Internationally comparable diagnosis-specific survival probabilities for calculation of the ICD-10-based Injury Severity Score

An update of the severe trauma scoring system using the Korean National Emergency Department Information System (NEDIS) database

BACKGROUND

Various scoring systems are utilized to assess severe trauma patients, with one of the most commonly used tools being the International Classification of Diseases Injury Severity Score (ICISS) criteria derived from the Survival Risk Ratio (SRR) calculated using diagnostic codes. This study aimed to redefine the severe trauma scoring system in Korea based on the SRR for diagnostic codes, and subsequently evaluate its performance in predicting survival outcomes for trauma patients.

METHODS

This study included trauma patients who visited Level 1 and 2 emergency departments (EDs) between January 2016 and December 2019, utilizing the Korean National Emergency Department Information System (NEDIS) database. The primary outcome of this study was in-hospital mortality. The new SRR-2020 value was calculated for each of the 865 trauma diagnosis codes (Korean Standard Classification of Diseases [KCD-7] codes, 4-digit format), and the patient-specific ICISS-2020 value was derived by multiplying the corresponding SRR-2020 value based on patient diagnosis. We compared the predictive performance for in-hospital mortality between severe trauma patients with an ICISS <0.9 based on the newly developed ICISS-2020 version and those defined by the previously used ICISS-2015 version.

RESULTS

A total of 3,841,122 patients were enrolled, with an in-hospital mortality rate of 0.5 %. Severe trauma patients with ICISS-2020 < 0.9 accounted for 5.3 % (204,897 cases) that was lower than ICISS-2015 < 0.9 accounting for 15.3 % (587,801 cases). Among the 20,619 in-hospital mortality cases, 81.4 % had ICISS-2020 < 0.9, and 88.6 % had ICISS-2015 < 0.9. When comparing predictive performance for in-hospital mortality between the two ICISS versions, ICISS-2020 showed higher accuracy (0.95), specificity (0.95), positive predictive value (PPV) (0.08), positive likelihood ratio (LR+) (16.53), and area under the receiver operating characteristic curve (AUROC) (0.96) than ICISS-2015 for accuracy (0.85), sensitivity (0.88), specificity (0.85), PPV (0.03), LR+ (5.94), and AUROC (0.94). However, regarding sensitivity, ICISS-2020 < 0.9 showed a lower value of 0.81 compared to ICISS-2015 < 0.9, which was 0.88. The negative predictive value (NPV) was 1.00 for both versions.

CONCLUSIONS

The newly developed ICISS-2020, utilizing a nationwide emergency patient database, demonstrated relatively good performance (accuracy, specificity, PPV, LR+, and AUROC) in predicting survival outcomes for patients with trauma.

Development and validation of a multi-dimensional diagnosis-based comorbidity index that improves prediction of death in men with prostate cancer: Nationwide, population-based register study

Assessment of comorbidity is crucial for confounding adjustment and prediction of mortality in register-based studies, but the commonly used Charlson comorbidity index is not sufficiently predictive. We aimed to develop a multidimensional diagnosis-based comorbidity index (MDCI) that captures comorbidity better than the Charlson Comorbidity index. The index was developed based on 286,688 men free of prostate cancer randomly selected from the Swedish general population, and validated in 54,539 men without and 68,357 men with prostate cancer. All ICD-10 codes from inpatient and outpatient discharges during 10 years prior to the index date were used to define variables indicating frequency of code occurrence, recency, and total duration of related hospital admissions. Penalized Cox regression was used to predict 10-year all-cause mortality. The MDCI predicted risk of death better than the Charlson comorbidity index, with a c-index of 0.756 (95% confidence interval [CI] = 0.751, 0.762) vs 0.688 (95% CI = 0.683, 0.693) in the validation cohort of men without prostate cancer. Men in the lowest vs highest MDCI quartile had distinctively different survival in the validation cohort of men with prostate cancer, with an overall hazard ratio [HR] of 5.08 (95% CI = 4.90, 5.26). This was also consistent within strata of age and Charlson comorbidity index, e.g. HR = 5.90 (95% CI = 4.65, 7.50) in men younger than 60 years with CCI 0. These results indicate that comorbidity assessment in register-based studies can be improved by use of all ICD-10 codes and taking related frequency, recency, and duration of hospital admissions into account.

Gender versus sex in predicting outcomes of traumatic brain injury: a cohort study utilizing large administrative databases

Understanding the factors associated with elevated risks and adverse consequences of traumatic brain injury (TBI) is an integral part of developing preventive measures for TBI. Brain injury outcomes differ based on one's sex (biological characteristics) and gender (social characteristics reflecting norms and relationships), however, whether it is sex or gender that drives differences in early (30-day) mortality and discharge location post-TBI is not well understood. In the absence of a gender variable in existing data, we developed a method for "measuring gender" in 276,812 residents of Ontario, Canada who entered the emergency department and acute care hospitals with a TBI diagnostic code between April 1st, 2002, and March 31st, 2020. We applied logistic regression to analyse differences in diagnostic codes between the sexes and to derive a gender score that reflected social dimensions. We used the derived gender score along with a sex variable to demonstrate how it can be used to separate the relationship between sex, gender and TBI outcomes after severe TBI. Sex had a significant effect on early mortality after severe TBI with a rate ratio (95% confidence interval (CI)) of 1.54 (1.24-1.91). Gender had a more significant effect than sex on discharge location. A person expressing more "woman-like" characteristics had lower odds of being discharged to rehabilitation versus home with odds ratio (95% CI) of 0.54 (0.32-0.88). The method we propose offers an opportunity to measure a gender effect independently of sex on TBI outcomes.

The influence of initial spinal cord haematoma and cord compression on neurological grade improvement in acute traumatic spinal cord injury: A prospective observational study

STUDY DESIGN

Prospective observational cohort study linked with administrative data.

OBJECTIVES

Magnetic Resonance Imaging (MRI) is routinely performed after traumatic spinal cord injury (TSCI), facilitating early, accurate diagnosis to optimize clinical management. Prognosis from early MRI post-injury remains unclear, yet if available could guide early intervention. The aim of this study was to determine the association of spinal cord intramedullary haematoma and/or extent of cord compression evident on initial spine MRI with neurological grade change after TSCI.

METHODS

Individuals with acute TSCI ≥16 years of age; MRI review. Neurological gradings (American Spinal Injury Association Impairment Scale (AIS)) were compared with initial MRI findings. Various MRI parameters were evaluated for prediction of neurological improvement pre-discharge.

RESULTS

120 subjects; 79% male, mean (SD) age 51.0 (17.7) years. Motor vehicle crashes (42.5%) and falls (40.0%) were the most common injury mechanisms. Intramedullary spinal cord haematoma was identified by MRI in 40.0% of patients and was associated with more severe neurologic injury (58.3% initially AIS A). Generalised linear regression showed higher maximum spinal cord compression (MSCC) was associated with lower likelihood of neurological improvement from initial assessment to follow up prior to rehabilitation discharge. Combined thoracic level injury, intramedullary haematoma, and MSCC > 25% resulted in almost 90% probability of pre-discharge AIS (grade A) remaining unchanged from admission assessment.

CONCLUSIONS

MRI is a vital tool for evaluating the severity and extent of TSCI, assisting in appropriate management decision-making early in TSCI patient care. This study adds to the body of knowledge assisting clinicians in prognostication.

The effect of time of measurement on the discriminant ability for mortality in trauma of a pre-hospital shock index multiplied by age and divided by the Glasgow Coma Score: a registry study

BACKGROUND

The shock index (SI) and its derivatives have been shown to predict mortality in severely injured patients, both in pre-hospital and in-hospital settings. However, the impact of the time of measurement on the discriminative ability of the pre-hospital SI is unknown. The aim of this study was to evaluate whether the time of measurement influences the discriminative ability of the SI multiplied by age (SIA) and divided by the Glasgow Coma Score (SIA/G).

METHODS

Registry data were obtained from the national helicopter emergency medical services (HEMS) on trauma patients aged ≥ 18 years. The SI values were calculated based on the first measured vitals of the trauma patients by the HEMS unit. The discriminative ability of the SIA/G, with 30-day mortality as the endpoint, was evaluated according to different delay times (0 - 19, 20 - 39 and ≥ 40 min) from the initial incident. Sub-group analyses were performed for trauma patients without a traumatic brain injury (TBI), patients with an isolated TBI and patients with polytrauma, including a TBI.

RESULTS

In total, 3,497 patients were included in the study. The SIA/G was higher in non-survivors (median 7.8 [interquartile range 4.7-12.3] vs. 2.4 [1.7-3.6], P < 0.001). The overall area under the receiver operator characteristic curve (AUROC) for the SIA/G was 0.87 (95% CI: 0.85-0.89). The AUROC for the SIA/G was similar in the short (0.88, 95% CI: 0.85-0.91), intermediate (0.86, 95% CI: 0.84-0.89) and long (0.86, 95% CI: 0.82-0.89) measurement delay groups. The findings were similar in the three trauma sub-groups.

