Comparing traditional and novel injury scoring systems in a US level-I trauma center: an opportunity for improved injury surveillance in low- and middle-income countries.

BACKGROUND: In most low- and middle-income countries (LMICs), the resources to accurately quantify injury severity using traditional injury scoring systems are limited. Novel injury scoring systems appear to have adequate discrimination for mortality in LMIC contexts, but they have not been rigorously compared where traditional injury scores can be accurately calculated. To determine whether novel injury scoring systems perform as well as traditional ones in a HIC with complete and comprehensive data collection. METHODS: Data from an American level-I trauma registry collected 2008-2013 were used to compare three traditional injury scoring systems: Injury Severity Score (ISS); Revised Trauma Score (RTS); and Trauma Injury Severity Score (TRISS); and three novel injury scoring systems: Kampala Trauma Score (KTS); Mechanism, GCS, Age and Pressure (MGAP) score; and GCS, Age and Pressure (GAP) score. Logistic regression was used to assess the association between each scoring system and mortality. Standardized regression coefficients (ß2), Akaike information criteria, area under the receiver operating characteristics curve, and the calibration line intercept and slope were used to evaluate the discrimination and calibration of each model. RESULTS: Among 18,746 patients, all six scores were associated with hospital mortality. GAP had the highest effect size, and KTS had the lowest median Akaike information criteria. Although TRISS discriminated best, the discrimination of KTS approached that of TRISS and outperformed GAP, MGAP, RTS, and ISS. MGAP was best calibrated, and KTS was better calibrated than RTS, GAP, ISS, or TRISS. CONCLUSIONS: The novel injury scoring systems (KTS, MGAP, and GAP), which are more feasible to calculate in low-resource settings, discriminated hospital mortality as well as traditional injury scoring systems (ISS and RTS) and approached the discrimination of a sophisticated, data-intensive injury scoring system (TRISS) in a high-resource setting. Two novel injury scoring systems (KTS and MGAP) surpassed the calibration of TRISS. These novel injury scoring systems should be considered when clinicians and researchers wish to accurately account for injury severity. Implementation of these resource-appropriate tools in LMICs can improve injury surveillance, guiding quality improvement efforts, and supporting advocacy for resource allocation commensurate with the volume and severity of trauma.

A systematic review of quantitative research on traumatic brain injury in India.

INTRODUCTION: Over a quarter of the world's trauma deaths occur in India, with traumatic brain injury (TBI) as the leading cause of death and disability within trauma. With little known about TBI in India, we set out to do a systematic review to characterize the quantitative literature on TBI in India. MATERIALS AND METHODS: The following databases were searched from their inception to December 31, 2015: PubMed, Cochrane, Web of Science, and the World Health Organization's Global Health Library, using the keywords: neurotrauma, brain injury, traumatic brain injury, TBI, head injury, and India. Articles were screened by two independent reviewers, with disagreements arbitrated by discussion or a third reviewer. RESULTS: A total of 72 manuscripts were included, encapsulating 19962 patients over 27 years in 14 states of India. The sample-size-weighted mean age was 31.3 years, male-to-female ratio was 3.8:1, and sample-size-weighted mean in-hospital mortality was 24.6%. Age and mortality did not change significantly over time. Road traffic accidents (55.5%) and falls (29.2%) were the most commonly reported mechanisms of injury for TBI in India. The mean quality of reporting on TBI in India was 65.7%, according to the appropriate EQUATOR guideline score. CONCLUSION: The quality of reporting of quantitative studies published on TBI in India is low, and future methodological excellence should be ensured. The demographics and outcomes identified can be used as an epidemiological baseline for future research on TBI in India. Future research can build upon this platform to develop and refine context-appropriate policy recommendations and treatment protocols.

Waiting at the hospital door: a prospective, multicentre assessment of third delay in four tertiary hospitals in India.

