Good mortality prediction by Glasgow Coma Scale for neurosurgical patients

Use of the Neutrophil-to-Lymphocyte Ratio Improves the Accuracy of Outcome Prediction in Patients with Acute Traumatic Subdural Hematoma Undergoing Surgical Treatment

BACKGROUND

Traumatic brain injury is a major cause of disability and mortality worldwide. Acute traumatic subdural hematoma (TSDH) accounts for a large proportion of all traumatic brain injury cases. However, factors to predict postoperative prognosis in patients with acute TSDH are limited. Recently, it has been reported that inflammatory markers increase the accuracy of prognosis in various diseases. The neutrophil-to-lymphocyte ratio (NLR) is a marker for inflammation, which is easy to test, inexpensive, and can be performed quickly. However, the prognostic value of NLR in patients with acute TSDH remains controversial. This study therefore aimed to assess the predictive value of the admission and postoperative NLR in patients with acute TSDH who underwent surgical treatment.

METHODS

We retrospectively identified patients who underwent surgery for acute TSDH at our institute between April 2010 and August 2023. The NLR was calculated as the ratio of the absolute neutrophil count to the absolute lymphocyte count. Multivariable logistic regression analysis was subsequently applied to assess the independent predictors of 30-day mortality. In logistic regression analysis, multivariate analysis was performed using the backward elimination method for all P value<0.05 in the univariate analysis. Receiver-operating characteristic curve analysis was used to assess the predictive abilities of the postoperative 48-hour NLR and determine the cutoff values.

RESULTS

A total of 131 patients were enrolled, among whom the mortality within 1 month was 47.3% (62 patients). Initial NLR (P value = 0.905) was not strongly associated with mortality in patients with acute TSDH who underwent surgery. Only the postoperative 48-hour NLR (odds ratio, 1.103; 95% confidence interval, 1.051-1.157; P < 0.001) and Glasgow Coma Scale score at admission (odds ratio, 0.855; 95% confidence interval, 0.756-0.967; P = 0.012) were independent factors for 1-month mortality in the multivariate logistic analysis. The optimal cutoff value of the postoperative 48-hour NLR to distinguish between survival and nonsurvival was 15.786.

CONCLUSIONS

Initial NLR was not strongly associated with 1-month mortality in patients with acute TSDH who underwent surgery. However, the postoperative 48-hour NLR was associated with 1-month mortality.

A competing risk model analysis of dexmedetomidine of in-hospital mortality in subarachnoid hemorrhage patients

Subarachnoid hemorrhage (SAH) is a severe cerebrovascular disorder characterized by the sudden influx of blood into the subarachnoid space. The use of sedatives may be associated with the prognosis of SAH patients. We obtained SAH data from the MIMIC-IV database. The receiver operating characteristic curve, Delong test, and decision curve analysis were used to assess the predictive value of sedatives. Propensity score matching (PSM) method was applied to match samples at a 1:1 ratio. Logistic regression analysis, generalized linear regression analysis, and stratified analysis were used to investigate the association of the sedative with in-hospital mortality and length of hospital stay (LOS). Finally, a competing risk analysis was performed to evaluate the survival probability with two potential outcomes. Dexmedetomidine had a better prognosis value than Propofol and Midazolam. After PSM analysis, the Dexmedetomidine and the non-Dexmedetomidine groups had 248 samples each. The application of Dexmedetomidine reduced the risk of in-hospital mortality but might prolong the LOS. When considering in-hospital mortality as a competing risk factor for LOS, Dexmedetomidine was a protective factor for in-hospital mortality but had no significant relationship with LOS. In conclusion, treatment of Dexmedetomidine could reduce the risk of in-hospital mortality with satisfactory predictive efficiency.

The Predictive Value of the Verbal Glasgow Coma Scale in Traumatic Brain Injury: A Systematic Review

BACKGROUND

Traumatic brain injury (TBI) is a major global health concern, imposing significant burdens on individuals and healthcare systems. The Glasgow Coma Scale (GCS), a widely utilized instrument for evaluating neurological status, includes 3 variables: motor, verbal, and eye opening. The GCS plays a crucial role in TBI severity stratification. While extensive research has explored the predictive capabilities of the overall GCS score and its motor component, the Verbal Glasgow Coma Scale (V-GCS) has garnered less attention.

OBJECTIVE

To examine the predictive accuracy of the V-GCS in assessing outcomes in patients with TBI, with a particular focus on functional outcome and mortality. In addition, we intend to compare its predictive performance with other components of the GCS.

METHODS

A systematic review, based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was conducted utilizing the PubMed, Scopus, and Web of Science databases. Inclusion criteria encompassed 10 clinical studies involving patients with TBI, wherein the level of consciousness was assessed using the verbal GCS score. Predominant statistical measures employed were odds ratios (ORs) and area under the curve (AUC).

RESULTS

Recorded findings consistently underscore that lower V-GCS scores are associated with adverse functional outcomes and mortality in patients with TBI. Despite the predictive accuracy of the V-GCS, the Motor Glasgow Coma Scale (M-GCS) emerges as a superior predictor.

