Variables associated with unplanned general adult ICU admission in hospitalised patients: protocol for a systematic review

Comparison of Reverse Triage with National Early Warning Score, Sequential Organ Failure Assessment and Charlson Comorbidity Index to classify medical inpatients of an Italian II level hospital according to their resource's need

Resource allocation in our overcrowded hospitals would require classification of inpatients according to the severity of illness, the evolving risk and the clinical complexity. Reverse triage (RT) is a method used in disasters to identify inpatients according to their use of hospital resources. The aim of this observational prospective study is to evaluate the use of RT in medical inpatients of an Italian Hospital and to compare the RT score with National Early Warning Score, Sequential Organ Failure Assessment and Charlson Comorbidity Index. Cluster sampling was performed on high dependency unit (HDU), geriatrics (Ger) and internal medicine (IM) wards. We calculate RT, NEWS, SOFA and CCI from inpatient charts. Length of stay (LOS), transfer to a higher level of care, death and discharge date were collected after 30 days. We obtained demographics, comorbidities, severity and clinical complexity of 260 inpatients. We highlighted differences in NEWS, SOFA and CCI in the three divisions. On the contrary RT score was uniformly high (median 7), with 85% of patients with RT = 8. NEWS, SOFA and CCI were higher in patients with higher RT score. We used the sum of the interventions listed by RT (RT sum) as a proxy of the level of care needed. RT-sum showed moderate correlation with NEWS (r = 0.52 Spearman, p < 0.001). RT-sum was the highest in HDU, related to the evolving severity of HDU patients. Ger patients that showed the highest CCI score (with all patients in the CCI ≥ 3 category) had the second highest RT-sum. RT score showed similar values in the majority of the inpatients regardless of differences in NEWS, SOFA and CCI in different ward subgroups. RT-sum is related both to evolving severity (NEWS) and to clinical complexity (CCI). RT and NEWS could predict inpatient level of care and resource need associated with CCI.

Patient centred variables with univariate associations with unplanned ICU admission: a systematic review

Background

Multiple predictive scores using Electronic Patient Record data have been developed for hospitalised patients at risk of clinical deterioration. Methods used to select patient centred variables for inclusion in these scores varies. We performed a systematic review to describe univariate associations with unplanned Intensive Care Unit (ICU) admission with the aim of assisting model development for future scores that predict clinical deterioration.

Methods

Data sources were MEDLINE, EMBASE, CINAHL, CENTRAL and the Cochrane Database of Systematic Reviews. Included studies were published since 2000 describing an association between patient centred variables and unplanned ICU admission determined using univariate analysis. Two authors independently screened titles, abstracts and full texts against inclusion and exclusion criteria. DistillerSR (Evidence Partners, Canada, Ottawa, Ontario) software was used to manage the data and identify duplicate search results. All screening and data extraction forms were implemented within DistillerSR. Study quality was assessed using an adapted version of the Newcastle-Ottawa Scale. Variables were analysed for strength of association with unplanned ICU admission.

Results

The database search yielded 1520 unique studies; 1462 were removed after title and abstract review; 57 underwent full text screening; 16 studies were included. One hundred and eighty nine variables with an evaluated univariate association with unplanned ICU admission were described.

Discussion

Being male, increasing age, a history of congestive cardiac failure or diabetes, a diagnosis of hepatic disease or having abnormal vital signs were all strongly associated with ICU admission.

Conclusion

These findings will assist variable selection during the development of future models predicting unplanned ICU admission.

Trial registration

This study is a component of a larger body of work registered in the ISRCTN registry (ISRCTN12518261).

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0820-1) contains supplementary material, which is available to authorized users.

Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: Development and validation of a multivariable model

Aim

The National Early Warning System (NEWS) is based on vital signs; the Laboratory Decision Tree Early Warning Score (LDT-EWS) on laboratory test results. We aimed to develop and validate a new EWS (the LDTEWS:NEWS risk index) by combining the two and evaluating the discrimination of the primary outcome of unanticipated intensive care unit (ICU) admission or in-hospital mortality, within 24 h.

Methods

We studied emergency medical admissions, aged 16 years or over, admitted to Oxford University Hospitals (OUH) and Portsmouth Hospitals (PH). Each admission had vital signs and laboratory tests measured within their hospital stay. We combined LDT-EWS and NEWS values using a linear time-decay weighting function imposed on the most recent blood tests. The LDTEWS:NEWS risk index was developed using data from 5 years of admissions to PH, and validated on a year of data from both PH and OUH. We tested the risk index’s ability to discriminate the primary outcome using the c-statistic.

Results

The development cohort contained 97,933 admissions (median age = 73 years) of which 4723 (4.8%) resulted inhospital death and 1078 (1.1%) in unanticipated ICU admission. We validated the risk index using data from PH (n = 21,028) and OUH (n = 16,383). The risk index showed a higher discrimination in the validation sets (c-statistic value (95% CI)) (PH, 0.901 (0.898–0.905); OUH, 0.916 (0.911–0.921)), than NEWS alone (PH, 0.877 (0.873–0.882); OUH, 0.898 (0.893–0.904)).

Conclusions

The LDTEWS:NEWS risk index increases the ability to identify patients at risk of deterioration, compared to NEWS alone.

Chief physicians' attitudes towards early warning score systems in Switzerland: Results of a cross-sectional survey

RATIONALE, AIMS AND OBJECTIVES

Early warning score systems (EWS-S) have been shown to be valuable tools to recognize otherwise unnoticed clinical deterioration (CDET) of patients. They have been associated with fewer unplanned transfers to the intensive care unit (UTICU) and lower in-hospital mortality. Little is known about their current usage in Switzerland and about the attitudes towards such tools among chief physicians. We aimed to assess the use of EWS-S in Switzerland and the attitudes of chief physicians towards EWS-S depending on previously experienced CDET followed by UTICU, reanimation, or death.

METHODS

Chief physicians of medical and surgical departments from all acute care hospitals in Switzerland were asked to participate within a project that aims to develop recommendations for the use of EWS-S in Switzerland (n = 118). The explorative study assessed perceived CDET, which led to UTICU, reanimation, or death of a patient, the knowledge and usage about different EWS-S and attitudes towards EWS-S in a written questionnaire. Means and percentages were used, and differences were assessed with independent t tests, chi-square, or Fisher exact test, as appropriate.

RESULTS

Adverse events based on CDET were reported frequently, and awareness among chief physicians was high. Less than half of the chief physicians knew tools that systematically assess CDET with one-fifth of responders reporting using tools at their department. Previous experiences of UTICU, reanimation, or death after due to CDET were associated with more positive attitudes towards EWS-S.

CONCLUSIONS

Adverse events based on CDET of patients are frequent and the awareness of this problem is high among chief physicians. Positive attitudes were more common with previous experiences of adverse events due to CDET. Our results strengthen the argumentation that the recommendation and future implementation of EWS-S in Switzerland would be meaningful.