BACKGROUND: A common framework to assess delays in health-care in countries with low-income and middle-income (LMICs) defines three time periods that add to the interval between onset of symptoms and treatment; the time it takes to receive care after hospital arrival is known as the third delay. Tertiary centres in LMICs are known to be overcrowded and under-capacity, but few studies have formally assessed the third delay. This study aims to quantify the third delay in LMIC tertiary centres and identify contributing factors at the facility level. METHODS: A prospective multicentre study was conducted from July, 2013, to July, 2014, in four tertiary care hospitals in the three largest cities in India: Mumbai, Delhi, and Kolkata. The time from patient arrival to the time when vital signs were first recorded was used as a proxy for the third delay. This delay was recorded by the research officers for those patients who were directly observed. For the rest of the patients the data were collected from patient records. Qualitative interviews were conducted with a subset of patients exploring reasons for the delay. FINDINGS: Data were collected for 5087 patients (1664 from Delhi, 469 from Mumbai centre-1, 711 from Mumbai centre-2, and 2243 from Kolkatta); median age was 30 years (IQR 20-45), 3944 (78%) were men, 3372 (66%) were transfers from other facilities, and 3424 (67·3%) arrived in an ambulance. Researchers directly observed 1392 (27·4%) patients from arrival to time of vital signs. There were wide variations in delays between groups, transferred versus direct presentation (0 min vs 20 min) and in between hospitals (median time 0·0 min in Mumbai to 1·5 h in Kolkatta) and in groups within each hospital. The reasons for delay were multifactorial: administrative (police case recordings, admission paper registration), logistical (no vacant beds, no physician available), and process-based (investigations before vitals, multiple patients at one time, junior physicians in-charge); process based reasons were the most common (80%). INTERPRETATION: Delays in care persist in tertiary centres in LMICs for a variety of reasons. Low-cost but context-specific changes that optimise care processes like prioritisation and transfer protocols could yield major reductions in third delay. Adoption of best practices of the better performing hospitals in the Indian setting will help to improve the trauma quality practices in India. FUNDING: The Laerdal Foundation for Acute Medicine and the Swedish National Board of Health and Welfare.

30-Day In-hospital Trauma Mortality in Four Urban University Hospitals Using an Indian Trauma Registry.

INTRODUCTION: In India, half of the annual 200,000 road traffic deaths occur in hospitals, but the exact in-hospital trauma mortality rate remains unknown. A research consortium of universities, with a mandate to reduce trauma mortality, measured the baseline 30-day in-hospital mortality rate. METHODS: Between September 2013 and February 2015, trained data collectors collected on-admission demographic, physiological vital signs, and health service performance indicators (time of injury to admission, investigation, or intervention) on all patients with traumatic injuries admitted to four public university hospitals in three Indian megacities. RESULTS: Of the 11,202 hospitalized trauma patients, 21.4 % died within 30 days of hospitalization. The median age was 30 years for survivors and 37 years for non-survivors. The on-admission systolic blood pressure and Glasgow Coma Score was near-normal in survivors, but was significantly lower in non-survivors and associated with both early and late mortality (p = 0.001). In the absence of a trauma system, there were process-of-care delays from injury to reaching and being examined, investigated, or operated in the hospital. CONCLUSION: Using a multi-institutional Indian registry, this study is the first to systematically document that the 30-day in-hospital trauma mortality was twice that found in similar registries from high-income countries. Physiological scoring of on-admission vitals was clinically useful to predict mortality. More research is needed to understand the causes of high mortality and time delays in the process of delivering trauma care in India, which has no prehospital or trauma system.

Validation of a novel prediction model for early mortality in adult trauma patients in three public university hospitals in urban India.