CONCLUSION

In the context of TBI outcome prediction, the V-GCS demonstrates its efficacy as a prognostic tool. However, the M-GCS exhibits superior performance compared with the V-GCS. These insights underscore the multifaceted nature of TBI assessment and emphasize the necessity of considering distinct components of the Glasgow Coma Scale for comprehensive evaluation. Further research is warranted to refine and improve the application of these predictive measures in clinical practice.

Electrical bioimpedance measurement and near-infrared spectroscopy in pediatric postoperative neurocritical care: a prospective observational study

Background

To investigate the clinical significance of the disturbance coefficient (DC) and regional cerebral oxygen saturation (rSO₂) as obtained through the use of electrical bioimpedance and near-infrared spectroscopy (NIRS) in pediatric neurocritical care.

Participants and methods

We enrolled 45 pediatric patients as the injury group and 70 healthy children as the control group. DC was derived from impedance analysis of 0.1 mA-50 kHz current via temporal electrodes. rSO₂ was the percentage of oxyhemoglobin measured from reflected NIR light on the forehead. DC and rSO₂ were obtained at 6, 12, 24, 48 and 72 h after surgery for the injury group and during the health screening clinic visit for the control group. We compared DC and rSO₂ between the groups, their changes over time within the injury group and their correlation with intracranial pressure (ICP), cerebral perfusion pressure (CPP), Glasgow coma scale (GCS) score, Glasgow outcome scale (GOS) score, and their ability to diagnose postoperative cerebral edema and predict poor prognosis.

Results

DC and rSO₂ were significantly lower in the injury group than in the control group. In the injury group, ICP increased over the monitoring period, while DC, CPP and rSO₂ decreased. DC was negatively correlated with ICP and positively correlated with GCS score and GOS score. Additionally, lower DC values were observed in patients with signs of cerebral edema, with a DC value of 86.5 or below suggesting the presence of brain edema in patients aged 6-16 years. On the other hand, rSO₂ was positively correlated with CPP, GCS score, and GOS score, with a value of 64.4% or below indicating a poor prognosis. Decreased CPP is an independent risk factor for decreased rSO₂.

Conclusion

DC and rSO₂ monitoring based on electrical bioimpedance and near-infrared spectroscopy not only reflect the degree of brain edema and oxygenation, but also reflect the severity of the disease and predict the prognosis of the patients. This approach offers a real-time, bedside, and accurate method for assessing brain function and detecting postoperative cerebral edema and poor prognosis.

Glasgow coma scale compared to other trauma scores in discriminating in-hospital mortality of traumatic brain injury patients admitted to urban Indian hospitals: A multicentre prospective cohort study

BACKGROUND

Glasgow Coma Scale (GCS) is one of the most commonly used trauma scores and is a good predictor of outcome in traumatic brain injury (TBI) patients. There are other more complex scores with additional physiological parameters. Whether they discriminate better than GCS in predicting mortality in TBI patients is debatable. The aim of this study was to compare the discrimination of GCS with that of MGAP, GAP, RTS and KTS for 24-hour and 30-day in-hospital mortality in adult TBI patients, in a resource limited LMIC setting.

METHOD

We analysed data from the multicentre, observational trauma cohort Towards Improved Trauma Care Outcome (TITCO) in India. We included all patients 18 years or older, admitted from the emergency department with TBI. The Area Under the Receiver Operating Characteristic (AUROC) curve was used to quantify and compare the discrimination of all scores: GCS; Revised Trauma Score (RTS); mechanism, GCS, age, systolic blood pressure (MGAP); GCS, age, systolic blood pressure (GAP) and Kampala Trauma Score (KTS) in the prediction of 24-hour and 30-day in-hospital mortality.

RESULTS

A total of 3306 TBI patients were included in this study. The majority were within the GCS range 3-8. The commonest mechanism of injury was road traffic injuries [1907(58.0%)]. In-hospital mortality was 27.2% (899). There was no significant difference in discrimination in 24-hour in-hospital mortality when comparing GCS with MGAP and GAP. While GCS performed better than KTS, RTS performed better than GCS. For 30-day in-hospital mortality, GCS discriminated significantly better compared with KTS, but there was no significant difference when compared to MGAP and RTS. GAP discriminated significantly better when compared with GCS.

CONCLUSION

This study shows that the discrimination of GCS is comparable to that of more complex trauma scores in predicting 24-hour and 30-day in-hospital mortality in adult TBI patients in a resource limited LMIC setting.

Comparison of Perioperative Characteristics and Clinical Outcomes of COVID-19 and non-COVID-19 Patients Undergoing Neurosurgery—A Retrospective Analysis

Background Patients with coronavirus disease 2019 (COVID-19) presenting for neurosurgery are not rare. Considering the lack of literature informing the outcomes in this subset, present study was conducted to compare perioperative management and postoperative outcomes between COVID-19 and non-COVID-19 neurosurgical patients.

