Using risk prediction tools in survivors of in-hospital cardiac arrest

A comparison of Simplified Acute Physiology Score II and Sepsis-related Organ Failure Assessment Score for prediction of mortality after Intensive Care Unit cardiac arrest

BACKGROUND

This study investigates the predictive value and suitable cutoff values of the Sepsis-related Organ Failure Assessment Score (SOFA) and Simplified Acute Physiology Score II (SAPS-II) to predict mortality during or after Intensive Care Unit Cardiac Arrest (ICU-CA).

METHODS

In this secondary analysis the ICU database of a German university hospital with five ICU was screened for all ICU-CA between 2016-2019. SOFA and SAPS-II were used for prediction of mortality during ICU-CA, hospital-stay and one-year-mortality. Receiver operating characteristic curves (ROC), area under the ROC (AUROC) and its confidence intervals were calculated. If the AUROC was significant and considered "acceptable," cutoff values were determined for SOFA and SAPS-II by Youden Index. Odds ratios and sensitivity, specificity, positive and negative predictive values were calculated for the cutoff values.

RESULTS

A total of 114 (78 male; mean age: 72.8±12.5 years) ICU-CA were observed out of 14,264 ICU-admissions (incidence: 0.8%; 95% CI: 0.7-1.0%). 29.8% (N.=34; 95% CI: 21.6-39.1%) died during ICU-CA. SOFA and SAPS-II were not predictive for mortality during ICU-CA (P>0.05). Hospital-mortality was 78.1% (N.=89; 95% CI: 69.3-85.3%). SAPS-II (recorded within 24 hours before and after ICU-CA) indicated a better discrimination between survival and death during hospital stay than SOFA (AUROC: 0.81 [95% CI: 0.70-0.92] vs. 0.70 [95% CI: 0.58-0.83]). A SAPS-II-cutoff-value of 43.5 seems to be suitable for prognosis of hospital mortality after ICU-CA (specificity: 87.5%, sensitivity: 65.6%; SAPS-II>43.5: 87.5% died in hospital; SAPS-II<43.5: 65.6% survived; odds ratio:13.4 [95% CI: 3.25-54.9]). Also for 1-year-mortality (89.5%; 95% CI: 82.3-94.4) SAPS-II showed a better discrimination between survival and death than SOFA: AUROC: 0.78 (95% CI: 0.65-0.91) vs. 0.69 (95% CI: 0.52-0.87) with a cutoff value of the SAPS-II of 40.5 (specificity: 91.7%, sensitivity: 64.3%; SAPS-II>40.5: 96.4% died; SAPS-II<40.5: 42.3% survived; odd ratio: 19.8 [95% CI: 2.3-168.7]).

CONCLUSIONS

Compared to SOFA, SAPS-II seems to be more suitable for prediction of hospital and 1-year-mortality after ICU-CA.

Outcomes of in-hospital cardiac arrests during and after office hours in a single tertiary centre in Singapore

INTRODUCTION

In-hospital cardiac arrest (IHCA) is a significant healthcare burden with a paucity of data in Singapore. Various factors, including time of cardiac arrest, affect survival from acute resuscitation.

METHODS

This was a retrospective cohort study that evaluated the characteristics of patients who sustained an IHCA, including the Cardiac Arrest Survival Post Resuscitation In-hospital (CASPRI) scores, and the impact of arrest time in 220 consecutive cardiac arrests occurring in a tertiary hospital. The primary outcome was rate of return of spontaneous circulation (ROSC) post-IHCA, and the secondary outcome was 90-day survival.

RESULTS

The ROSC rate among patients with IHCA out of and during office hours was 69.5% and 75.4%, respectively (odds ratio [OR] 0.74, 95% confidence interval [CI] 0.39-1.42). There were no statistically significant differences between the CASPRI scores of both groups. After adjusted analysis, the OR of ROSC post-IHCA out of office hours as compared to that during office hours was 0.78 (95% CI 0.39-1.53). The 90-day survival rate of patients who had an IHCA out of and during office hours was 25.7% and 34.6%, respectively (OR 0.65, 95% CI 0.32-1.34). The adjusted OR of 90-day survival was 0.66 (0.28-1.59).

