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Lead Investigators: Mohit Bhandari, McMaster University, Canada

Parag Sancheti, Sancheti Institute, Pune India

Methods and Coordinating- McMaster University Project Officers: Clary Foote MD, Mangesh Shende

Data Management: Robert Ozolins, Clary Foote MD

Statistics: Joseph Beyene PhD, Binod Neupene PhD

Investigators Parag Sancheti, Steve Rocha, Chetan Pradhan,

Sancheti Institute of Orthopaedics, Pune, India

Vijay Shetty & Chintan Hegde, Hiranandani Hospital, Mumbai, India

Prakash Kotwal, All Indian Institute Medical Sciences (AIIMS), Delhi, India

Lakshminarayan, Sri Ramchandra University, Chennai, India

Anil Jain, Guru Teg Bahadur (GTB) Hospital, Delhi, India

Mandeep Dhillon & Sarvdeep Dhatt, Post Graduate Institute of Medical Education

and Research (PGIMER), Chandigarh, India

Hitesh Gopalan, Medical Trust Hospital, Cochin, India

Bobby John, Christian Medical College (CMC), Ludhiana, India

Shantharam Shetty, Tejasvini Hospital, Mangalore, India

Gurava Reddy, Sunshine Hospital, Hyderabad, India

Avtar Singh, Amandeep Hospital, Amritsar, India

Rajasekaran Shanmuganathan, Ganga Hospital, Coimbatore, India

Abhay Srivastava, Jabalpur Hospital and Research Centre, Jabalpur, India

Shrath Rao, University Hospital, Manipal, India

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Funding and Disclosures

Surgical Associates Foundation, McMaster University

Regional Medical Associates, McMaster University

HHS Trauma Research Fund, Hamilton, Ontario

The authors have no financial interest, arrangement or affiliation with one or more organizations that could be perceived as a direct/indirect conflict of interest in the content of this presentation.

The Problem Burden of Trauma

5.8 million people die per year1

10% of world’s deaths

UN report: 3rd largest killer by 20202

Disability > Death

1. Rodgers, A., Ezzati, M., Vander Hoorn, S., Lopez, A. D., Lin, R. B., & Murray, C. J. (2004). Distribution of major health risks: findings from the Global Burden of Disease study. PLoS Med, 1(1): e27.

2. WHO (2010). Injury Prevention and Safety Promotion - Urbanization and Health, Health in South East Asia, Vol. 3: 1-2.

The Problem Burden of Trauma

5.8 million people die per year1

10% of world’s deaths

UN report: 3rd largest killer by 20202

Disability > Death

1. Rodgers, A., Ezzati, M., Vander Hoorn, S., Lopez, A. D., Lin, R. B., & Murray, C. J. (2004). Distribution of major health risks: findings from the Global Burden of Disease study. PLoS Med, 1(1): e27.

2. WHO (2010). Injury Prevention and Safety Promotion - Urbanization and Health, Health in South East Asia, Vol. 3: 1-2.

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The EpicentreIndia

648,000 Major traumas

334,000 Accidental Deaths

Indian Bureau of Accidental Deaths Report 2009

1. WHO (2007). Injury Prevention and Care in the South-East Asia Region, Regional Meeting of National Programme Managers: 1, 12. Nonthaburi, Thailand: Sirindhorn National Medical Rehabilitation.

2. Bureau of Indian Accidental Deaths and Suicide. 2009. Delhi, India..

1. Bureau of Indian Accidental Deaths and Suicide. 2009. Delhi, India.. 

0

50000

100000

150000

200000

250000

300000

350000

400000

1967 1977 1987 1997 2000 2004 2005 2006 2007 2009

Death

s

Accidental Deaths in India

1. WHO, World Accident Resport 2013. 

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Road Traffic Safety Decade

2011-2021

1.3 Million deaths (90% Low Income countries)

51 Million major injuries

WHO and United Nations

Over 100 participating nations

Indian Roads

RTA 7.4 billion dollars

Second highest 30 per 100,000

Burden of Fractures

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The ProblemDeveloped nations data established

Developing Poor data on trauma

?Musculoskeletal trauma

THE SOLUTION :INORMUS

Large observational cohort study in India

across the entire subcontinent

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RationaleExplore determinants of outcomes

Precise estimates of the growing burden of fractures

Understand the contribution of specific injury mechanisms

Identify potential discrepancies between hospital systems (e.g. timing of care, outcomes)

Specific AimsPrimary

Predictors of Mortality

Secondary (Descriptive)

Access to primary trauma care

Time to orthopaedic care

Methods

Recruitment of all patients presenting to emergency departments of hospitals in India with an orthopaedic injury over an 8 week period.