Methods After ethics committee approval, data of all patients with COVID-19 along with an equal number of age and diagnosis matched non-COVID-19 patients undergoing neurosurgery between April 2020 and January 2021 was analyzed retrospectively. Predictors of poor outcome were identified using multivariate logistic regression analysis.

Results During the study period, 50 COVID-19 patients (28 laboratory confirmed (group-C) and 22 clinicoradiological diagnosed [group-CR]) underwent neurosurgery and were compared with 50 matched non-COVID-19 patients. Preoperatively, clinicoradiological diagnosed COVID-19 patients had higher American Society of Anesthesiologists (ASA) grade (p = 0.01), lower Glasgow Coma Scale (GCS) score (p < 0.001), and more pulmonary involvement (p = 0.004). The duration of intensive care unit stay was significantly longer in laboratory confirmed patients (p = 0.03). Poor clinical outcome (in-hospital mortality or discharge motor-GCS ≤ 5) did not differ significantly between the groups (p = 0.28). On univariate analysis, younger age, higher ASA grade, lower preoperative GCS, and motor-GCS, higher intraoperative blood and fluid administration and traumatic brain injury diagnosis were associated with poor outcome. On multivariable logistic regression. only lower preoperative motor-GCS remained the predictor of poor outcome.

Conclusions The concomitant presence of COVID-19 infection did not translate into poor outcome in patients undergoing neurosurgery. Preoperative motor-GCS predicted neurological outcome in both COVID-19 and non-COVID-19 neurosurgical patients.

State of the Art of Machine Learning-Enabled Clinical Decision Support in Intensive Care Units: Literature Review

Background

Modern clinical care in intensive care units is full of rich data, and machine learning has great potential to support clinical decision-making. The development of intelligent machine learning–based clinical decision support systems is facing great opportunities and challenges. Clinical decision support systems may directly help clinicians accurately diagnose, predict outcomes, identify risk events, or decide treatments at the point of care.

Objective

We aimed to review the research and application of machine learning–enabled clinical decision support studies in intensive care units to help clinicians, researchers, developers, and policy makers better understand the advantages and limitations of machine learning–supported diagnosis, outcome prediction, risk event identification, and intensive care unit point-of-care recommendations.

Methods

We searched papers published in the PubMed database between January 1980 and October 2020. We defined selection criteria to identify papers that focused on machine learning–enabled clinical decision support studies in intensive care units and reviewed the following aspects: research topics, study cohorts, machine learning models, analysis variables, and evaluation metrics.

Results

A total of 643 papers were collected, and using our selection criteria, 97 studies were found. Studies were categorized into 4 topics—monitoring, detection, and diagnosis (13/97, 13.4%), early identification of clinical events (32/97, 33.0%), outcome prediction and prognosis assessment (46/97, 47.6%), and treatment decision (6/97, 6.2%). Of the 97 papers, 82 (84.5%) studies used data from adult patients, 9 (9.3%) studies used data from pediatric patients, and 6 (6.2%) studies used data from neonates. We found that 65 (67.0%) studies used data from a single center, and 32 (33.0%) studies used a multicenter data set; 88 (90.7%) studies used supervised learning, 3 (3.1%) studies used unsupervised learning, and 6 (6.2%) studies used reinforcement learning. Clinical variable categories, starting with the most frequently used, were demographic (n=74), laboratory values (n=59), vital signs (n=55), scores (n=48), ventilation parameters (n=43), comorbidities (n=27), medications (n=18), outcome (n=14), fluid balance (n=13), nonmedicine therapy (n=10), symptoms (n=7), and medical history (n=4). The most frequently adopted evaluation metrics for clinical data modeling studies included area under the receiver operating characteristic curve (n=61), sensitivity (n=51), specificity (n=41), accuracy (n=29), and positive predictive value (n=23).

Conclusions

Early identification of clinical and outcome prediction and prognosis assessment contributed to approximately 80% of studies included in this review. Using new algorithms to solve intensive care unit clinical problems by developing reinforcement learning, active learning, and time-series analysis methods for clinical decision support will be greater development prospects in the future.

Estimated incidence and case fatality rate of traumatic brain injury among children (0-18 years) in Sub-Saharan Africa. A systematic review and meta-analysis

INTRODUCTION

Studies from Sub-Saharan Africa (SSA) countries have reported on the incidence and case fatality rate of children with Traumatic Brain Injury (TBI). However, there is lack of a general epidemiologic description of the phenomenon in this sub-region underpinning the need for an accurate and reliable estimate of incidence and outcome of children (0-18 years) with TBI. This study therefore, extensively reviewed data to reliably estimate incidence, case fatality rate of children with TBI and its mechanism of injury in SSA.

METHODS

Electronic databases were systematically searched in English via Medline (PubMed), Google Scholar, and Africa Journal Online (AJOL). Two independent authors performed an initial screening of studies based on the details found in their titles and abstracts. Studies were assessed for quality/risk of bias using the modified Newcastle-Ottawa Scale (NOS). The pooled case fatality rate and incidence were estimated using DerSimonian and Laird random-effects model (REM). A sub-group and sensitivity analyses were performed. Publication bias was checked by the funnel plot and Egger's test. Furthermore, trim and fill analysis was used to adjust for publication bias using Duval and Tweedie's method.