BACKGROUND: Trauma is one of the top threats to population health globally. Several prediction models have been developed to supplement clinical judgment in trauma care. Whereas most models have been developed in high-income countries the majority of trauma deaths occur in low- and middle-income countries. Almost 20 % of all global trauma deaths occur in India alone. The aim of this study was to validate a basic clinical prediction model for use in urban Indian university hospitals, and to compare it with existing models for use in early trauma care. METHODS: We conducted a prospective cohort study in three hospitals across urban India. The model we aimed to validate included systolic blood pressure and Glasgow coma scale. We compared this model with three additional models, which all have been designed for use in bedside trauma care, and two single variable models based on systolic blood pressure and Glasgow coma scale respectively. The outcome was early mortality, defined as death within 24 h from the time when vital signs were first measured. We compared the models in terms of discrimination, calibration, and potential clinical consequences using decision curve analysis. Multiple imputation was used to handle missing data. Performance measures are reported using their median and inter-quartile range (IQR) across imputed datasets. RESULTS: We analysed 4440 patients, out of which 1629 were used as an updating sample and 2811 as a validation sample. We found no evidence that the basic model that included only systolic blood pressure and Glasgow coma scale had worse discrimination or potential clinical consequences compared to the other models. A model that also included heart had better calibration. For the model with systolic blood pressure and Glasgow coma scale the discrimination in terms of area under the receiver operating characteristics curve was 0.846 (IQR 0.841-0.849). Calibration measured by estimating a calibration slope was 1.183 (IQR 1.168-1.202). Decision curve analysis revealed that using this model could potentially result in 45 fewer unnecessary surveys per 100 patients. CONCLUSIONS: A basic clinical prediction model with only two parameters may prove to be a feasible alternative to more complex models in contexts such as the Indian public university hospitals studied here. We present a colour-coded chart to further simplify the decision making in early trauma care.

Unmet burden of cleft lip and palate in rural Gujarat, India: a population-based study.

BACKGROUND: The burden of cleft lip and palate (CLP) in the developing world is being tackled by local hospitals and international surgical missions. However, the unmet surgical burden of these conditions is not known, because there are few population-based studies. We conducted this study to find the incidence and prevalence of cleft lip (CL), cleft palate (CP), and CLP and also estimate the unmet burden of these conditions. METHODS: Four blocks comprising of half a million people in the Patan district of Gujarat were chosen as the study areas. This study was conducted over a period of 3 months in 2009. Patients with CL, CP, and CLP were identified by community health workers using snowball sampling method. Data collected included demographics, type of cleft, operated or not, and place of operation. Disability adjusted life years (DALY) was calculated to measure the unmet burden of this disease. RESULTS: The most common among the three conditions was CL (69.4 %). Overall, cleft abnormalities were more common in males (61 %). The overall incidence and prevalence of cleft deformity was 0.73 per 1,000 live births and 0.1 per 1,000 people respectively. The unmet burden of surgical disease of these four blocks was 230 to 494 DALYs. CONCLUSIONS: The incidence of CL with or without palate was found to be 0.7 per 1,000 live births. The large number of unoperated cases (backlog) of cleft deformities suggests a big burden of unmet need in rural India.

Optimal evidence in difficult settings: improving health interventions and decision making in disasters.

Martin Gerdin and colleagues argue that disaster health interventions and decision-making can benefit from an evidence-based approach Please see later in the article for the Editors' Summary.

Does need matter? Needs assessments and decision-making among major humanitarian health agencies.

Disasters of physical origin, including earthquakes, floods, landslides, tidal waves, tropical storms, tsunamis, and volcanic eruptions, have affected millions of people globally over the past 100 years. Proportionately, there is far greater likelihood of being affected by such disasters in low-income countries than in high-income countries. Furthermore, low-income countries are in need of international assistance following disasters more often than high-income countries. The funding of international humanitarian assistance has increased from USD 12.9 billion in 2006 to an estimated USD 16.7 billion in 2010. The majority of this funding is channelled through humanitarian agencies and is supposed to be distributed based on the need of those affected, as assessed using needs assessments. Such needs assessments may be used to inform decisions internally, to influence others, to justify response decisions, and to obtain funding. Little is known about the quality of needs assessments in practical applications. Consequently, this paper reports on and analyses the views of operational decision-makers in major health-related humanitarian agencies on needs assessments.

Foreign field hospitals after the 2010 Haiti earthquake: how good were we?