CONCLUSIONS

The discriminative ability of the SIA/G in predicting 30-day mortality was not significantly affected by the measurement time of the index in the pre-hospital setting. The SIA/G is a simple and reliable tool for assessing the risk of mortality among severely injured patients in the pre-hospital setting.

Predictive value of shock index variants on 30-day mortality of trauma patients in helicopter emergency medical services: a nationwide observational retrospective multicenter study

The original shock index (SI) has been further developed to increase its prognostic value. We aimed to evaluate the predictive value of different SI variants on 30-day mortality among severely injured trauma patients in pre-hospital critical care settings. Adult trauma patients in the national Helicopter Emergency Medical Services (HEMS) registry were evaluated based on the primary outcome of 30-day mortality. SI, SIA (SI multiplied by age), SI/G (SI divided by Glasgow Coma Scale (GCS)), SIA/G (SI multiplied by age and divided by GCS), and SS (SI divided by oxygen saturation) were calculated based on the first vital signs measured at the time of HEMS contact. The area under the receiver operating curve (AUROC) was calculated for each SI variant. In total 4108 patients were included in the study. The overall 30-day mortality was 13.5%. The SIA/G and SI/G had the highest predictive ability (AUROC 0.884 [95% CI 0.869-0.899] and 0.8000 [95% CI 0.7780-0.8239], respectively). The SIA/G yielded good predictive performance between 30-day survivors and non-survivors in the pre-hospital critical care setting.

Optimized diagnosis-based comorbidity measures for all-cause mortality prediction in a national population-based ICU population

BACKGROUND

We aimed to optimize prediction of long-term all-cause mortality of intensive care unit (ICU) patients, using quantitative register-based comorbidity information assessed from hospital discharge diagnoses prior to intensive care treatment.

MATERIAL AND METHODS

Adult ICU admissions during 2006 to 2012 in the Swedish intensive care register were followed for at least 4 years. The performance of quantitative comorbidity measures based on the 5-year history of number of hospital admissions, length of stay, and time since latest admission in 36 comorbidity categories was compared in time-to-event analyses with the Charlson comorbidity index (CCI) and the Simplified Acute Physiology Score (SAPS3).

RESULTS

During a 7-year period, there were 230,056 ICU admissions and 62,225 deaths among 188,965 unique individuals. The time interval from the most recent hospital stays and total length of stay within each comorbidity category optimized mortality prediction and provided clear separation of risk categories also within strata of age and CCI, with hazard ratios (HRs) comparing lowest to highest quartile ranging from 1.17 (95% CI: 0.52-2.64) to 6.41 (95% CI: 5.19-7.92). Risk separation was also observed within SAPS deciles with HR ranging from 1.07 (95% CI: 0.83-1.38) to 3.58 (95% CI: 2.12-6.03).

CONCLUSION

Baseline comorbidity measures that included the time interval from the most recent hospital stay in 36 different comorbidity categories substantially improved long-term mortality prediction after ICU admission compared to the Charlson index and the SAPS score. Trial registration ClinicalTrials.gov ID NCT04109001, date of registration 2019-09-26 retrospectively.

Injury-Related Pediatric Emergency Department Visits in the First Year of COVID-19

OBJECTIVES

To describe the epidemiology of pediatric injury-related visits to children's hospital emergency departments (EDs) in the United States during early and later periods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic.

METHODS

We conducted a cross-sectional study using the Pediatric Health Information System, an administrative database to identify injury-related ED visits at 41 United States children's hospitals during the SARS-CoV-2 pandemic period (March 15, 2020 to March 14, 2021) and a 3 year comparator period (March 15-March 14, 2017-2020). For these 2 periods, we compared patient characteristics, injury type and severity, primary discharge diagnoses, and disposition, stratified by early (March 15, 2020 to June 30, 2020), middle (July 1, 2020 to October 31, 2020), and late (November 1, 2020 to March 14, 2021) pandemic periods.

RESULTS

Overall, ED injury-related visits decreased by 26.6% during the first year of the SARS-CoV-2 pandemic, with the largest decline observed in minor injuries. ED injury-related visits resulting in serious-critical injuries increased across the pandemic (15.9% early, 4.9% middle, 20.6% late). Injury patterns with the sharpest relative declines included superficial injuries (41.7% early) and sprains/strains (62.4% early). Mechanisms of injury with the greatest relative increases included (1) firearms (22.9% early; 42.8% middle; 37% late), (2) pedal cyclists (60.4%; 24.9%; 32.2%), (3) other transportation (20.8%; 25.3%; 17.9%), and (4) suffocation/asphyxiation (21.4%; 20.2%; 28.4%) and injuries because of suicide intent (-16.2%, 19.9%, 21.8%).

CONCLUSIONS

Pediatric injury-related ED visits declined in general. However, there was a relative increase in injuries with the highest severity, which warrants further investigation.

Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes

Various assessment methods based on the International Classification of Diseases, Tenth Edition, Clinical Modification (ICD-10-CM), such as ICD-10-CM Injury Severity Score (ICISS), trauma mortality prediction model (TMPM-ICD10), and injury mortality prediction (IMP-ICDX), are purely anatomic trauma assessment, which need to be further improved. Traumatic injury mortality prediction (TRIMP-ICDX) is a comprehensive assessment method based on anatomic injuries and incorporating available information to determine whether it is superior to Trauma and Injury Severity Score (TRISS) and IMP-ICDX in predicting trauma outcomes. This retrospective cohort study was based on data from 704,287 trauma patients admitted to 710 trauma centers in the National Trauma Data Bank of the United States in 2016. The TRIMP-ICDX was established using anatomical injury, physiological reserves, and physiological response indicators. Its performance was compared with the IMP-ICDX and TRISS by examining the area under the receiver operating characteristic curve (AUC), calibration (Hosmer-Lemeshow goodness-of-fit test, HL), and the Akaike information criterion (AIC). The TRIMP-ICDX showed significantly better discrimination (AUCTRIMP-ICDX 0.968; 95% confidence interval (CI), 0.966-0.970, AUCTRISS 0.922; 95% CI, 0.918-0.925, and AUCIMP-ICDX 0.894; 95% CI, 0.890-0.899), better calibration (HLTRIMP-ICDX 5.6; 95% CI, 3.0-8.0, HLTRISS 72.7; 95% CI, 38.4-104.5, and HLIMP-ICDX 53.1; 95% CI, 26.6-77.8), and a lower AIC (AICTRIMP-ICDX 24,774, AICTRISS 30,753, and AICIMP-ICDX 32,780) compared with TRISS and IMP-ICDX. Similar results were found in statistical comparisons among different body regions. As a comprehensive evaluation method based on the ICD-10-CM lexicon TRIMP-ICDX is significantly better than IMP-ICDX and TRISS with respect to both discriminative power and calibration. The TRIMP-ICDX should become a research method for the comprehensive evaluation of trauma severity.

Injury severity and increased socioeconomic differences: A population-based cohort study

BACKGROUND

Several studies have documented an inverse gradient between socioeconomic status (SES) and injury mortality, but the evidence is less consistent for injury morbidity. The aim of this study was to investigate the association between SES and injury severity for acute hospitalizations in a nationwide population-based cohort.

METHODS

We conducted a registry-based cohort study of all individuals aged 25-64 years residing in Norway by 1st of January 2008. This cohort was followed from 2008 through 2014 using inpatient registrations for acute hospitalizations due to all-cause injuries. We derived two measures of severity: threat-to-life using the International Classification of Disease-based Injury Severity Score (ICISS), and threat of disability using long-term disability weights from the Injury-VIBES project. Robust Poisson regression models, with adjustment for age, sex, marital status, immigrant status, municipality population size and healthcare region of residence, were used to calculate incidence rate ratios (IRRs) by SES measured as an index of education, income, and occupation.

RESULTS

We identified 177,663 individuals (7% of the population) hospitalized with at least one acute injury in the observation period. Two percent (n = 4,186) had injuries categorized with high threat-to-life, while one quarter (n = 43,530) had injuries with high threat of disability. The overall adjusted IRR of hospitalization among people with low compared to high SES was 1.57 (95% CI 1.55, 1.60). Comparing low to high SES, injuries with low threat-to-life were associated with an IRR of 1.56 (95% CI 1.54, 1.59), while injuries with high threat-to-life had an IRR of 2.25 (95% CI 2.03, 2.51). Comparing low to high SES, injuries with low, medium, and high threat of disability were associated with IRRs of respectively, 1.15 (95% CI 1.11, 1.19), 1.70 (95% CI 1.66, 1.73) and 1.99 (95% CI 1.92, 2.07).