RESULTS

Thirteen (13) hospital-based articles involving a total of 40685 participants met the inclusion criteria. The pooled case fatality rate for all the included studies in SSA was 8.0%; [95% CI: 3.0%-13.0%], and the approximate case fatality rate was adjusted to 8.2%, [95% CI:3.4%-13.0%], after the trim-and-fill analysis was used to correct for publication bias. A sub-group analysis of sub-region revealed that case fatality rate was 8% [95% CI: 2.0%-13.0%] in East Africa, 1.0% [95% CI: 0.1% -3.0%] in Southern Africa and 18.0% [95% CI: 6.0%-29.0%] in west Africa. The pooled incidence proportion of TBI was 18% [95% CI: 2.0%-33.0%]. The current review showed that Road Traffic Accident (RTA) was the predominant cause of children's TBI in SSA. It ranged from 19.1% in South Africa to 79.1% in Togo.

CONCLUSION

TBI affects 18% of children aged 0 to 18 years, with almost one-tenth dying in SSA. The most common causes of TBI among this population in SSA were RTA and falls. TBI incidence and case fatality rate of people aged 0-18 years could be significantly reduced if novel policies focusing on reducing RTA and falls are introduced and implemented in SSA.

Clinical Characteristics and Outcomes of Critically Ill Neurological Patients with COVID-19 Infection in Neuro-intensive Care Unit: A Retrospective Study

Background

There are insufficient data about clinical outcomes in critically ill neurological patients with concomitant coronavirus disease (COVID-19). This study describes the clinical characteristics, predictors of mortality, and clinical outcomes in COVID-19-positive neurological patients managed in a dedicated COVID-19 neurointensive care unit (CNICU).

Methods

This single-center, retrospective cohort study was conducted in critically ill neurological and neurosurgical patients with concomitant COVID-19 infection admitted to the CNICU at the National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, from July to November 2020. Patients’ demographic, clinical, laboratory, imaging, treatment, and outcome data were retrieved from the manual and electronic medical records. Predictors of mortality and neurological outcome were identified using logistic regression.

Results

During the study period, 50 COVID-19-positive neurological patients were admitted to the CNICU. Six patients were excluded from the analysis as they were managed in the CNICU for <24 hours. A poor outcome, defined as death or motor Glasgow Coma Scale <5 at hospital discharge, was observed in 34 of 44 patients (77.27%) with inhospital mortality in 26 of 44 patients (59%). Worst modified sequential organ failure assessment (MSOFA) score, lactate dehydrogenase maximum levels (LDH_max), and lymphocyte count were predictors of inhospital mortality with an odds ratio (OR) of 1.88, 1.01, and 0.87, respectively, whereas worst MSOFA and LDH_max levels were predictors for poor neurological outcome with OR of 1.99 and 1.01, respectively.

Conclusions

Mortality is high in neurological patients with concomitant COVID-19 infection. Elevated inflammatory markers of COVID-19 suggest the role of systemic inflammation on clinical outcomes. Predictors of mortality and poor outcome were higher MSOFA score and elevated LDH levels. Additionally, lymphopenia was associated with mortality.

How to cite this article

Surve RM, Mishra RK, Malla SR, Kamath S, Chakrabarti DR, Kulanthaivelu K, et al. Clinical Characteristics and Outcomes of Critically Ill Neurological Patients with COVID-19 Infection in Neuro-intensive Care Unit: A Retrospective Study. Indian J Crit Care Med 2021;25(10):1126–1132.

The prediction value of Glasgow coma scale-pupils score in neurocritical patients: a retrospective study

BACKGROUND

External validation is necessary before  its clinical recommendation in new setting. The aim is to externally validate Glasgow Coma Scale-pupils score (GCS-P) in neurocritical patients and to compare its performances with Glasgow Coma Scale (GCS) and its derivatives.

METHODS

GCS-P at admission was calculated for individual based on the model developed by Brennan et al. Area under the receiver operating characteristic curves (AUCs), Nagelkerke's R2 and Brier scores were used to assess external validity of GCS-P to predict mortality in neurocritical patients and to compare predictive performance with GCS and its derivatives.

SUBJECTS

4372 neurocritical patients from intensive care units of Beth Israel Deaconess Medical Center, United States between 2001 and 2012.

RESULTS

GCS-P showed good discrimination (AUC 0.847 for in-hospital mortality and 0.774 for ninety-day mortality), modest calibration (Nagelkerke's R2 33.1% for in-hospital mortality and 23.3% for ninety-day mortality). Predictive performances of GCS and its derivatives was inferior to GCS-P.

CONCLUSIONS

GCP-P discriminated well in between death in neurocritical patients. GCP-P improved predictive performance for short-term mortality over GCS and its derivatives in neurocritical patients. It would be a simple, early and reasonable daily routine option for prognosis assessment in neurocritical setting.