CONCLUSION

The results of this observational study did not show an association between the timing of cardiac arrest and the rate of ROSC or 90-day survival.

The value of a machine learning algorithm to predict adverse short-term outcome during resuscitation of patients with in-hospital cardiac arrest: a retrospective study

Background and importance Guidelines recommend that hospital emergency teams locally validate criteria for termination of cardiopulmonary resuscitation in patients with in-hospital cardiac arrest (IHCA). Objective To determine the value of a machine learning algorithm to predict failure to achieve return of spontaneous circulation (ROSC) and unfavourable functional outcome from IHCA using only data readily available at emergency team arrival. Design Retrospective cohort study. Setting and participants Adults who experienced an IHCA were attended to by the emergency team. Outcome measures and analysis Demographic and clinical data typically available at the arrival of the emergency team were extracted from the institutional IHCA database. In addition, outcome data including the Cerebral Performance Category (CPC) score count at hospital discharge were collected. A model selection procedure for random forests with a hyperparameter search was employed to develop two classification algorithms to predict failure to achieve ROSC and unfavourable (CPC 3-5) functional outcomes. Main results Six hundred thirty patients were included, of which 390 failed to achieve ROSC (61.9%). The final classification model to predict failure to achieve ROSC had an area under the receiver operating characteristic curve of 0.9 [95% confidence interval (CI), 0.89-0.9], a balanced accuracy of 0.77 (95% CI, 0.75-0.79), an F1-score of 0.78 (95% CI, 0.76-0.79), a positive predictive value of 0.88 (0.86-0.91), a negative predictive value of 0.61 (0.6-0.63), a sensitivity of 0.69 (0.66-0.72), and a specificity of 0.84 (0.8-0.88). Five hundred fifty-nine subjects experienced an unfavourable outcome (88.7%). The final classification model to predict unfavourable functional outcomes from IHCA at hospital discharge had an area under the receiver operating characteristic curve of 0.93 (95% CI, 0.92-0.93), a balanced accuracy of 0.59 (95% CI, 0.57-0.61), an F1-score of 0.94 (95% CI, 0.94-0.95), a positive predictive value of 0.91 (0.9-0.91), a negative predictive value of 0.57 (0.48-0.66), a sensitivity of 0.98 (0.97-0.99), and a specificity of 0.2 (0.16-0.24). Conclusion Using data readily available at emergency team arrival, machine learning algorithms had a high predictive power to forecast failure to achieve ROSC and unfavourable functional outcomes from IHCA while cardiopulmonary resuscitation was still ongoing; however, the positive predictive value of both models was not high enough to allow for early termination of resuscitation efforts.

CT imaging in idiopathic out-of-hospital cardiac arrest: An assessment of current practice and diagnostic utility

Idiopathic Out-Of-Hospital Cardiac Arrest (OHCA) requires urgent treatment. Early Computed Tomography (CT) imaging may be useful to aid diagnosis. We aimed to determine current CT imaging practice, safety, and diagnostic value in this patient population. This study was a single-centre, retrospective cohort study of patients presenting to the Emergency Department (ED) of the Royal Infirmary of Edinburgh with idiopathic non-traumatic OHCA and Return Of Spontaneous Circulation (ROSC). Between 1st January 2016 and 31st December 2019, 140 of 156 (90%) eligible patients underwent 195 CT scans identifying the cause of OHCA in 6 (4%). CT head diagnosed one ischaemic and three haemorrhagic strokes, and CT pulmonary angiogram diagnosed one acute coronary syndrome and one pulmonary embolism. CT head (134), CT pulmonary angiogram (25) and CT cervical spine (16) were the commonest scans. 68 of 195 (35%) CT scans showed important pathology, mostly secondary to OHCA. CT imaging was safe with no cases of contrast nephropathy, allergic reaction, or other complications. The diagnostic value of CT imaging in this patient population was limited. However, imaging was a valuable method of identifying other important secondary pathology.