DISCUSSION

We observed an inverse gradient between SES and injury morbidity, with the steepest gradient for the most severe injuries. This suggests a need for targeted preventive measures to reduce the magnitude and burden of severe injuries for patients with low socioeconomic status.

Effect of time intervals in critical care provided by helicopter emergency medical services on 30-day survival after trauma

BACKGROUND

Trauma is the leading cause of death especially in children and young adults. Prehospital care following trauma emphasizes swift transport to a hospital following initial care. Previous studies have shown conflicting results regarding the effect of time on the survival following major trauma. In our study we investigated the effect of prehospital time-intervals on 30-day mortality on trauma patients that received prehospital critical care.

METHODS

We performed a retrospective study on all trauma patients encountered by helicopter emergency medical services in Finland from 2012 to 2018. Patients discharge diagnoses were classed into (1) trauma without traumatic brain injury, (2) isolated traumatic brain injury and (3) trauma with traumatic brain injury. Emergency medical services response time, helicopter emergency medical services response time, on-scene time and transport time were used as time-intervals and age, Glasgow coma scale, hypotension, need for prehospital airway intervention and ICD-10 based Injury Severity Score were used as variables in logistic regression analysis.

RESULTS

Mortality data was available for 4,803 trauma cases. The combined 30-day mortality was 12.1% (582/4,803). Patients with trauma without a traumatic brain injury had the lowest mortality, at 4.3% (111/2,605), whereas isolated traumatic brain injury had the highest, at 22.9% (435/1,903). Patients with both trauma and a traumatic brain injury had a mortality of 12.2% (36/295). Following adjustments, no association was observed between time intervals and 30-day mortality.

DISCUSSION

Our study revealed no significant association between different timespans and mortality following severe trauma in general. Trends in odds ratios can be interpreted to favor more expedited care, however, no statistical significance was observed. As trauma forms a heterogenous patient group, specific subgroups might require different approaches regarding the prehospital timeframes.

STUDY TYPE

prognostic/therapeutic/diagnostic test.

International classification of disease based injury severity score (ICISS): A data linkage study of hospital and death data in Victoria, Australia

BACKGROUND

Surveillance of severe injury incidence and prevalence using ICD-based injury severity scores (ICISS) requires valid, locally applicable diagnosis-specific survival probabilities (DSPs). This study aims to derive and validate ICISS in Victoria, Australia, and compare various ICISS methodologies in terms of accuracy and calculated severe injury prevalence.

METHODS

This study used injury admissions (ICD-10-AM coded) from the Victorian Admitted Episodes Database (VAED) linked with death data (Cause of Death - Unit Record Files: CODURF). Using design data (July 2008 - June 2014; n = 720,759), various ICISS scales were derived, based on (i) in-hospital and (ii) three-month mortality. These scales were applied to testing data (July 2014 - December 2016; n = 334,363). Logistic regression modelling was used to determine model discrimination and calibration.

RESULTS

In the design data, there were 6,337(0.9%) hospital deaths and 17,514(2.4%) three-months deaths; in the testing data, there were 2,700(0.8%) hospital deaths and 8,425(2.5%) three-month deaths. Newly developed ICISS scales had acceptable to outstanding discrimination, with Area Under the Curve ranging from 0.758 to 0.910. Age-specific ICISS scales were superior to general ICISS scales in model discrimination but inferior in model calibration. Calculated severe injury (ICISS ≤0.941) prevalence in the testing data ranged from 2% to 24%, depending on which mortality outcomes were used to calculate DRGs.

CONCLUSIONS

This study provides local, validated ICISS scores that can be used in Victoria. It is recommended that age group stratified ICISS based on the worst-injury method is used. From the comparison of various ICISS scores, reflecting the range of ICISS permutations that are currently in use, care should be taken to compare ICISS methodology before comparing severe injury prevalence per population, injury cause, and time trends.

The use of computed tomography in the management of injury in tertiary emergency departments in Western Australia: Evidence of overtesting?

BACKGROUND

This study investigated trends in computed tomography (CT) utilization across different triage categories of injury presentations to tertiary emergency departments (EDs) and associations with diagnostic yield measured by injury severity, hospitalization and length of stay (LOS), and mortality.

METHODS

A total of 411,155 injury-related ED presentations extracted from linked records from Western Australia from 2004 to 2015 were included in the retrospective study. The use of CT scanning and diagnostic yield measured by rate of diagnosis with severe injury, hospitalizations and LOS, and mortality were captured annually for injury-related ED presentations. Multivariable regression models were used to calculate the annual adjusted rate of CT scanning for injury presentations and hospitalizations across triage categories, diagnosis with severe injury, LOS, and mortality. The significance of changes observed was compared among patients with CT imaging relative to those without CT.

RESULTS

While the number of ED presentations with injury increased by 65% from 2004 to 2015, the use of CT scanning in these presentations increased by 176%. The largest increase in CT use was among ED presentations triaged as semi-/nonurgent (+256%). Injury presentations with CT, compared to those without, had a higher rate of diagnosis with moderate/severe injury and hospitalization but no difference in LOS and mortality. The probability/rate observed in the outcomes of interest had a greater decrease over time in those with CT scanning compared with those without CT scanning across triage categories.

CONCLUSIONS

The reduction in diagnostic yield in terms of injury severity and hospitalization found in our study might indicate a shift toward overtesting using CT in ED for injury or a higher use of CT to assist in the management of injuries. This helps health care policymakers consider whether the current increase in CT use meets the desired levels of quality and efficient care.

External validation of International Classification of Injury Severity Score to predict mortality in a Greek adult trauma population

INTRODUCTION

The International Classification of diseases- based Injury Severity Score (ICISS) obtained by empirically derived diagnosis-specific survival probabilities (DSPs) is the best-known risk-adjustment measure to predict mortality. Recently, a new set of pooled DSPs has been proposed by the International Collaborative Effort on Injury Statistics but it remains to be externally validated in other cohorts. The aim of this study was to externally validate the ICISS using international DSPs and compare its prognostic performance with local DSPs derived from Greek adult trauma population.

MATERIALS AND METHODS

This retrospective single-center cohort study enrolled adult trauma patients (≥ 16 years) hospitalized between January 2015 and December 2019 and temporally divided into derivation (n = 21,614) and validation cohorts (n = 14,889). Two different ICISS values were calculated for each patient using two different sets of DSPs: international (ICISSint) and local (ICISSgr). The primary outcome was in-hospital mortality. Models' prediction was performed using discrimination and calibration statistics.

RESULTS

ICISSint displayed good discrimination in derivation (AUC = 0.836 CI 95% 0.819-0.852) and validation cohort (AUC = 0.817 CI 95% 0.797-0.836). Calibration using visual analysis showed accurate prediction at patients with low mortality risk, especially below 30%. ICISSgr yielded better discrimination (AUC = 0.834 CI 95% 0.814-0.854 vs 0.817 CI 95% 0.797-0.836, p ˂ .05) and marginally improved overall accuracy (Brier score = 0.0216 vs 0.0223) compared with the ICISSint in the validation cohort. Incorporation of age and sex in both models enhanced further their performance as reflected by superior discrimination (p ˂ .05) and closer calibration curve to the identity line in the validation cohort.

CONCLUSION

This study supports the use of international DSPs for the ICISS to predict mortality in contemporary trauma patients and provides evidence regarding the potential benefit of applying local DSPs. Further research is warranted to confirm our findings and recommend the widespread use of ICISS as a valid measure that is easily obtained from administrative data based on ICD-10 codes.

Quantifying injury severity for traumatic brain injury with routinely collected health data

BACKGROUND

Routinely collected health data (RCHD) offers many opportunities for traumatic brain injury (TBI) research, in which injury severity is an important factor.

OBJECTIVE

The use of clinical injury severity indices in a context of RCHD is explored, as are alternative measures created for this specific purpose. To identify useful scales for full body injury severity and TBI severity this study focuses on their performance in predicting these currently used indices, while accounting for age and comorbidities.

DATA

This study utilized an extensive population-based RCHD dataset consisting of all patients with TBI admitted to any Belgian hospital in 2016.

METHODS

Full body injury severity is scored based on the (New) Injury Severity Score ((N)ISS) and the ICD-based Injury Severity Score (ICISS). For TBI specifically, the Abbreviated Injury Scale (AIS) Head, Loss of Consciousness and the ICD-based Injury Severity Score for TBI injuries (ICISS) were used in the analysis. These scales were used to predict three outcome variables strongly related to injury severity: in-hospital death, admission to intensive care and length of hospital stay. For the prediction logistic regressions of the different injury severity scales and TBI severity indices were used, and error rates and the area under the receiver operating curve were evaluated visually.