Longer Time Before Acute Rehabilitation Therapy Worsens Disability After Intracerebral Hemorrhage

OBJECTIVE

Assess the association of time to initiation of acute rehabilitation therapy with disability after intracerebral hemorrhage (ICH) and identify predictors of time to initiation of rehabilitation therapy.

DESIGN

Retrospective data analysis of prospectively collected data from an ongoing observational cohort study.

SETTING

Large comprehensive stroke center in a metropolitan area.

PARTICIPANTS

Adults with ICH consecutively admitted (n=203).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Disability was assessed with the modified Rankin Scale (mRS), with poor outcome defined as mRS 4-6 (dependence or worse). Time to initiation of acute rehabilitation therapy was defined as the number of days between hospital admission and the first consult by any rehabilitation therapy specialist (eg, physical therapy, occupational therapy, speech therapy).

RESULTS

The median number of days from hospital admission to initiation of acute rehabilitation therapy was 3 (range=2-7). Multivariable logistic regression models indicated that each additional day between admission and initiation of acute rehabilitation therapy was associated with increased odds of poor outcome at 30 days (adjusted odds ratio [OR]=1.151; 95% confidence interval [CI]=1.044-1.268; P=.005) and at 90 days (adjusted OR=1.107; 95% CI=1.003-1.222; P=.044) for patients with ICH. A multivariable linear regression model used to identify the predictors of time to initiation of rehabilitation therapy identified heavy drinking (>5 drinks per day), premorbid mRS<4, presence of pulmonary embolism, and longer length of stay in the intensive care unit as independent predictors of later initiation of acute rehabilitation therapy.

CONCLUSIONS

Longer time to initiation of acute rehabilitation therapy after ICH may have persistent effects on poststroke disability. Delays in acute rehabilitation therapy consults should be minimized and may improve outcomes after ICH.

Using components of the Glasgow coma scale and Rotterdam CT scores for mortality risk stratification in adult patients with traumatic brain injury: A preliminary study

OBJECTIVE

The Glasgow Coma Scale (GCS) and Rotterdam Computed Tomography Score (RCTS) are widely used to predict outcomes after traumatic brain injury (TBI). The objective of this study was to determine whether the GCS and RCTS components can be used to predict outcomes in patients with traumatic intracranial hemorrhage (IH) after TBI.

PATIENTS AND METHODS

Between May 2009 and July 2017, 773 patients with IH after TBI were retrospectively reviewed. Data on initial GCS, RCTS according to initial brain CT, and status at hospital discharge and last follow-up were collected. Logistic regression analysis was performed to evaluate the relationship between GCS and RCTS components with outcomes after TBI.

RESULTS

Among the 773 patients, the overall in-hospital mortality rate was 14.0%. Variables independently associated with outcomes were the verbal (V-GCS) and motor components of GCS (M-GCS), epidural mass lesion (E-RCTS) and intraventricular or subarachnoid hemorrhage components of RCTS (H-RCTS) (p < 0.0001). The new TBI score was obtained with the following calculation: [V-GCS + M-GCS] - [E-RCTS + H-RCTS].

CONCLUSION

The new TBI score includes both clinical status and radiologic findings from patients with IH after TBI. The new TBI score is a useful tool for assessing TBI patients with IH in that it combines the GCS and RCTS components that increases area under the curve for predicting in-hospital mortality and unfavorable outcomes and eliminates the paradoxical relationship with outcomes which was observed in GCS score. It allows a practical method to stratify the risk of outcomes after TBI.

Modified Glasgow Coma Scale Using Serum Factors as a Prognostic Model in Traumatic Brain Injury

BACKGROUND

Traumatic brain injury (TBI) is a major cause of death and disability. This study evaluated a possible relationship between serum factors at admission and the outcome of TBI. We propose a statistically validated scale for patients with TBI that combines serum factors and the Glasgow Coma Scale (GCS).

METHODS

Between May 2011 and July 2016, 219 patients underwent decompressive craniectomy for TBI. We assessed laboratory data on admission, and correlations with GSC and Glasgow Outcome Scale were investigated. The modified GCS was developed from a multivariable logistic regression model, which was validated with the backward stepwise method.

RESULTS

Of 219 patients with TBI enrolled in our study, 175 were men (79.9%) and 44 were women (20.1%) with a mean age of 49.1 ± 11.5 years. Initial serum values of hemoglobin, platelets, prothrombin time, and lactate dehydrogenase were associated with in-hospital mortality. The factor score was derived by adding the following points: hemoglobin (≥13.0 g/dL = 0, <13.0 g/dL = 1), platelets (≥150 × 10³/mm³ = 0, <150 × 10³/mm³ = 1), prothrombin time (<13.2 seconds = 0, ≥13.2 seconds = 1), and lactate dehydrogenase (<271 U/L = 0, ≥271 U/L = 1). The modified GCS score (GCS score [range, 6-15] - FS [range, 0-4]) was calculated.

CONCLUSIONS

The modified GCS score using serum factors extended the information provided about patient outcomes to be comparable to more complex methods. The modified GCS score may be useful to predict in-hospital mortality in patients with TBI.