OBJECTIVE: To assess the timing and activities of foreign field hospitals (FFH) deployed during the first month after the Haiti earthquake and to evaluate adherence to WHO/Pan American Health Organization (PAHO) guidelines. Results were compared with data from past sudden-onset disasters. METHODS: A systematic attempt was made to contact all relief actors within the health care sector involved in the 12 January through 12 February 2010 FFH deployment. This was done using an email-based questionnaire and a web survey. In addition, the authors undertook a literature review using PubMed and the Google search engine between March 2010 and May 2011. The authors contacted key informants and agencies identified by direct observations in the field by email or phone. RESULTS: A total of 44 FFH were identified. The first FFH was operational on day two post-earthquake. The number of FFH beds peaked at about 3300 on day 17 post-earthquake. During the first month, the authors estimate that FFH conducted no more than 12 000 major surgical operations. While 25% of the FFH adhered to either WHO/PAHO first essential deployment requirements, none followed both requirements of WHO/PAHO. Compared with the 2005 earthquake in Pakistan, twice as many FFH provided medical care, resulting in three times more FFH beds. CONCLUSIONS: The present study suggests that more FFH were sent to Haiti than to any previous sudden-onset disasters, but due to lack of data and transparency it remains impossible to determine to what extent did the first wave of FFH do any good in Haiti.

Time for order in chaos! A health system framework for foreign medical teams in earthquakes.

The number of reported natural disasters is increasing, as is the number of foreign medical teams (FMTs) sent to provide relief. Studies show that FMTs are not coordinated, nor are they adapted to the medical needs of victims. Another key challenge to the response has been the lack of common terminologies, definitions, and frameworks for FMTs following disasters.In this report, a conceptual health system framework that captures two essential components of health care response by FMTs after earthquakes is presented. This framework was developed using expert panels and personal experience, as well as an exhaustive literature review.The framework can facilitate decisions for deployment of FMTs, as well as facilitate coordination in disaster-affected countries. It also can be an important tool for registering agencies that send FMTs to sudden onset disasters, and ultimately for improving disaster response.

Income change after cruciate ligament injury - A population-based study.

OBJECTIVES: To investigate the association between choice of treatment and patients' income after cruciate ligament (CL) injury and assess the effect of different covariates such as sex, age, comorbidities and type of work. METHODS: This entire-population cohort study in Sweden included working patients with a diagnosed CL injury between 2002 and 2005, identified in The National Swedish Patient Register (n = 13,662). The exposure was the treatment choice (operative or non-operative treatment). The main outcome measure was average yearly income five years after CL diagnosis, adjusted for the following covariates: sex, age, comorbidities, type of work, region, calendar year, education and income. RESULTS: Relative to non-operative treatment, operative treatment was associated with greater average yearly incomes (nine to 15%) after injury among patients between 20 and 50 years, patients with partial university education, patients living in large cities and patients with one comorbidity, despite no overall significant association in the national cohort. Delayed operative treatment (>1 year) had no significant association with income change, whereas early operative treatment (<1 year) was associated with higher average yearly incomes (11 to 16%) among females, patients between 20 and 50 years, patients living in large cities and patients with one comorbidity. CONCLUSIONS: In a broad sense, treatment choice was not associated with changes in income five years after CL injuries among patients in the workforce, however earlier operative treatment was associated with higher average incomes among patients with ages between 20 and 50, females, living in large cities, with one comorbidity and with a high level of education.

The clinical usefulness of prognostic prediction models in critical illness.

Critical illness is any immediately life-threatening disease or trauma and results in several million deaths globally every year. Responsive hospital systems for managing critical illness include quick and accurate identification of the critically ill patients. Prognostic prediction models are widely used for this aim. To be clinically useful, a model should have good predictive performance, often measured using discrimination and calibration. This is not sufficient though: a model also needs to be tested in the setting where it will be used, it should be user-friendly and should guide decision making and actions. The clinical usefulness and impact on patient outcomes of prediction models has not been greatly studied. The focus of research should shift from attempts to optimise the precision of models to real-world intervention studies to compare the performance of models and their impacts on outcomes.

Ni-catalyzed Si-B addition to 1,3-dienes: disproportionation in lieu of silaboration.