RESULTS

In general, the ICISS had the best predictive performance (error rate between 0.06 and 0.23; AUC between 0.82 [0.81;0.83] and 0.86 [0.85;0.86]). A clearly increasing error rate can be noticed with advancing age and accumulating comorbidity.

CONCLUSION

Both for full body injury severity and TBI severity, the ICISS tends to outperform other scales. It is therefore the preferred scale for use in research on TBI in the context of RCHD. In their current form, the severity scales are not suitable for use in older populations.

An Aggregated Comorbidity Measure Based on History of Filled Drug Prescriptions: Development and Evaluation in Two Separate Cohorts

BACKGROUND

The ability to account for comorbidity when estimating survival in a population diagnosed with cancer could be improved by using a drug comorbidity index based on filled drug prescriptions.

METHODS

We created a drug comorbidity index from age-stratified univariable associations between filled drug prescriptions and time to death in 326,450 control males randomly selected from the general population to men with prostate cancer. We also evaluated the index in 272,214 control females randomly selected from the general population to women with breast cancer.

RESULTS

The new drug comorbidity index predicted survival better than the Charlson Comorbidity Index (CCI) and a previously published prescription index during 11 years of follow-up. The concordance (C)-index for the new index was 0.73 in male and 0.76 in the female population, as compared with a C-index of 0.67 in men and 0.69 in women for the CCI. In men of age 75-84 years with CCI = 0, the median survival time was 7.1 years (95% confidence interval [CI] = 7.0, 7.3) in the highest index quartile. Comparing the highest to the lowest drug comorbidity index quartile resulted in a hazard ratio (HR) of 2.2 among men (95% CI = 2.1, 2.3) and 2.4 among women (95% CI = 2.3, 2.6).

CONCLUSIONS

A new drug comorbidity index based on filled drug prescriptions improved prediction of survival beyond age and the CCI alone. The index will allow a more accurate baseline estimation of expected survival for comparing treatment outcomes and evaluating treatment guidelines in populations of people with cancer.

A geospatial examination of specialist care accessibility and impact on health outcomes for patients with acute traumatic spinal cord injury in New South Wales, Australia: a population record linkage study

BACKGROUND

Timely treatment is essential for achieving optimal outcomes after traumatic spinal cord injury (TSCI), and expeditious transfer to a specialist spinal cord injury unit (SCIU) is recommended within 24 h from injury. Previous research in New South Wales (NSW) found only 57% of TSCI patients were admitted to SCIU for acute post-injury care; 73% transferred within 24 h from injury. We evaluated pre-hospital and inter-hospital transfer practices to better understand the post-injury care pathways impact on patient outcomes and highlight areas in the health service pathway that may benefit from improvement.

METHODS

This record linkage study included administrative pre-hospital (Ambulance), admissions (Admitted Patients) and costs data obtained from the Centre for Health Record Linkage, NSW. All patients aged ≥16 years with incident TSCI in NSW (2013-2016) were included. We investigated impacts of geographical disparities on pre-hospital and inter-hospital transport decisions from injury location using geospatial methods. Outcomes assessed included time to SCIU, surgery and the impact of these variables on the experience of inpatient complications.

RESULTS

Inclusion criteria identified 316 patients, geospatial analysis showed that over half (53%, n = 168) of all patients were injured within 60 min road travel of a SCIU, yet only 28.6% (n = 48) were directly transferred to a SCIU. Patients were more likely to experience direct transfer to a SCIU without comorbid trauma (p < 0.01) but higher ICISS (p < 0.001), cervical injury (p < 0.01), and transferred by air-ambulance (p < 0.01). Indirect transfer to SCIU was more likely with two or more additional traumatic injuries (p < 0.01) or incomplete injury (p < 0.01). Patients not admitted to SCIU at all were older (p = 0.05) with lower levels of injury (p < 0.01). Direct transfers received earlier operative intervention (median (IQR) 12.9(7.9) hours), compared with patients transferred indirectly to SCIU (median (IQR) 19.5(18.9) hours), and had lower risk of complications (OR 3.2 v 1.4, p < 0.001). Complications included pressure injury, deep vein thrombosis, urinary infection, among others.

CONCLUSIONS

Getting patients with acute TSCI patients to the right place at the right time is dependent on numerous factors; some are still being triaged directly to non-trauma services which delays specialist and surgical care and increases complication risks. The higher rates of complication following delayed transfer to a SCIU should motivate health service policy makers to investigate reasons for this practice and consent to improvement strategies. More stringent adherence to recommended guidelines would prioritise direct SCIU transfer for patients injured within 60 min radius, enabling the benefits of specialised care.

Impact of hospital type on risk-adjusted, traffic-related 30-day mortality: a population-based registry study

Background

Traffic incidents are still a major contributor to hospital admissions and trauma-related mortality. The aim of this nationwide study was to examine risk-adjusted traffic injury mortality to determine whether hospital type was an independent survival factor.

Methods

Data on all patients admitted to Swedish hospitals with traffic-related injuries, based on International Classification of Diseases codes, between 2001 and 2011 were extracted from the Swedish inpatient and cause of death registries. Using the binary outcome measure of death or survival, data were analysed using logistic regression, adjusting for age, sex, comorbidity, severity of injury and hospital type. The severity of injury was established using the International Classification of Diseases Injury Severity Score (ICISS).

Results

The final study population consisted of 152,693 hospital admissions. Young individuals (0-25 years of age) were overrepresented, accounting for 41% of traffic-related injuries. Men were overrepresented in all age categories. Fatalities at university hospitals had the lowest mean (SD) ICISS 0.68 (0.19). Regional and county hospitals had mean ICISS 0.75 (0.15) and 0.77 (0.15), respectively, for fatal traffic incidents. The crude overall mortality in the study population was 1193, with a mean ICISS 0.72 (0.17). Fatalities at university hospitals had the lowest mean ICISS 0.68 (0.19). Regional and county hospitals had mean ICISS 0.75 (0.15) and 0.77 (0.15), respectively, for fatal traffic incidents.When regional and county hospitals were merged into one group and its risk-adjusted mortality compared with university hospitals, no significant difference was found. A comparison between hospital groups with the most severely injured patients (ICISS ≤0.85) also did not show a significant difference (odds ratio, 1.13; 95% confidence interval, 0.97-1.32).

Conclusions

This study shows that, in Sweden, the type of hospital does not influence risk adjusted traffic related mortality, where the most severely injured patients are transported to the university hospitals and centralization of treatment is common.

Incidence and Outcome of Popliteal Artery Injury Associated with Knee Dislocations, Ligamentous Injuries, and Close to Knee Fractures: A Nationwide Population Based Cohort Study

OBJECTIVE

Arterial injury in knee trauma is rare but can be devastating if the diagnosis is delayed. The frequency of concomitant arterial injury resulting from knee dislocations remains unclear, and from knee fractures it remains unknown. The primary aim was to investigate the incidence of arterial injury in knee trauma requiring hospitalisation. Secondary aims were to identify risk factors and describe outcome.

METHODS

Traumatic popliteal artery injury and knee trauma were identified by International Classification of Diseases (ICD)-10 codes from the Swedish National Inpatient registry (NPR), 1998-2014 and linked with data using the unique personal identification number with the National Registry for vascular surgery (Swedvasc). Risk factors for popliteal artery injury (PAI) such as cause of injury, comorbidities and injury severity were extracted from the NPR. Socio-economic status data and population count came from Statistics Sweden, and cause and date of death from the Swedish Cause of Death Registry.

RESULTS

A total of 71 149 admissions due to all knee trauma were identified, and 359 with simultaneous PAIs. Some of those injuries were non-orthopaedic. The proportion of PAI after knee dislocation ranged between 3.4% (46/1370 dislocations or multiligamentous injuries) and 8.2% (46/564 dislocations), and 0.2% after fracture close to the knee (60/36 483). The most common causes of injury with PAI were falls causing knee dislocations and motor vehicle accidents (MVAs) causing fractures. The fact that all 46 injuries occurring after multiligamentous injuries were classified as knee dislocations is probably explained by the fact that the ICD codes are chosen retrospectively when the patient leaves the hospital.

CONCLUSION

PAI after knee dislocation is not uncommon, and most frequently caused by a fall. PAI associated with knee fracture is rare and mostly caused by a MVA, while in low energy knee fractures PAI is practically non-existent.

Trauma-related mortality of patients with severe psychiatric disorders: population-based study from the French national hospital database

BACKGROUND

Most research on mortality in people with severe psychiatric disorders has focused on natural causes of death. Little is known about trauma-related mortality, although bipolar disorder and schizophrenia have been associated with increased risk of self-administered injury and road accidents.

AIMS

To determine if 30-day in-patient mortality from traumatic injury was increased in people with bipolar disorder and schizophrenia compared with those without psychiatric disorders.