ACUTE PHYSIOLOGY AND CHRONIC HEALTH EVALUATION (APACHE) II SCORE - THE CLINICAL PREDICTOR IN NEUROSURGICAL INTENSIVE CARE UNIT

The APACHE II scoring system is approved for its benchmarking and mortality predictions, but there are only a few articles published to demonstrate it in neurosurgical patients. Therefore, this study was performed to acknowledge this score and its predictive performance to hospital mortality in a tertiary referral neurosurgical intensive care unit (ICU). All patients admitted to the Neurosurgical ICU from February 1 to July 31, 2011 were recruited. The parameters indicated in APACHE II score were collected. The adjusted predicted risk of death was calculated and compared with the death rate observed. Descriptive statistics including the receiver operating characteristic curve (ROC) was performed. The results showed that 276 patients were admitted during the mentioned period. The APACHE II score was 16.56 (95% CI, 15.84-17.29) and 19.08 (95% CI, 15.40-22.76) in survivors and non-survivors, while the adjusted predicted death rates were 13.39% (95% CI, 11.83-14.95) and 17.49% (95% CI, 9.81-25.17), respectively. The observed mortality was only 4.35%. The area under the ROC of APACHE II score to the hospital mortality was 0.62 (95% CI, 0.44-0.79). In conclusion, not only the APACHE II score in neurosurgical patients indicated low severity, but its performance to predict hospital mortality was also inferior. Additional studies of predicting mortality among these critical patients should be undertaken.

The Effectiveness of Scoring Systems in the Prediction of Diagnosis-Based Mortality

Scoring systems are used for mortality and morbidity rating in intensive care conditions, prognosis prediction, standardization of scientific data and the monitoring of clinical quality. The aim of this study was to retrospectively analyze the efficacy of APACHE II (Acute Physiology and Chronic Health Evaluation), APACHE IV and SAPS (Simplified Acute Physiology Score) III prognostic scorings in the prediction of mortality and disease severity of patients admitted to the Anesthesia and Reanimation Clinic Intensive Care Unit (ICU) in Bakırköy Dr. Sadi Konuk Training and Research Hospital according to general and specific diagnoses. A total of 1896 patient files were included in the study. With the exception of single system or head trauma patient groups, a statistically significant difference was found in the mortality prediction rates in all other diagnosis groups (P < 0.05). The discrimination calculated with AUROC fields was sufficient in all groups, and calibration was evaluated as good except for the neurological and neurosurgical patient group. In respect of standard mortality prediction, APACHE II and IV were good in cases of sepsis, and SAPS III made almost exact predictions for cardiovascular diseases, APACHE II for neurological diseases, and APACHE IV for gastrointestinal system diseases. From the results of this study, it was seen that different scoring systems vary in predictions according to the diagnoses, therefore, it can be recommended that the diagnosis should be taken into account more when applying scoring systems.

Modified Revised Trauma-Marshall score as a proposed tool in predicting the outcome of moderate and severe traumatic brain injury

Background

Traumatic brain injury (TBI) is a common healthcare problem related to disability. An easy-to-use trauma scoring system informs physicians about the severity of trauma and helps to decide the course of management. The purpose of this study is to use the combination of both physiological and anatomical assessment tools that predict the outcome and develop a new modified prognostic scoring system in TBIs.

Patients and methods

A total of 181 subjects admitted to the emergency department (ED) of Sanglah General Hospital were documented for both Marshall CT scan classification score (MCTC) and Revised Trauma Score (RTS) upon admission. Glasgow Outcome Scale (GOS) was then documented at six months after brain injury. A new Modified Revised Trauma–Marshall score (m-RTS) was developed using statistical analytic methods.

Results

The total sample enrolled for this study was 181 patients. The mean RTS upon admission was 10.2±1.2. Of the 181 subjects, 110 (60.8%) were found to have favorable GOS (GOS score >3). Best Youden’s index results were obtained with any of the RTS of ≤10 with area under receiver operating characteristic (ROC) curve of 0.2542 and with risk ratio of 2.9 (95% CI=1.98−4.28; P=0.001); and Marshall score ≤2 with area under ROC curve of 0.2249 with risk ratio of 3.9 (95% CI=2.52−5.89; P=0.001). The RTS–Marshall combination has higher sensitivity with risk ratio of 4.5 (CI 95%=2.55−8.0; P=0.001) for screening tools of unfavorable outcome. The Pearson’s correlation between RTS and Marshall classification is 0.464 (P<0.001).

Conclusion

Combination of physiological and anatomical score improves the prognostic of outcome in moderate and severe TBI patients, formulated in this accurate, simple, applicable and reliable m-RTS prognostic score model.

