within 180 days; hazard ratio (HR) = 7.58; confidence intervals (CI) 7.02-8.19, P < .001]. After accounting for multiple, other patients' variables associated with increased risk of mortality, the correlation remained significant (HR = 3.25; CI 2.85-3.71, P < .001). We further performed a propensity matching analysis (a subgroup of 710 patients, subdivided to two groups with 355 patients each): survival rates were as low as 45% for patients categorized as prone to death compared to 78% in patients who weren't categorized as such (P < .001). Reliance on clinical evaluation, done by an experienced senior physician, is an appropriate tool for mortality prediction upon hospital admission, achieving high accuracy rates.

SURvival PRediction In SEverely Ill Patients Study-The Prediction of Survival in Critically Ill Patients by ICU Physicians

The surprise question, "Would I be surprised if this patient died in the next 12 months?" is a tool to identify patients at high risk of death in the next year. Especially in the situation of an ICU admission, it is important to recognize patients who could and could not have the benefits of an intensive treatment in the ICU department.

Design and Setting

A single-center, prospective, observational cohort study was conducted between April 2013 and April 2018, in ICU Gelre hospitals, location Apeldoorn.

Patients

A total of 3,140 patients were included (57% male) with a mean age of 63.5 years. Seven-hundred thirteen patients (23%) died within 1 year.

Interventions

The physician answered three different surprise question's with either "yes" or "no": "I expect that the patient is going to survive the ICU admission" (surprise question 1), "I expect that the patient is going to survive the hospital stay" (surprise question 2), and "I expect that the patient is going to survive one year after ICU admission" (surprise question 3). We tested positive and negative predicted values of the surprise questions, the mean accuracy of the surprise questions, and kappa statistics.

Measurements and Main Results

The positive and negative predictive values of the surprise questions for ICU admission, hospital admission, and 1-year survival were, respectively, 64%/94%, 59%/92%, and 60%/86%. Accordingly, the mean accuracy and kappa statistics were 93% (95% CI, 92-94%), κ equals to 0.43, 89% (95% CI, 88-90%), κ equals to 0.40, and 81% (95% CI, 80-82%), κ equals to 0.43.

Conclusions

The frequently overlooked simple and cheap surprise question is probably an useful tool to evaluate the prognosis of acutely admitted critically ill patients.

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

OBJECTIVES

To determine clinician accuracy in the identification and prediction of multiple organ dysfunction syndrome.

DESIGN

Prospective cohort study.

SETTING

University of Michigan's C.S. Mott Children's Hospital PICU.

PATIENTS

Patients admitted to the PICU with an anticipated PICU length of stay greater than 48 hours.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

For each patient, the clinical team (attending, fellow, resident/nurse practitioner) was surveyed regarding existing and anticipated organ dysfunction. The primary outcomes were clinicians' accuracy at identifying multiple organ dysfunction syndrome and predicting new or progressive multiple organ dysfunction syndrome, compared to the objective assessment of multiple organ dysfunction syndrome using Proulx criteria. We also measured sensitivity, specificity, negative and positive predictive values, and negative and positive likelihood ratios of clinician assessments. We tested for differences in accuracy by clinician type using chi-square tests. Clinicians rated their confidence in prediction on a 5-point Likert scale. There were 476 eligible PICU admissions, for whom 1,218 surveys were completed. Multiple organ dysfunction syndrome was present in 89 patients (18.7%) at enrollment, and new or progressive multiple organ dysfunction syndrome occurred in 39 (8.2%). Clinicians correctly identified multiple organ dysfunction syndrome with 79.9% accuracy and predicted additional organ dysfunction with 82.6% accuracy. However, the positive and negative likelihood ratios for new or progressive multiple organ dysfunction syndrome prediction were 3.0 and 0.7, respectively, indicating a weak relationship between the clinician prediction and development of new or progressive multiple organ dysfunction syndrome. The positive predictive value of new or progressive multiple organ dysfunction syndrome prediction was just 22.1%. We found no differences in accuracy by clinician type for either identification of multiple organ dysfunction syndrome (80.2% vs 78.2% vs 81.0%; p = 0.57) or prediction of new or progressive multiple organ dysfunction syndrome (84.8% vs 82.8% vs 80.3%; p = 0.26) for attendings, fellows, and residents/nurse practitioners, respectively. There was a weak correlation between the confidence and accuracy of prediction (pairwise correlation coefficient, 0.26; p < 0.001).

CONCLUSIONS

PICU clinicians correctly identified multiple organ dysfunction syndrome and predicted new or progressive multiple organ dysfunction syndrome with 80% accuracy. However, only 8% of patients developed new or progressive multiple organ dysfunction syndrome, so accuracy was largely due to true negative predictions. The positive predictive value for new or progressive multiple organ dysfunction syndrome prediction was just 22%. Accuracy did not differ by clinician type, but was correlated with self-rated confidence and was higher for negative predictions.

Legislating how critical care physicians discuss and implement do-not-resuscitate orders

A few weeks ago, Texas took an unprecedented position on unilateral DNRs by passing Senate Bill (SB) 11, which requires patient/surrogate consent for writing DNR orders. The motivation behind the bill was based on the drafters' beliefs that physicians frequently write unilateral DNR orders. SB 11, however, does not stop at requiring physicians to seek consent for DNR orders. Instead, the legislation uncharacteristically exceeds what is typically within the scope and role boundaries for lawmakers by legislating how physicians discuss and implement DNR orders. We contend that this bill is ethically problematic and will have far-reaching, negative consequences that will affect how critical care medicine is practiced. In what follows, we describe how proponents' arguments rely on several ethical assumptions, and we describe potential negative impacts stemming from this legislation. Finally, we offer an alternative approach that would mitigate proponents' concerns. We believe SB 11 and our analytic deconstruction of it should serve as "lessons learned" for other states considering similar legislation.

The ability of intensive care unit physicians to estimate long-term prognosis in survivors of critical illness

PURPOSE

To assess the reliability of physicians' prognoses for intensive care unit (ICU) survivors with respect to long-term survival and health related quality of life (HRQoL).

METHODS

We performed an observational cohort-study in a single mixed tertiary ICU in The Netherlands. ICU survivors with a length of stay >48h were included. At ICU discharge, one-year prognosis was estimated by physicians using the four-option Sabadell score to record their expectations. The outcome of interest was poor outcome, which was defined as dying within one-year follow-up, or surviving with an EuroQoL5D-3L index <0.4.

RESULTS

Among 1399 ICU survivors, 1068 (76%) subjects were expected to have a good outcome; 243 (18%) a poor long-term prognosis; 43 (3%) a poor short-term prognosis, and 45 (3%) to die in hospital (i.e. Sabadell score levels). Poor outcome was observed in 38%, 55%, 86%, and 100% of these groups respectively (concomitant c-index: 0.61). The expected prognosis did not match observed outcome in 365 (36%) patients. This was almost exclusively (99%) due to overoptimism. Physician experience did not affect results.

CONCLUSIONS

Prognoses estimated by physicians incorrectly predicted long-term survival and HRQoL in one-third of ICU survivors. Moreover, inaccurate prognoses were generally the result of overoptimistic expectations of outcome.

Pentraxin 3 as a prognostic biomarker in patients with systemic inflammation or infection

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.