METHOD

A French national 2016 database of 144 058 hospital admissions for trauma was explored. Patients with bipolar disorder and schizophrenia were selected and matched with mentally healthy controls in a 1:3 ratio according to age, gender, social deprivation and region of residence. We collected the following data: sociodemographic characteristics, comorbidities, trauma severity characteristics and trauma circumstances. Study outcome was 30-day in-patient mortality.

RESULTS

The study included 1059 people with bipolar disorder, 1575 people with schizophrenia and their respective controls (n = 3177 and n = 4725). The 30-day mortality was 5.7% in bipolar disorder, 5.1% in schizophrenia and 3.3 and 3.8% in the controls, respectively. Only bipolar disorder was associated with increased mortality in univariate analyses. This association remained significant after adjustment for sociodemographic characteristics and comorbidities but not after adjustment for trauma severity. Self-administered injuries were associated with increased mortality independent of the presence of a psychiatric diagnosis.

CONCLUSIONS

Patients with bipolar disorder are at higher risk of 30-day mortality, probably through increased trauma severity. A self-administered injury is predictive of a poor survival prognosis regardless of psychiatric diagnosis.

Pre-injury health status and excess mortality in persons with traumatic brain injury: A decade-long historical cohort study

An increasing number of patients are able to survive traumatic brain injuries (TBIs) with advanced resuscitation. However, the role of their pre-injury health status in mortality in the following years is not known. Here, we followed 77,088 consecutive patients (59% male) who survived the TBI event in Ontario, Canada for more than a decade, and examined the relationships between their pre-injury health status and mortality rates in excess to the expected mortality calculated using sex- and age-specific life tables. There were 5792 deaths over the studied period, 3163 (6.95%) deaths in male and 2629 (8.33%) in female patients. The average excess mortality rate over the follow-up period of 14 years was 1.81 (95% confidence interval = 1.76-1.86). Analyses of follow-up time windows showed different patterns for the average excess rate of mortality following TBI, with the greatest rates observed in year one after injury. Among identified pre-injury comorbidity factors, 33 were associated with excess mortality rates. These rates were comparable between sexes. Additional analyses in the validation dataset confirmed that these findings were unlikely a result of TBI misclassification or unmeasured confounding. Thus, detection and subsequent management of pre-injury health status should be an integral component of any strategy to reduce excess mortality in TBI patients. The complexity of pre-injury comorbidity calls for integration of multidisciplinary health services to meet TBI patients' needs and prevent adverse outcomes.

Gap in funding for specialist hospitals treating patients with traumatic spinal cord injury under an activity-based funding model in New South Wales, Australia

Objective The aim of this study was to estimate the difference between treatment costs in acute care settings and the level of funding public hospitals would receive under the activity-based funding model. Methods Patients aged ≥16 years who had sustained an incident traumatic spinal cord injury (TSCI) between June 2013 and June 2016 in New South Wales were included in the study. Patients were identified from record-linked health data. Costs were estimated using two approaches: (1) using District Network Return (DNR) data; and (2) based on national weighted activity units (NWAU) assigned to activity-based funding activity. The funding gap in acute care treatment costs for TSCI patients was determined as the difference in cost estimates between the two approaches. Results Over the study period, 534 patients sustained an acute incident TSCI, accounting for 811 acute care hospital separations within index episodes. The total acute care treatment cost was estimated at A$40.5 million and A$29.9 million using the DNR- and NWAU-based methods respectively. The funding gap in total costs was greatest for the specialist spinal cord injury unit (SCIU) colocated with a major trauma service (MTS), at A$4.4 million over the study period. Conclusions The findings of this study suggest a substantial gap in funding for resource-intensive patients with TSCI in specialist hospitals under current DRG-based funding methods. What is known about the topic? DRG-based funding methods underestimate the treatment costs at the hospital level for patients with complex resource-intensive needs. This underestimation of true direct costs can lead to under-resourcing of those hospitals providing specialist services. What does this paper add? This study provides evidence of a difference between true direct costs in acute care settings and the level of funding hospitals would receive if funded according to the National Efficient Price and NWAU for patients with TSCI. The findings provide evidence of a shortfall in the casemix funding to public hospitals under the activity-based funding for resource-intensive care, such as patients with TSCI. Specifically, depending on the classification system, the principal referral hospitals, the SCIU colocated with an MTS and stand-alone SCIU were underfunded, whereas other non-specialist hospitals were overfunded for the acute care treatment of patients with TSCI. What are the implications for practitioners? Although health care financing mechanisms may vary internationally, the results of this study are applicable to other hospital payment systems based on diagnosis-related groups that describe patients of similar clinical characteristics and resource use. Such evidence is believed to be useful in understanding the adequacy of hospital payments and informing payment reform efforts. These findings may have service redesign policy implications and provide evidence for additional loadings for specialist hospitals treating low-volume, resource-intensive patients.

Pre-existing mental disorder, clinical profile, inpatient services and costs in people hospitalised following traumatic spinal injury: a whole population record linkage study

BACKGROUND

Risk of traumatic injury is increased in individuals with mental illness, substance use disorder and dual diagnosis (mental disorders); these conditions will pre-exist among individuals hospitalised with acute traumatic spinal injury (TSI). Although early intervention can improve outcomes for people who experience mental disorders or TSI, the incidence, management and cost of this often complex comorbid health profile is not sufficiently understood. In a whole population cohort of patients hospitalised with acute TSI, we aimed to describe the prevalence of pre-existing mental disorders and compare differences in injury epidemiology, costs and inpatient allied health service access.

METHODS

Record linkage study of all hospitalised cases of TSI between June 2013 and June 2016 in New South Wales, Australia. TSI was defined by specific International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) codes. Mental disorder status was considered as pre-existing where specific ICD-10-AM codes were recorded in incident admissions.

RESULTS

13 489 individuals sustained acute TSI during this study. 13.11%, 6.06% and 1.82% had pre-existing mental illness, substance use disorder and dual diagnosis, respectively. Individuals with mental disorder were older (p<0.001), more likely to have had a fall or self-harmed (p<0.001), experienced almost twice the length of stay and inpatient complications, and increased injury severity compared with individuals without mental disorder (p<0.001).

CONCLUSION

Individuals hospitalised for TSI with pre-existing mental disorder have greater likelihood of increased injury severity and more complex, costly acute care admissions compared with individuals without mental disorder. Care pathway optimisation including prevention of hospital-acquired complications for people with pre-existing mental disorders hospitalised for TSI is warranted.

Identifying Predictors of Higher Acute Care Costs for Patients With Traumatic Spinal Cord Injury and Modeling Acute Care Pathway Redesign: A Record Linkage Study

STUDY DESIGN

Record linkage study using healthcare utilization and costs data.

OBJECTIVE

To identify predictors of higher acute-care treatment costs and length of stay for patients with traumatic spinal cord injury (TSCI).

SUMMARY OF BACKGROUND DATA

There are few current or population-based estimates of acute hospitalization costs, length of stay, and other outcomes for people with TSCI, on which to base future planning for specialist SCI health care services.

METHODS

Record linkage study using healthcare utilization and costs data; all patients aged more than or equal to 16 years with incident TSCI in the Australian state of New South Wales (June 2013-June 2016). Generalized Linear Model regression to identify predictors of higher acute care treatment costs for patients with TSCI. Scenario analysis quantified the proportionate cost impacts of patient pathway modification.

RESULTS

Five hundred thirty-four incident cases of TSCI (74% male). Total cost of all acute index episodes approximately AUD$40.5 (95% confidence interval [CI] ±4.5) million; median cost per patient was AUD$45,473 (Interquartile Range: $15,535-$94,612). Patient pathways varied; acute care was less costly for patients admitted directly to a specialist spinal cord injury unit (SCIU) compared with indirect transfer within 24 hours. Over half (53%) of all patients experienced at least one complication during acute admission; their care was less costly if they had been admitted directly to SCIU. Scenario analysis demonstrated that a reduction of indirect transfers to SCIU by 10% yielded overall cost savings of AUD$3.1 million; an average per patient saving of AUD$5,861.

CONCLUSION

Direct transfer to SCIU for patients with acute TSCI resulted in lower treatment costs, shorter length of stay, and less costly complications. Modeling showed that optimizing patient-care pathways can result in significant acute-care cost savings. Reducing potentially preventable complications would further reduce costs and improve longer-term patient outcomes.

LEVEL OF EVIDENCE

3.

Where to start? Injury prevention priority scores in Canadian children

PURPOSE

Given limited resources, it is essential to determine which Mechanisms of Injury (MOIs) to prioritize for injury prevention policy and research. We developed objective, evidence-based Injury Prevention Priority Scores (IPPSs) for Canadian children across three prevention perspectives: mortality, injury severity, and resource utilization.

METHODS

We performed a retrospective cohort study of all injuries in Canada in individuals aged 0 to 19 years old from 2009 to 2014. For each MOI, an IPPS was calculated as a balanced measure of frequency and either mortality rate, median ICD-10 derived Injury Severity Score (ICISS), or median cost per hospitalization.