The use of SAPS 3, SOFA, and Glasgow Coma Scale to predict mortality in patients with subarachnoid hemorrhage: A retrospective cohort study

Guidelines for patients with subarachnoid hemorrhage (SAH) management and several grading systems or prognostic indices have been used not only to improve the quality of care but to predict also the outcome of these patients. Among them, the gold standards Fisher radiological grading scale, Hunt-Hess and the World Federation of Neurological Surgeons (WFNS) are the most employed. The objective of this study is to compare the predictive values of simplified acute physiology score (SAPS) 3, sequential organ failure assessment (SOFA), and Glasgow Coma Scale (GCS) in the outcome of patients with aneurysmal SAH.Fifty-one SAH patients (33% males and 67% females; mean age of 54.1 ± 10.3 years) admitted to the intensive care units (ICU) in the post-operative phase were retrospectively studied. The patients were divided into survivors (n=37) and nonsurvivors (n = 14). SAPS 3, Fischer scale, WFNS, SOFA, and GCS were recorded on ICU admission (day 1 - D1), and 72-hours (day 3 - D3) SOFA, and GCS. The capability of each index SAPS 3, SOFA, and GCS (D1 and D3) to predict mortality was analyzed by receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) and the respective confidence interval (CI) were used to measure the index accuracy. The level of significance was set at P < .05.The mean SAPS 3, SOFA, and GCS on D1 were 13.5 ± 12.7, 3.1 ± 2.4, and 13.7 ± 2.8 for survivors and 32.5 ± 28.0, 5.6 ± 4.9, and 13.5 ± 1.9 for nonsurvivors, respectively. The AUC and 95% CI for SAPS 3, SOFA, and GCS on D1 were 0.735 (0.592-0.848), 0.623 (0.476-0.754), 0.565 (0.419-0.703), respectively. The AUC and 95% CI for SOFA and GCS on D3 were 0.768 (0.629-0.875) and 0.708 (0.563-0.826), respectively. The overall mortality was 37.8%.Even though SAPS 3 and Fischer scale predicted mortality better on admission (D1), both indices SOFA and GCS performed similarly to predict outcome in SAH patients on D3.

A novel mortality prediction model for the current population in an adult intensive care unit

BACKGROUND

The accurate and reliable mortality prediction is very useful, in critical care medicine. There are various new variables proposed in the literature that could potentially increase the predictive ability for death in ICU of the new predictive scoring model.

OBJECTIVE

To develop and validate a new intensive care unit (ICU) mortality prediction model, using data that are routinely collected during the first 24 h of ICU admission, and compare its performance to the most widely used conventional scoring systems.

METHODS

Prospective observational study in a medical/surgical, multidisciplinary ICU, using multivariate logistic regression modeling. The new model was developed using data from a medical record review of 400 adult intensive care unit patients and was validated on a separate sample of 36 patients, to accurately predict mortality in ICU.

RESULTS

The new model is simple, flexible and shows improved performance (ROC AUC = 0.85, SMR = 1.25), compared to the conventional scoring models (APACHE II: AUC = 0.76, SMR = 2.50, SAPS III: AUC = 0.76, SMR = 1.50), as well as higher predictive capability regarding ICU mortality (predicted mortality: 41.63 ± 31.61, observed mortality: 41.67%).

CONCLUSION

The newly developed model is a quite simple risk-adjusted outcome prediction tool based on 12 routinely collected demographic and clinical variables obtained from the medical record data. It appears to be a reliable predictor of ICU mortality and is proposed for further investigation aiming at its evaluation, validation and applicability to other ICUs.

Preoperative serum lactate cannot predict in-hospital mortality after decompressive craniectomy in traumatic brain injury

PURPOSE

Despite the utility of serum lactate for predicting clinical courses, little information is available on the topic after decompressive craniectomy. This study was conducted to determine the ability of perioperative serum lactate levels to predict in-hospital mortality in traumatic brain-injury patients who received emergency or urgent decompressive craniectomy.

METHODS

The medical records of 586 consecutive patients who underwent emergency or urgent decompressive craniectomy due to traumatic brain injuries from January 2007 to December 2014 were retrospectively analyzed. Pre- and intraoperative serum lactate levels and base deficits were obtained from arterial blood gas analysis results.

RESULTS

The overall mortality rate after decompressive craniectomy was 26.1 %. Mean preoperative serum lactate was significantly higher in the non-survivors (P = 0.034) than the survivors but had no significance for predicting in-hospital mortality in the multivariate regression analysis (P = 0.386). Rather, preoperative Glasgow Coma Score was a significant predictor for in-hospital mortality (hazard ratio 0.796, 95 % confidence interval 0.755-0.836, P < 0.001).

CONCLUSION

Preoperative lactate level is not an independent predictor of in-hospital mortality after decompressive craniectomy in traumatic brain-injury patients.

The ability of two scoring systems to predict in-hospital mortality of patients with moderate and severe traumatic brain injuries in a Moroccan intensive care unit

Aim of Study:

We aim to assess and to compare the predicting power for in-hospital mortality (IHM) of the Acute Physiology and Chronic Health Evaluation-II (APACHE-II) and the Simplified Acute Physiology Score-II (SAPS-II) for traumatic brain injury (TBI).