Associations between initial serum pH value and outcomes of pediatric out-of-hospital cardiac arrest

INTRODUCTION

Pediatric out-of-hospital cardiac arrest (OHCA) is one of the most critical conditions seen in the emergency department (ED). Although initial serum pH value is reported to be associated with outcome in adult OHCA patients, the association is unclear in pediatric OHCA patients. Thus, we aimed to identify the association between initial pH value and outcome among pediatric OHCA patients.

METHODS

This study was a retrospective analysis of a multicenter prospective cohort registry (Japanese Association for Acute Medicine out-of-hospital cardiac arrest registry) from 87 hospitals in Japan. We included pediatric OHCA patients younger than 16 years of age who were registered in this registry between June 2014 and December 2017. Of the 34,754 patients in the database, 458 patients were ultimately included in the analysis. We equally divided the patients into four groups, based on their initial pH value, and conducted a multivariate logistic regression analysis to calculate the adjusted odds ratios of the initial pH value on hospital arrival with their 95% confidence intervals for the primary outcome.

RESULTS

The median (interquartile range) age was 1 (0-6) year, and 77.9% (357/458) of the first monitored rhythm was asystole. The primary outcome was 1-month survival. The overall 1-month survival was 13.3% (61/458), and a 1-month favorable neurologic outcome was seen in 5.2% (24/458) of cases. The adjusted odds ratios and 95% confidence intervals for the pH 6.81-6.64, pH 6.63-6.47, pH <6.47, and pH unknown groups compared with the pH ≥6.82 group for 1-month survival were 0.39 (0.16-0.97), 0.13 (0.04-0.44), 0.03 (0.00-0.24), and 0.07 (0.02-0.21), respectively.

CONCLUSIONS

This study demonstrated the association between the initial pH value on hospital arrival and 1-month survival among pediatric OHCA patients.

In Hospitals With More Nurses Who Have Baccalaureate Degrees, Better Outcomes For Patients After Cardiac Arrest

In 2010, prompted by compelling evidence that demonstrated better patient outcomes in hospitals with higher percentages of nurses with a bachelor of science in nursing (BSN), the Institute of Medicine recommended that 80 percent of the nurse workforce be qualified at that level or higher by 2020. Using data from the American Heart Association's Get With the Guidelines-Resuscitation registry (for 2013-18), RN4CAST-US hospital nurse surveys (2015-16), and the American Hospital Association (2015), we found that each 10-percentage-point increase in the hospital share of nurses with a BSN was associated with 24 percent greater odds of surviving to discharge with good cerebral performance among patients who experienced in-hospital cardiac arrest. Lower patient-to-nurse ratios on general medical and surgical units were also associated with significantly greater odds of surviving with good cerebral performance. These findings contribute to the growing body of evidence that supports policies to increase access to baccalaureate-level education and improve hospital nurse staffing.

One-Year Survival after Inhospital Cardiac Arrest-Does Prearrest Sepsis Matter?

AIM

Cardiac arrest is not a common complication of sepsis, although sepsis has been recognized as one condition behind cardiac arrest. Our aim was to evaluate the prevalence of sepsis among patients with inhospital cardiac arrest (IHCA), and to determine if sepsis is associated with inferior outcome after IHCA.

METHODS

All consecutive emergency team dispatches in Turku University Hospital in 2011 to 2014 (n = 607) were retrospectively reviewed to identify the patients undergoing cardiopulmonary resuscitation (CPR) for IHCA (n = 301). The patient records were reviewed for the criteria of severe sepsis, organ dysfunction, and chronic comorbidities before IHCA. Outcome was followed for 1 year.