RESULTS

Of 87,017 injuries, 83,112 were nonfatal hospitalizations, and 3905 were deaths. Overall mortality rate was 0.04 deaths/injury, median ICISS was 0.994 (IQR 0.75-0.996), and median cost per hospitalization was CAD$3262 (IQR $2118-$5001). The top three mechanisms were falls (IPPS 72), intentional self-harm (IPPS 68), and drowning (IPPS 65) for mortality, falls (IPPS73), drowning (IPPS 61), and suffocation (IPPS 61) for injury severity and falls (IPPS 70), fires (IPPS 65), and intentional self-harm (IPPS 60) for resource utilization.

CONCLUSION

Falls, if prevented, would provide the most benefit to the largest proportion of the Canadian pediatric population and should be targeted for injury prevention.

LEVEL OF EVIDENCE

Level III.

Female risk-adjusted survival advantage after injuries caused by falls, traffic or assault: a nationwide 11-year study

BACKGROUND

A female survival advantage after injury has been observed, and animal models of trauma have suggested either hormonal or genetic mechanisms as component causes. Our aim was to compare age and risk-adjusted sex-related mortality in hospital for the three most common mechanisms of injury in relation to hormonal effects as seen by age.

METHODS

All hospital admissions for injury in Sweden during the period 2001-2011 were retrieved from the National Patient Registry and linked to the Cause of Death Registry. The International Classification of Diseases Injury Severity Score (ICISS) was used to adjust for injury severity, and the Charlson Comorbidity Index to adjust for comorbidity. Age categories (0-14, 15-50, and ≥ 51 years) were used to represent pre-menarche, reproductive and post- menopausal women.

RESULTS

Women had overall a survival benefit (OR 0.51; 95% CI 0.50 to 0.53) after adjustment for injury severity and comorbidity. A similar pattern was seen across the age categories (0-14 years OR 0.56 (95% CI 0.25 to 1.25), 15-50 years OR 0.70 (95% CI 0.57 to 0.87), and ≥ 51 years OR 0.49 (95% CI 0.48 to 0.51)).

CONCLUSION

In this 11-year population-based study we found no support for an oestrogen-related mechanism to explain the survival advantage for females compared to males following hospitalisation for injury.

Unintentional injuries: A profile of hospitalization and risk factors for in-hospital mortality in Beijing, China

INTRODUCTION

Unintentional injuries (UIs) impose a significant burden on low- and middle-income countries (LMICs). However, available UI epidemiological data are limited for LMICs, including China. This article aimed to provide an overview of the UI hospitalization profile, identify risk factors for in-hospital mortality and provide diagnosis-specific survival risk ratios (SRRs) for reference by LMICs using hospital discharge abstract data (DAD) from Beijing, China.

PATIENTS AND METHODS

A cross-sectional study was conducted for patients sustaining UIs requiring admission. Information was retrieved from 138 hospitals in Beijing to describe the demographics, injury nature, mechanisms, severity and hospital outcomes. Multivariate logistic regression was performed to identify and evaluate risk factors for in-hospital mortality for UIs.

RESULTS

Falls (57.1%), transport accidents (19.9%) and exposure to inanimate mechanical forces (16.4%) were the leading causes of UI hospitalization. Falls and transport accidents were responsible for 94.2% of the in-hospital deaths caused by UIs. Injury mechanisms differed among sex (χ² = 5322.1, P <  0.001) and age (χ² = 24,143.3, P <  0.001) groups. Male sex (OR: 1.50, 95% confidence interval (CI): 1.23-1.79), age ≥ 85 years (OR: 16.39, 95% CI: 7.46-36.00), Barthel Index at admission ≤ 60 (OR: 25.78, 95% CI: 13.30-49.95), modified Charlson comorbidity index ≥ 6 (OR: 2.60, 95% CI: 1.91-3.55), International Classification of Diseases-based injury severity score (ICISS) < 0.85 (OR: 15.17, 95% CI: 12.57-18.30), sustaining injuries to the head/neck (OR: 23.20, 95% CI: 7.31-73.64), injuries caused by foreign body entering through natural orifice (OR: 34.00, 95%CI: 6.37-181.54) and injuries resulting from transport accidents (OR: 1.71, 95% CI: 1.41-2.07) were important risk factors for in-hospital mortality for UIs.

CONCLUSIONS

Hospital DAD are an objective and cost-effective data source that allows for a hospital-based perspective of UI epidemiology. Sex, age, functional status at admission, comorbidities, injury nature, severity and mechanism are significantly associated with the in-hospital mortality of UIs in China. This study generates a reference dataset of diagnosis-specific SRRs from a large trauma population in China, which may be more applicable in injury severity estimation using ICISS in LMICs.

Identification and internal validation of models for predicting survival and ICU admission following a traumatic injury

Background

Measures to improve the accuracy of determining survival and intensive care unit (ICU) admission using the International Classification of Injury Severity Score (ICISS) are not often conducted on a population-wide basis. The aim is to determine if the predictive ability of survival and ICU admission using ICISS can be improved depending on the method used to derive ICISS and incremental inclusion of covariates.

Method

A retrospective analysis of linked injury hospitalisation and mortality data during 1 January 2010 to 30 June 2014 in New South Wales, Australia was conducted. Both multiplicative-injury and single-worst-injury ICISS were calculated. Logistic regression examined 90-day mortality and ICU admission with a range of predictor variables. The models were assessed in terms of their ability to discriminate survivors and non-survivors, model fit, and variation explained.

Results

There were 735,961 index injury admissions, 13,744 (1.9%) deaths within 90-days and 23,054 (3.1%) ICU admissions. The best predictive model for 90-day mortality was single-worst-injury ICISS including age group, gender, all comorbidities, trauma centre type, injury mechanism, and nature of injury as covariates. The multiplicative-injury ICISS with age group, gender, all comorbidities, injury mechanism, and nature of injury was the best predictive model for ICU admission.

Conclusions

The inclusion of comorbid conditions, injury mechanism and nature of injury, improved discrimination for both 90-day mortality and ICU admission. Moves to routinely use ICD-based injury severity measures, such as ICISS, should be considered for hospitalisation data replacing more resource-intensive injury severity classification measures.

Electronic supplementary material

The online version of this article (10.1186/s13049-018-0563-5) contains supplementary material, which is available to authorized users.

Predicting mortality with the international classification of disease injury severity score using survival risk ratios derived from an Indian trauma population: A cohort study

Background

Trauma is predicted to become the third leading cause of death in India by 2020, which indicate the need for urgent action. Trauma scores such as the international classification of diseases injury severity score (ICISS) have been used with great success in trauma research and in quality programmes to improve trauma care. To this date no valid trauma score has been developed for the Indian population.

Study design

This retrospective cohort study used a dataset of 16047 trauma-patients from four public university hospitals in urban India, which was divided into derivation and validation subsets. All injuries in the dataset were assigned an international classification of disease (ICD) code. Survival Risk Ratios (SRRs), for mortality within 24 hours and 30 days were then calculated for each ICD-code and used to calculate the corresponding ICISS. Score performance was measured using discrimination by calculating the area under the receiver operating characteristics curve (AUROCC) and calibration by calculating the calibration slope and intercept to plot a calibration curve.

Results

Predictions of 30-day mortality showed an AUROCC of 0.618, calibration slope of 0.269 and calibration intercept of 0.071. Estimates of 24-hour mortality consistently showed low AUROCCs and negative calibration slopes.

Conclusions

We attempted to derive and validate a version of the ICISS using SRRs calculated from an Indian population. However, the developed ICISS-scores overestimate mortality and implementing these scores in clinical or policy contexts is not recommended. This study, as well as previous reports, suggest that other scoring systems might be better suited for India and other Low- and middle-income countries until more data are available.

Assessment of the predictive value of the International Classification of Diseases Injury Severity Score for trauma mortality in urban India

BACKGROUND

Trauma is the cause of 1.2 million deaths in India annually. Injury severity scores play an important role in trauma research and care because these scores enable the adjustment of trauma severity when comparing mortality outcomes. The generalizability of the International Classification of Diseases Injury Severity Score (ICISS) between different populations is not fully known, and the validity of the ICISS has not been assessed in the Indian context. The aim of this study was to assess the predictive performances of three international versions of the ICISS, derived from data from Australia, New Zealand and pooled data from seven different high-income countries, in trauma patients admitted to four public hospitals in urban India.

MATERIAL AND METHODS

We used patient data from an Indian cohort of 16,047 trauma patients. The patients were assigned an ICISS based on International Classification of Diseases codes using survival risk ratios from publicly available data sets from Australia and New Zealand and with pooled data from seven different high-income countries. Predicted mortality based on the ICISS was compared with observed patient mortality, and the predictive performance was assessed in terms of discrimination and calibration.