Patients and Methods:

This retrospective cohort study was conducted during a period of 2 years and 9 months in a Moroccan intensive care unit. Data were collected during the first 24 h of each admission. The clinical and laboratory parameters were analyzed and used as per each scoring system to calculate the scores. Univariate and multivariate analyses through regression logistic models were performed, to predict IHM after moderate and severe TBIs. Areas under the receiver operating characteristic curves (AUROC), specificities and sensitivities were determined and also compared.

Results:

A total of 225 patients were enrolled. The observed IHM was 51.5%. The univariate analysis showed that the initial Glasgow coma scale (GCS) was lower in nonsurviving patients (mean GCS = 6) than the survivors (mean GCS = 9) with a statistically significant difference (P = 0.0024). The APACHE-II and the SAPS-II of the nonsurviving patients were higher than those of the survivors (respectively 20.4 ± 6.8 and 31.2 ± 13.6 for nonsurvivors vs. 15.7 ± 5.4 and 22.7 ± 10.3 for survivors) with a statistically significant difference (P = 0.0032 for APACHE-II and P = 0.0045 for SAPS-II). Multivariate analysis: APACHE-II was superior for predicting IHM (AUROC = 0.92).

Conclusion:

The APACHE-II is an interesting tool to predict IHM of head injury patients. This is particularly relevant in Morocco, where TBI is a greater public health problem than in many other countries.

Descriptive characteristics and rehabilitation outcomes in active duty military personnel and veterans with disorders of consciousness with combat- and noncombat-related brain injury

OBJECTIVE

To report the injury and demographic characteristics, medical course, and rehabilitation outcome for a consecutive series of veterans and active duty military personnel with combat- and noncombat-related brain injury and disorder of consciousness (DOC) at the time of rehabilitation admission.

DESIGN

Retrospective study.

SETTING

Rehabilitation center.

PARTICIPANTS

From January 2004 to October 2009, persons (N=1654) were admitted to the Polytrauma Rehabilitation System of Care. This study focused on the N=122 persons admitted with a DOC. Participants with a DOC were primarily men (96%), on active duty (82%), ≥12 years of education, and a median age of 25. Brain injury etiologies included mixed blast trauma (24%), penetrating (8%), other trauma (56%), and nontrauma (13%). Median initial Glasgow Coma Scale score was 3, and rehabilitation admission Glasgow Coma Scale score was 8. Individuals were admitted for acute neurorehabilitation approximately 51 days postinjury with a median rehabilitation length of stay of 132 days.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Recovery of consciousness and the FIM instrument.

RESULTS

Most participants emerged to regain consciousness during neurorehabilitation (64%). Average gains ± SD on the FIM cognitive and motor subscales were 19 ± 25 and 7 ± 8, respectively. Common medical complications included spasticity (70%), dysautonomia (34%), seizure occurrence (30%), and intracranial infection (22%). Differential outcomes were observed across etiologies, particularly for those with blast-related brain injury etiology.

CONCLUSIONS

Despite complex comorbidities, optimistic outcomes were observed. Individuals with severe head injury because of blast-related etiologies have different outcomes and comorbidities observed. Health-services research with a focus on prevention of comorbidities is needed to inform optimal models of care, particularly for combat injured soldiers with blast-related injuries.

Effect of the modified Glasgow Coma Scale score criteria for mild traumatic brain injury on mortality prediction: comparing classic and modified Glasgow Coma Scale score model scores of 13

BACKGROUND

The Glasgow Coma Scale (GCS) classifies traumatic brain injuries (TBIs) as mild (14-15), moderate (9-13), or severe (3-8). The Advanced Trauma Life Support modified this classification so that a GCS score of 13 is categorized as mild TBI. We investigated the effect of this modification on mortality prediction, comparing patients with a GCS score of 13 classified as moderate TBI (classic model) to patients with GCS score of 13 classified as mild TBI (modified model).

METHODS

We selected adult TBI patients from the Pennsylvania Outcome Study database. Logistic regressions adjusting for age, sex, cause, severity, trauma center level, comorbidities, and isolated TBI were performed. A second evaluation included the time trend of mortality. A third evaluation also included hypothermia, hypotension, mechanical ventilation, screening for drugs, and severity of TBI. Discrimination of the models was evaluated using the area under receiver operating characteristic curve (AUC). Calibration was evaluated using the Hosmer-Lemershow goodness of fit test.

RESULTS

In the first evaluation, the AUCs were 0.922 (95% CI, 0.917-0.926) and 0.908 (95% CI, 0.903-0.912) for classic and modified models, respectively. Both models showed poor calibration (p < 0.001). In the third evaluation, the AUCs were 0.946 (95% CI, 0.943-0.949) and 0.938 (95% CI, 0.934-0.940) for the classic and modified models, respectively, with improvements in calibration (p = 0.30 and p = 0.02 for the classic and modified models, respectively).

CONCLUSION

The lack of overlap between receiver operating characteristic curves of both models reveals a statistically significant difference in their ability to predict mortality. The classic model demonstrated better goodness of fit than the modified model. A GCS score of 13 classified as moderate TBI in a multivariate logistic regression model performed better than a GCS score of 13 classified as mild.