RESULTS

The criteria for prearrest severe sepsis were met by 83/301 (28%) of the patients, and 93/301 (31%) had multiorgan dysfunction (3 or more organ systems). The patients with severe sepsis had higher mortality than those without severe sepsis, increasing from 30-day mortalities of 63/83 (76%) and 151/218 (69%), respectively (P = 0.256), to 1-year mortalities of 72/83 (87%) and 164/218 (75%), respectively (P = 0.030). Emergency admission, age, immunosuppression, DM, multiorgan dysfunction, and a nonshockable rhythm were independent predictors of 1-year mortality by multivariate logistic regression analysis. Six out of 83 patients with severe sepsis before IHCA (7%) survived 1 year with good neurological outcome (CPC scale 1).

CONCLUSIONS

A high proportion of patients with IHCA have sepsis and multiorgan dysfunction, and their prognosis is worse than the prognosis of patients with IHCA in general.

Survival after in-hospital cardiac arrest among cerebrovascular disease patients

Stroke is a leading cause of death and disability, and while preferences for cardiopulmonary resuscitation (CPR) are frequently discussed, there is limited evidence detailing outcomes after CPR among acute cerebrovascular neurology (inclusive of stroke, subarachnoid hemorrhage (SAH)) patients. Systematic review and meta-analysis of PubMed and Cochrane libraries from January 1990 to December 2016 was conducted among stroke patients undergoing in-hospital CPR. Primary data from studies meeting inclusion criteria at two levels were extracted: 1) studies reporting survival to hospital discharge after CPR with cerebrovascular primary admitting diagnosis, and 2) studies reporting survival to hospital discharge after CPR with cerebrovascular comorbidity. Meta-analysis generated weighted, pooled survival estimates for each population. Of 818 articles screened, there were 176 articles (22%) that underwent full review. Three articles met primary inclusion criteria, with an estimated 8% (95% Confidence Interval (CI) 0.01, 0.14) rate of survival to hospital discharge from a pooled sample of 561 cerebrovascular patients after in-hospital CPR. Twenty articles met secondary inclusion criteria, listing a cerebrovascular comorbidity, with an estimated rate of survival to hospital discharge of 16% (95% CI 0.14, 0.19). All studies demonstrated wide variability in adherence to Utstein guidelines, and neurological outcomes were detailed in only 6 (26%) studies. Among the few studies reporting survival to hospital discharge after CPR among acute cerebrovascular patients, survival is lower than general inpatient populations. These findings synthesize the limited empirical basis for discussions about resuscitation among stroke patients, and highlight the need for more disease stratified reporting of outcomes after inpatient CPR.

Predicting in-hospital mortality for initial survivors of acute respiratory compromise (ARC) events: Development and validation of the ARC Score

AIM

Acute respiratory compromise (ARC) is a common and highly morbid event in hospitalized patients. To date, however, few investigators have explored predictors of outcome in initial survivors of ARC events. In the present study, we leveraged the American Heart Association's Get With The Guidelines^®-Resuscitation (GWTG-R) ARC data registry to develop a prognostic score for initial survivors of ARC events.

METHODS

Using GWTG-R ARC data, we identified 13,193 index ARC events. These events were divided into a derivation cohort (9807 patients) and a validation cohort (3386 patients). A score for predicting in-hospital mortality was developed using multivariable modeling with generalized estimating equations.

RESULTS

The two cohorts were well balanced in terms of baseline demographics, illness-types, pre-event conditions, event characteristics, and overall mortality. After model optimization, nine variables associated with the outcome of interest were included. Age, hypotension preceding the event, and intubation during the event were the greatest predictors of in-hospital mortality. The final score demonstrated good discrimination in both the derivation and validation cohorts. The score was also very well calibrated in both cohorts. Observed average mortality was <10% in the lowest score category of both cohorts and >70% in the highest category, illustrating a wide range of mortality separated effectively by the scoring system.

CONCLUSIONS

In the present study, we developed and internally validated a prognostic score for initial survivors of in-hospital ARC events. This tool will be useful for clinical prognostication, selecting cohorts for interventional studies, and for quality improvement initiatives seeking to risk-adjust for hospital-to-hospital comparisons.