RESULTS

Discrimination and calibration did not reach the threshold for predictive performance in any of the ICISS versions used. The threshold value used was 0.8 for discrimination, which was not significantly different from one for the calibration slope and not significantly different from zero for the calibration intercept.

CONCLUSIONS

None of the international versions of the ICISS adequately predicted mortality within the study population, indicating the need for an ICISS version specifically adapted to the Indian context.

Prehospital triage of patients diagnosed with perforated peptic ulcer or peptic ulcer bleeding: an observational study of patients calling 1-1-2

BACKGROUND

Triage systems are used in emergency medical services to systematically prioritize prehospital resources according to individual patient conditions. Previous studies have shown cases of preventable deaths in emergency medical services even when triage systems are used, indicating a potential undertriage among some conditions. The aim of this study was to investigate the triage level among patients diagnosed with perforated peptic ulcer (PPU) or peptic ulcer bleeding (PUB).

METHODS

In a three-year period in Central Denmark Region, all patients hospitalized within 24 h after a 1-1-2 emergency call and who subsequently received either a PPU or a PUB (hereinafter combined and referred to as PPU/PUB) or a First Hour Quintet (FHQ: respiratory failure, stroke, trauma, cardiac chest pain, and cardiac arrest) diagnosis were investigated. A modified Poisson regression was used to estimate the relative risk of receiving the highest and lowest prehospital response level. Also, a linear regression analysis was used to estimate the relative risk of 30-day mortality.

RESULTS

Of 8658 evaluated patients, 263 were diagnosed with PPU/PUB. After adjusting for relevant confounding variables, patients diagnosed with PPU/PUB were less likely to receive ambulance transportation compared to patients diagnosed with stroke, RR = 1.41 (CI: 1.28-1.56); trauma, RR = 1.28 (CI: 1.15-1.42); cardiac chest pain, RR = 1.47 (CI: 1.33-1.62); and cardiac arrest, RR = 1.44 (CI: 1.31-1.42). Among patients diagnosed with PPU/PUB, 6.5% (CI: 3.3-9.7) did not receive ambulance transportation. The proportion of patients not receiving ambulance transportation was higher among patients diagnosed with PPU/PUB compared to patients diagnosed with an FHQ diagnosis. The 30-day mortality rate among patients diagnosed with PPU/PUB was 7.8% (CI: 4.2-11.1). This was lower than the 30-day mortality rate among patients diagnosed with respiratory failure (P = 0.010), stroke (P = 0.001), and cardiac arrest (P < 0.001), but comparable to the 30-day mortality among patients diagnosed with cardiac chest pain (P = 0.080) and trauma (P = 0.281).

CONCLUSION

Among patients calling 1-1-2, fewer patients diagnosed with PPU/PUB received ambulance transportation than patients diagnosed with FHQ diagnoses, despite a high mortality among patients diagnosed with PPU/PUB.

Decreased risk adjusted 30-day mortality for hospital admitted injuries: a multi-centre longitudinal study

Background

The interpretation of changes in injury-related mortality over time requires an understanding of changes in the incidence of the various types of injury, and adjustment for their severity. Our aim was to investigate changes over time in incidence of hospital admission for injuries caused by falls, traffic incidents, or assaults, and to assess the risk-adjusted short-term mortality for these patients.

Methods

All patients admitted to hospital with injuries caused by falls, traffic incidents, or assaults during the years 2001–11 in Sweden were identified from the nationwide population-based Patient Registry. The trend in mortality over time for each cause of injury was adjusted for age, sex, comorbidity and severity of injury as classified from the International Classification of diseases, version 10 Injury Severity Score (ICISS).

Results

Both the incidence of fall (689 to 636/100000 inhabitants: p = 0.047, coefficient − 4.71) and traffic related injuries (169 to 123/100000 inhabitants: p < 0.0001, coefficient − 5.37) decreased over time while incidence of assault related injuries remained essentially unchanged during the study period. There was an overall decrease in risk-adjusted 30-day mortality in all three groups (OR 1.00; CI95% 0.99–1.00). Decreases in traffic (OR 0.95; 95% CI 0.93 to 0.97) and assault (OR 0.93; 95% CI 0.87 to 0.99) related injuries was significant whereas falls were not during this 11-year period.

Discussion

Risk-adjustment is a good way to use big materials to find epidemiological changes. However after adjusting for age, year, sex and risk we find that a possible factor is left in the pre- and/or in-hospital care.

Conclusions

The decrease in risk-adjusted mortality may suggest changes over time in pre- and/or in-hospital care. A non-significantdecrease in risk-adjusted mortality was registered for falls, which may indicate that low-energy trauma has not benefited for the increased survivability as much as high-energy trauma, ie traffic- and assault related injuries.

Development and validation of an ICD-10-based disability predictive index for patients admitted to hospitals with trauma

BACKGROUND

There was no established disability predictive measurement for patients with trauma that could be used in administrative claims databases. The aim of the present study was to develop and validate a diagnosis-based disability predictive index for severe physical disability at discharge using the International Classification of Diseases, 10th revision (ICD-10) coding.

METHODS

This retrospective observational study used the Diagnosis Procedure Combination database in Japan. Patients who were admitted to hospitals with trauma and discharged alive from 01 April 2010 to 31 March 2015 were included. Pediatric patients under 15 years old were excluded. Data for patients admitted to hospitals from 01 April 2010 to 31 March 2013 was used for development of a disability predictive index (derivation cohort), while data for patients admitted to hospitals from 01 April 2013 to 31 March 2015 was used for the internal validation (validation cohort). The outcome of interest was severe physical disability defined as the Barthel Index score of <60 at discharge. Trauma-related ICD-10 codes were categorized into 36 injury groups with reference to the categorization used in the Global Burden of Diseases study 2013. A multivariable logistic regression analysis was performed for the outcome using the injury groups and patient baseline characteristics including patient age, sex, and Charlson Comorbidity Index (CCI) score in the derivation cohort. A score corresponding to a regression coefficient was assigned to each injury group. The disability predictive index for each patient was defined as the sum of the scores. The predictive performance of the index was validated using the receiver operating characteristic curve analysis in the validation cohort.

RESULTS

The derivation cohort included 1,475,158 patients, while the validation cohort included 939,659 patients. Of the 939,659 patients, 235,382 (25.0%) were discharged with severe physical disability. The c-statistics of the disability predictive index was 0.795 (95% confidence interval [CI] 0.794-0.795), while that of a model using the disability predictive index and patient baseline characteristics was 0.856 (95% CI 0.855-0.857).

CONCLUSIONS

Severe physical disability at discharge may be well predicted with patient age, sex, CCI score, and the diagnosis-based disability predictive index in patients admitted to hospitals with trauma.

Impact of hospital volume on mortality in patients with severe torso injury

BACKGROUND

Whether a positive volume-outcome relationship exists in the context of trauma remains controversial. Heterogeneity in the definition of hospital volume in previous studies is one of the main reasons for this inconclusiveness. We investigated whether hospital volume is associated with mortality in patients with severe torso injury using two different definitions of hospital volume.

MATERIALS AND METHODS

This retrospective cohort study used the Diagnosis Procedure Combination database in Japan. Patients who were admitted to tertiary emergency centers with severe torso injury and underwent emergency surgery or interventional radiology treatment for the torso injury upon admission from April 1, 2010 to March 31, 2014 were included. Hospital volume was defined as the annual number of admissions with severe torso injury (HV-torso) or the annual number of total trauma admissions (HV-all). The main outcome was 28-d mortality. Multivariable logistic regression models fitted with generalized estimating equations were used to evaluate relationships between hospital volume and 28-d mortality.

RESULTS

Overall, 7725 patients were included. The 28-d mortality rate was 15.3%. The HV-torso was significantly associated with reduced 28-d mortality (adjusted odds ratio = 0.59; 95% confidence interval = 0.44-0.79). However, there was no significant association between the HV-all and mortality (adjusted odds ratio = 1.02; 95% confidence interval = 0.72-1.46).

CONCLUSIONS

The HV-torso was significantly associated with reduced mortality in patients with severe torso injury. In contrast, the HV-all had no significant relationship with their mortality. Regionalization of trauma care for severe torso injury may be beneficial for patients with severe torso injury.

Prediction of mortality risk in victims of violent crimes

BACKGROUND

To predict mortality risk in victims of violent crimes based on individual injury diagnoses and other information available in health care registries.

METHODS

Data from the Swedish hospital discharge registry and the cause of death registry were combined to identify 15,000 hospitalisations or prehospital deaths related to violent crimes. The ability of patient characteristics, injury type and severity, and cause of injury to predict death was modelled using conventional, Lasso, or Bayesian logistic regression in a development dataset and evaluated in a validation dataset.