[reaction: see text] Upon attempted silaboration of acyclic 1- and 1,4-substituted 1,3-dienes, a new disproportionation reaction was discovered, yielding 1:1 mixtures of allylsilanes and dienylboranes. It was demonstrated that, as a key step in this new catalytic process, hydrogen is being transferred from one diene moiety to another.

How Bad Is It? Usefulness of the "7eed Model" for Scoring Severity and Level of Need in Complex Emergencies.

BACKGROUND: Humanitarian assistance is designated to save lives and alleviate suffering among people affected by disasters. In 2014, close to 25 billion USD was allocated to humanitarian assistance, more than 80% of it from governmental donors and EU institutions. Most of these funds are devoted to Complex Emergencies (CE). It is widely accepted that the needs of the affected population should be the main determinant for resource allocations of humanitarian funding. However, to date no common, systematic, and transparent system for needs-based allocations exists. In an earlier paper, an easy-to-use model, "the 7eed model", based on readily available indicators that distinguished between levels of severity among disaster-affected countries was presented. The aim of this paper is to assess the usefulness of the 7eed model in regards to 1) data availability, 2) variations between CE effected countries and sensitivity to change over time, and 3) reliability in capturing severity and levels of need. METHOD: We applied the 7eed model to 25 countries with CE using data from 2013 to 2015. Data availability and indicator value variations were assessed using heat maps. To calculate a severity score and a needs score, we applied a standardised mathematical formula, based on the UTSTEIN template. We assessed the model for reliability on previous CEs with a "known" outcome in terms of excess mortality. RESULTS: Most of the required data was available for nearly all countries and indicators, and availability increased over time. The 7eed model was able to discriminate between levels of severity and needs among countries. Comparison with historical complex disasters showed a correlation between excess mortality and severity score. CONCLUSION: Our study indicates that the proposed 7eed model can serve as a useful tool for setting funding levels for humanitarian assistance according to measurable levels of need. The 7eed model provides national level information but does not take into account local variations or specific contextual factors.

Validation of international trauma scoring systems in urban trauma centres in India.

INTRODUCTION: In the Lower-Middle Income Country setting, we validate trauma severity scoring systems, namely Injury Severity Score (ISS), New Injury Severity Scale (NISS) score, the Kampala Trauma Score (KTS), Revised Trauma Score (RTS) score and the TRauma Injury Severity Score (TRISS) using Indian trauma patients. PATIENTS AND METHODS: From 1 September 2013 to 28 February 2015, we conducted a prospective multi-centre observational cohort study of trauma patients in four Indian university hospitals, in three megacities, Kolkata, Mumbai and Delhi. All adult patients presenting to the casualty department with a history of injury and who were admitted to inpatient care were included. The primary outcome was in-hospital mortality within 30-days of admission. The sensitivity and specificity of each score to predict inpatient mortality within 30days was assessed by the areas under the receiver operating characteristic curve (AUC). Model fit for the performance of individual scoring systems was accomplished by using the Akaike Information criterion (AIC). RESULTS: In a registry of 8791 adult trauma patients, we had a cohort of 7197 patients eligible for the study. 4091 (56.8%)patients had all five scores available and was the sample for a complete case analysis. Over a 30-day period, the scores (AUC) was TRISS (0.82), RTS (0.81), KTS (0.74), NISS (0.65) and ISS (0.62). RTS was the most parsimonious model with the lowest AIC score. Considering overall mortality, both physiologic scores (RTS, KTS) had better discrimination and goodness-of-fit than ISS or NISS. The ability of all Injury scores to predict early mortality (24h) was better than late mortality (30day). CONCLUSION: On-admission physiological scores outperformed the more expensive anatomy-based ISS and NISS. The retrospective nature of ISS and TRISS score calculations and incomplete imaging in LMICs precludes its use in the casualty department of LMICs. They will remain useful for outcome comparison across trauma centres. Physiological scores like the RTS and KTS will be the practical score to use in casualty departments in the urban Indian setting, to predict early trauma mortality and improve triage.

Traumatic transfers: calibration is adversely affected when prediction models are transferred between trauma care contexts in India and the United States.