Study sample: 4000 patients

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Participating Hospitals

Eligibility

Skeletally mature

Fracture or dislocation (limbs, pelvis, or spine)

Hospital Types

Public

6 Hospitals

No medical Coverage

Commonly wards overcrowded

Conservative Management

Private

8 Hospitals

State of the art care

Mostly insured patients

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Sample SizeLogistic regression

Outcome: Death

Estimated Proportion: 2.5%

Model: 10 variables

Target = 4000 patients

Results

INORMUS exceeded defined sample size with 4612 patients

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5951 Screened

4822 Included

2400 Included in Analysis

2259 Included in Analysis

-392 skeletally immature

-737 minor injuries

2462 Public 2360 Private

16 missing fracture data

98 missing fracture

data

4612 Total

46 missing outcome data

3 missing outcome

data

Patients (n= 4612)Characteristic All Patients

Age (Yr)Mean ± Std

40.8 ± 16.9

Male 68.3%

Poverty* 8.7%

Injury locationRoad (%)

59.1%

MechanismMotorcycle 31.7%

Fracture 97.8%Open Fracture 15.0%

* Governmental Standards < 1000 USD/Year/family

Ambulance 30.1%

2/3 trauma patients transported by vehicles other than ambulances

Nonorthopedic injuries

Head injury 10.3%

Chest 9.6%

Abdomen 1.7%

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Orthopedic Injuries

Fracture 97.8%Multiple fractures 18.7%

Open fractures 15.1%Multiple open 2%

Open Fractures (n=707)

Grade

I 22.4% II 31.9%III 45.9%IIIa 15.4%IIIb 17.1%IIIc 13.3%

Time to Care Injury to admission > 24 hoursAll 18% (95% CI 16-20%)

Open 12% (95% CI 9-15%)

Delayed stabilization > 3 days

18% (95% CI 17-19%)

Delayed irrigation & debridement >12 hours (n=707)

22% (95% CI 19 - 25%)

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ComplicationsOutcome Total

Mortality  1.7%, 95% CI: 1.4‐2.2%

Unplanned reoperation 6.0%95% CI: 5.4‐6.7%

Infection  6.1%95% CI: 5.6‐7.0%

Characteristic Rich Upper middle class

Lower middle Class 

Poor p‐value

N 646 1050 1476 1103

Age(mean ± Std) 43.7 ± 17.7 41.2 ± 16.8 40.7 ± 16.7 38.9 ± 16.2 <0.001

Injury PlaceRoad/Street 377 (58.4%) 629 (59.9%) 881 (59.7%) 662 (60.0%) 0.91

Time from injury to hospital (hours) †< 24 hours24 – 72 hours> 72 hours

541 (83.6%)94 (14.6%)10 (1.5%)

878 (84.3%)118 (11.3%)46 (4.4%)

1241 (84.2%)154 (10.5%)78 (5.3%)

879 (79.7%)140 (12.7%)84 (7.6%)

0.02

Open Fracture 80 (12.4%) 132 (12.6%) 217 (14.7%) 232 (21.0%) <0.001

Time to irrigation and debridement ††< 6 hours 7‐12 hours13‐24 hours25‐48 hours 48 hours

50 (70.4%)12 (16.9%)9 (12.7%)00

85 (70.8%)18 (15.0%)10 (8.3%)4 (3.3%)3 (2.5%)

110 (55.0%)40 (20.0%)35 (17.5%)7 (3.5%)8 (4.0%)

107 (51.4%)38 (18.3%)45 (21.6%)12 (5.8%)6 (2.9%)

0.02

Outcomes at 30 days

Infection 26 (4.0%) 63 (6.0%) 95 (6.4%) 92 (8.3%) 0.004

20%

30%

Characteristic Road Accidents Other Mechanisms p-value

N 2742 (59.5%) 1870 (40.5%)

Age (years)Mean

38.0 ± 14.4 45.2 ± 19.2 <0.001

Gender (Male) 2071 (75.5%) 1087 (58.1%) <0.001

Number of fractures Dislocation only 1234 or more

42 (1.5%)2039 (74.4%)524 (19.1%)101 (3.7%)36 (1.3%)

56 (3.0%)1607 (85.9%)171 (9.1%)26 (1.4%)10 (0.5%)

<0.001

Open Fracture 568 (20.7%) 139 (7.4%) <0.001

Time from injury to hospital (hours) †< 24 hours24 – 72 hours> 72 hours

2315 (84.8%)293 (10.7%)123 (4.5%)

1451 (78.8%)253 (13.7%)138 (7.5%)

<0.001

Outcomes at 30 days

Mortality 58 (2.1%) 19 (1.0%) 0.02

25%

15%

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Mortality: Rates & PredictorsCharacteristic Other Mechanisms   Road Accidents p value

Unadjusted mortality rate

10.0 21.0 0.005

Mortality rate adjusted for risk factors †

17.0OR 1.0

35.2 (20.5 – 60.6)OR 2.1 (1.2 – 3.6) 

0.008

Mortality rate adjusted for risk factors and orthopedic injury severity*

3.0OR 1.0

4.1 (2.3 – 6.9)OR 1.4 (0.8 – 2.4)

0.27

Mortality rate adjusted for nonorthopaedic injury‡

3.0OR 1.0

3.6 (2.1 ‐ 6.4)OR 1.2 (0.7 – 2.1) 

0.51

Mortality rate adjusted for treatment factors§

0.01OR 1.0

0.01 (0.0 – 0.02)OR 1.1 (0.6 – 2.0)

0.75

Strength & WeaknessesWeaknessesPoor patients

Included hospitals

StrengthsRobust sample

Public/Private

Minimal data loss

Key FindingsA road traffic epidemic of MSK trauma

Delayed hospital arrivals are common

SES status predicts open fracture care

Mortality is predicted by:

Severity of orthopaedic and nonorthopaedic

Access to care variables

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Global INORMUS Fracture Study

India Recruited extend to 10,000patients

Expansion of INORMUS into Latin America, China, Africa towards global target: 30,000 patients

Partners: IGOT-UCSF for Latin America

Thank you ! Join us as an Investigator !

inormusinternational@gmail.com