RESULTS

Of 14,470 injury events severe enough to cause death or hospitalization 3.7% (556) died before hospital admission and 0.5% (71) during the hospital stay. The majority (76%) of hospital survivors had minor injury severity and most (67%) were discharged from hospital within 1day. A multivariable model with age, sex, the ICD-10 based injury severity score (ICISS), cause of injury, and major injury region provided predictions with very good discrimination (C-index=0.99) and calibration. Adding information on major injury interactions further improved model performance. Modeling individual injury diagnoses did not improve predictions over the combined ICISS score.

CONCLUSIONS

Mortality risk after violent crimes can be accurately estimated using administrative data. The use of Bayesian regression models provides meaningful risk assessment with more straightforward interpretation of uncertainty of the prediction, potentially also on the individual level. This can aid estimation of incidence trends over time and comparisons of outcome of violent crimes for injury surveillance and in forensic medicine.

Performance of International Classification of Diseases-based injury severity measures used to predict in-hospital mortality and intensive care admission among traumatic brain-injured patients

BACKGROUND

The International Classification of Diseases (ICD) is the main classification system used for population-based traumatic brain injury (TBI) surveillance activities but does not contain direct information on injury severity. International Classification of Diseases-based injury severity measures can be empirically derived or mapped to the Abbreviated Injury Scale, but no single approach has been formally recommended for TBI.

OBJECTIVE

The aim of this study was to compare the accuracy of different ICD-based injury severity measures for predicting in-hospital mortality and intensive care unit (ICU) admission in TBI patients.

METHODS

We conducted a population-based retrospective cohort study. We identified all patients 16 years or older with a TBI diagnosis who received acute care between April 1, 2006, and March 31, 2013, from the Quebec Hospital Discharge Database. The accuracy of five ICD-based injury severity measures for predicting mortality and ICU admission was compared using measures of discrimination (area under the receiver operating characteristic curve [AUC]) and calibration (calibration plot and the Hosmer-Lemeshow goodness-of-fit statistic).

RESULTS

Of 31,087 traumatic brain-injured patients in the study population, 9.0% died in hospital, and 34.4% were admitted to the ICU. Among ICD-based severity measures that were assessed, the multiplied derivative of ICD-based Injury Severity Score (ICISS-Multiplicative) demonstrated the best discriminative ability for predicting in-hospital mortality (AUC, 0.858; 95% confidence interval, 0.852-0.864) and ICU admissions (AUC, 0.813; 95% confidence interval, 0.808-0.818). Calibration assessments showed good agreement between observed and predicted in-hospital mortality for ICISS measures. All severity measures presented high agreement between observed and expected probabilities of ICU admission for all deciles of risk.

CONCLUSIONS

The ICD-based injury severity measures can be used to accurately predict in-hospital mortality and ICU admission in TBI patients. The ICISS-Multiplicative generally outperformed other ICD-based injury severity measures and should be preferred to control for differences in baseline characteristics between TBI patients in surveillance activities or injury research when only ICD codes are available.

LEVEL OF EVIDENCE

Prognostic study, level III.

Relationship between hospital volume and outcomes in patients with traumatic brain injury: A retrospective observational study using a national inpatient database in Japan

BACKGROUND

The relationship between hospital volume and outcome after traumatic brain injury (TBI) is not completely understood in a real clinical setting. We investigated whether patients admitted with TBI achieved better outcomes in high-volume hospitals than in low-volume hospitals using a national inpatient database in Japan.

METHODS

This retrospective cohort study used the Diagnosis Combination Procedure database in Japan. We included patients with TBI admitted to hospitals with a Japan Coma Scale (JCS) score ≥2 between April 1, 2013 and March 31, 2014. Hospital volume was defined as the annual number of all admissions with TBI in individual hospitals. The hospital volume was categorized into four volume groups: low (≤60 admissions per hospital), medium-low (61-120 admissions per hospital), medium-high (121-180 admissions per hospital) and high (≥181 admissions per hospital). The outcomes of interest included 28-day mortality and survival discharge with complete dependency defined as a Barthel Index score of 0 at discharge. We used multivariate logistic regression models fitted with generalized estimating equations to evaluate relationships between the hospital volume and the outcomes. The hospital volume was evaluated both as categorical variables defined above and as continuous variables.

RESULTS

The analysis dataset consisted of 20,146 eligible patients. Of these, 2,784 died within 28days (13.8%) and 3,409 were completely dependent among 16,996 patients discharged alive (20.1%). Multivariate analyses found that there was no significant difference between the high-volume and low-volume groups for 28-day mortality (adjusted odds ratio [OR] 0.79, 95% confidence interval [CI] 0.58-1.06 for the high-volume group) or complete dependency at discharge (adjusted OR 0.94, 95% CI 0.71-1.23 for the high-volume group). The results were the same when the hospital volume was evaluated as a continuous variable.

CONCLUSIONS

Hospital volume did not appear to influence outcomes in patients with TBI. High-volume hospitals may not be necessarily beneficial for patients with TBI exhibiting impaired consciousness as a whole.

Assessing Field Triage Decisions and the International Classification Injury Severity Score (ICISS) at Predicting Outcomes of Trauma Patients

Florida considers the International Classification Injury Severity Score (ICISS) from hospital discharges within a geographic region in the apportionment of trauma centers (TCs). Patients with an ICISS <0.85 are considered to require triage to a TC, yet many are triaged to an emergency department (ED). We assess outcomes of those with an ICISS <0.85 by the actual triage decision of emergency medical services (EMS). From October 2011 to October 2013, 39,021 consecutive admissions with injury ICD-9 codes were analyzed. ICISS was calculated from the product of the survival risk ratios for a patient's three worst injuries. Outcomes were compared between patients with ICISS <0.85 either triaged to the ED or its separate, neighboring, free-standing TC at a large urban hospital. A total of 32,191 (83%) patients were triaged to the ED by EMS and 6,827 (17%) were triaged to the TC. Of these, 2544 had an ICISS <0.85, with 2145 (84%) being triaged to the TC and 399 (16%) to the ED. In these patients, those taken to the TC more often required admission, and those taken to the ED had better outcomes. When the confounders influencing triage to an ED or a TC are eliminated, those triaged by EMS to the ED rather than the TC had better overall outcomes. EMS providers better identified patients at risk for mortality than did the retrospective application of ICISS. ICISS <0.85 does not identify the absolute need for TC as EMS providers were able to appropriately triage a large portion of this population to the ED.

Development and validation of a new ICD-10-based trauma mortality prediction scoring system using a Japanese national inpatient database

INTRODUCTION

To develop and validate a new trauma mortality prediction scoring system based on International Statistical Classification of Diseases (ICD)-10 codes, using a Japanese administrative claims and discharge abstract database.

METHODS

This retrospective observational study used the Japanese Diagnosis Procedure Combination database. Injuries were categorised into 33 groups with 5 additional groups based on injury sites and types. A multivariable logistic regression analysis was performed for in-hospital mortality in a derivation cohort after adjusting for the 38 groups, patient's sex, age and Charlson Comorbidity Index score. Each variable was assigned a score that was equal to the value of the regression coefficient. The new severity score was defined as the sum of the scores. The new scoring system was tested in a validation cohort.

RESULTS

The mortality rates were 2.4% (9270/393 395) and 2.5% (8778/349 285) in the derivation and validation cohorts, respectively. The area under the receiver operating curve (AUROC) of the new scoring system was 0.887 (95% CI 0.884 to 0.890) in the validation cohort. Subgroup analyses showed that the scoring system retained high predictive performance both for patients <65 years (AUROC 0.934, 95% CI 0.928 to 0.939) and for elderly patients at the age of ≥65 years (AUROC 0.825, 95% CI 0.820 to 0.829).

CONCLUSIONS

A new ICD-10-based injury severity scoring system was developed and validated. Further studies are required to validate the scoring system in other databases.

The epidemiology of life-threatening work-related injury--a demonstration paper

BACKGROUND

Workers' compensation (WC) data traditionally provides information to stakeholders on work-related disabling injuries. It is important to complement this with information on serious threat to life (TTL) injury, which is the focus of this paper.

METHODS

In this cross-sectional descriptive epidemiological study, based on New Zealand's WC data linked to hospital discharge data, TTL was measured using the ICD10-based Injury Severity Score (ICISS); ICISS ≤ 0.941 was used to define serious TTL injury.

RESULTS

During 2002-2004, there was an average of 368 serious TTL work-related injury cases annually. The distribution of these injuries was very different from those traditionally found using WC data to describe disabling injury. For example, for serious TTL injury the main injury types included traumatic brain injury, whereas for disabling injury it was sprains and dislocations.

CONCLUSIONS

The method presented provides the opportunity for government agencies to produce a national description of the epidemiology of serious TTL work-related injuries.