OBJECTIVE: We evaluated the transferability of prediction models between trauma care contexts in India and the United States and explored updating methods to adjust such models for new contexts. STUDY DESIGN AND SETTINGS: Using a combination of prospective cohort and registry data from 3,728 patients of Towards Improved Trauma Care Outcomes in India (TITCO) and from 18,756 patients of the US National Trauma Data Bank (NTDB), we derived models in one context and validated them in the other, assessing them for discrimination and calibration using systolic blood pressure, heart rate, and Glasgow coma scale as candidate predictors. RESULTS: Early mortality was 8% in the TITCO and 1-2% in the NTDB samples. Both models discriminated well, but the TITCO model overestimated the risk of mortality in NTDB patients, and the NTDB model underestimated the risk in TITCO patients. CONCLUSION: Transferability was good in terms of discrimination but poor in terms of calibration. It was possible to improve this miscalibration by updating the models' intercept. This updating method could be used in samples with as few as 25 events.

Ebola and indirect effects on health service function in sierra leone.

BACKGROUND: The indirect effects of the Ebola epidemic on health service function may be significant but is not known. The aim of this study was to quantify to what extent admission rates and surgery has changed at health facilities providing such care in Sierra Leone during the time of the Ebola epidemic. METHODS: Weekly data on facility inpatient admissions and surgery from admission and surgical theatre register books were retrospectively retrieved during September and October. 21 Community Health Officers enrolled in a surgical task-shifting program personally visited the facilities. The study period was January 6 (week 2) to October 12, (week 41) 2014. RESULTS: Data was retrieved from 40 out of 55 facilities. A total of 62,257 admissions and 12,124 major surgeries were registered for the study period. Total admissions in the week of the first Ebola case were 2,006, median 40 (IQR 20-76) compared to 883, median 12 (IQR 4-30) on the last week of the study. This equals a 70% drop in median number of admissions (p=0.005) between May and October. Total number of major surgeries fell from 342, median 6 (IQR 2-14) to 231, median 3 (IQR 0-6) in the same period, equal 50% reduction in median number of major surgeries (p=0.014). CONCLUSIONS: Inpatient health services have been severely affected by the Ebola outbreak. The dramatic documented decline in facility inpatient admissions and major surgery is likely to be an underestimation. Reestablishing such care is urgent and must be a priority.

Early hospital mortality among adult trauma patients significantly declined between 1998-2011: three single-centre cohorts from Mumbai, India.

BACKGROUND: Traumatic injury causes more than five million deaths each year of which about 90% occur in low- and middle-income countries (LMIC). Hospital trauma mortality has been significantly reduced in high-income countries, but to what extent similar results have been achieved in LMIC has not been studied in detail. Here, we assessed if early hospital mortality in patients with trauma has changed over time in an urban lower middle-income setting. METHODS: We conducted a retrospective study of patients admitted due to trauma in 1998, 2002, and 2011 to a large public hospital in Mumbai, India. Our outcome measure was early hospital mortality, defined as death between admission and 24-hours. We used multivariate logistic regression to assess the association between time and early hospital mortality, adjusting for patient case-mix. Injury severity was quantified using International Classification of Diseases-derived Injury Severity Score (ICISS). Major trauma was defined as ICISS<0.90. RESULTS: We analysed data on 4189 patients out of which 86.5% were males. A majority of patients were between 15 and 55 years old and 36.5% had major trauma. Overall early hospital mortality was 8.9% in 1998, 6.0% in 2002, and 8.1% in 2011. Among major trauma patients, early hospital mortality was 13.4%, in 1998, 11.3% in 2002, and 10.9% in 2011. Compared to trauma patients admitted in 1998, those admitted in 2011 had lower odds for early hospital mortality (OR = 0.56, 95% CI = 0.41-0.76) including those with major trauma (OR = 0.57, 95% CI = 0.41-0.78). CONCLUSIONS: We observed a significant reduction in early hospital mortality among patients with major trauma between 1998 and 2011. Improved survival was evident only after we adjusted for patient case-mix. This finding highlights the importance of risk-adjustment when studying longitudinal mortality trends.