| Literature DB >> 31673177 |
Rajesh Kumar Rohilla1, Sumit Kumar1, Roop Singh1, Ashish Devgan1, Hari Singh Meena1, Varun Arora2.
Abstract
BACKGROUND: Trauma causes a major burden on the health system and economy of the country. A better understanding of the epidemiology of trauma can be of great help in planning preventive and curative strategies.Entities:
Keywords: Demography; epidemiology; injury severity score; new injury severity score; orthopedic; road traffic accident; trauma
Year: 2019 PMID: 31673177 PMCID: PMC6804385 DOI: 10.4103/ortho.IJOrtho_161_19
Source DB: PubMed Journal: Indian J Orthop ISSN: 0019-5413 Impact factor: 1.251
Gender and age distribution in whole group and in various causes of trauma
| Age group (years) | Whole study group | RTA | Assault | Fall | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Male, | Female, | Total, | Male, | Female, | Total, | Male, | Female, | Total, | Male, | Female, | Total, | |
| Below 5 | 87 (2.1) | 1 (0.1) | 88 (1.8) | 84 (3.8) | 1 (0.3) | 85 (3.3) | 0 | 0 | 0 | 10 (0.82) | 4 (1.11) | 14 (0.89) |
| 5-14 | 383 (9.4) | 170 (22.7) | 553 (11.4) | 173 (7.9) | 17 (4.4) | 339 (13.1) | 4 (0.9) | 1 (1.2) | 5 (1) | 205 (16.90) | 31 (8.65) | 236 (15.02) |
| 15-19 | 419 (10.3) | 88 (11.7) | 507 (10.5) | 189 (8.6) | 85 (22) | 274 (10.6) | 10 (2.3) | 2 (2.3) | 12 (2.3) | 211 (17.39) | 36 (10.05) | 247 (15.72) |
| 20-24 | 625 (15.3) | 19 (2.5) | 644 (13.3) | 429 (19.5) | 11 (2.8) | 440 (17) | 6 (1.4) | 4 (4.7) | 10 (1.9) | 107 (8.82) | 25 (6.98) | 132 (8.40) |
| 25-44 | 1841 (45.1) | 198 (26.4) | 2039 (42.2) | 853 (38.8) | 104 (26.9) | 957 (37) | 331 (75.9) | 3 (3.5) | 334 (64) | 161 (13.27) | 168 (46.92) | 329 (20.94) |
| 45-64 | 673 (16.5) | 264 (35.2) | 937 (19.4) | 423 (19.2) | 166 (42.9) | 440 (17) | 82 (18.8) | 74 (86) | 156 (29.9) | 514 (42.37) | 89 (24.86) | 603 (38.38) |
| Above 64 | 56 (1.4) | 10 (1.3) | 66 (1.4) | 47 (2.1) | 3 (0.8) | 50 (1.9) | 3 (0.7) | 2 (2.3) | 5 (1) | 5 (0.41) | 5 (1.39) | 10 (0.63) |
| Total | 4084 | 750 | 4834 | 2198 | 387 | 2585 | 436 | 86 | 522 | 1213 | 358 | 1571 |
RTA=Road traffic accidents
Gender and age distribution in various causes of trauma
| Age group (years) | Machine injury | Railway track injury | Gunshot injury | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Male, | Female, | Total, | Male, | Female, | Total, | Male, | Female, | Total, | |
| Below 5 | 2 (1.36) | 1 (1.36) | 3 (1.36) | 0 | 0 | 0 | 0 | 0 | 0 |
| 5-14 | 9 (6.16) | 5 (6.84) | 14 (6.39) | 0 | 0 | 0 | 1 (7.14) | 0 | 1 (5.88) |
| 15-19 | 24 (16.43) | 13 (17.8) | 37 (16.89) | 1 (8.33) | 1 (14.28) | 2 (10.52) | 2 (14.28) | 0 | 2 (11.76) |
| 20-24 | 21 (14.38) | 9 (12.32) | 30 (13.69) | 1 (8.33) | 1 (14.28) | 2 (10.52) | 3 (21.42) | 1 (33.33) | 4 (23.52) |
| 25-44 | 63 (43.15) | 30 (41.09) | 93 (42.46) | 5 (41.66) | 3 (42.85) | 8 (42.8) | 7 (50) | 1 (33.33) | 8 (47.02) |
| 45-64 | 19 (13.01) | 14 (19.17) | 33 (15.06) | 2 (16.66) | 1 (14.28) | 3 (15.78) | 1 (7.14) | 1 (33.33) | 2 (11.76) |
| Above 64 | 8 (5.47) | 1 (1.36) | 9 (4.1) | 3 (25) | 1 (14.28) | 4 (21.05) | 0 | 0 | 0 |
| Total | 146 | 73 | 219 | 12 | 7 | 19 | 14 | 3 | 17 |
Distribution of patients in study according to different criteria
| Educational status | |
| Graduate | 1774 (36.69) |
| Up to matriculate | 1471 (30.43) |
| Illiterate | 1121 (23.2) |
| Postgraduate | 468 (9.7) |
| Total | 4834 |
| Occupational status | |
| Professional | 1577 (32.62) |
| Student | 1146 (23.7) |
| Laborer | 764 (15.8) |
| Farmer | 540 (11.17) |
| Homemaker | 464 (9.6) |
| Unemployed | 343 (7.1) |
| Total | 4834 |
| Mode of injury | |
| RTA | 2585 (53.5) |
| Fall | 1472 (30.5) |
| Physical assault | 522 (10.8) |
| Machine injury | 219 (4.5) |
| Railway track accident | 19 (0.4) |
| Gun shot | 17 (0.4) |
| Total | 4834 |
| Accident-causing vehicle | |
| Two wheeler | 1216 (44.9) |
| Car | 497 (18.35) |
| Truck | 311 (11.5) |
| Bus | 294 (10.85) |
| Auto-rickshaw | 267 (9.8) |
| Tractor | 87 (3.2) |
| Train | 36 (1.32) |
| Total | 2708 |
RTA=Road traffic accidents
Distribution of patients in study according to different criteria
| Yes, | No, | Total | |
|---|---|---|---|
| BPL | 857 (17.7) | 3977 (82.3) | 4834 |
| Time lapsed >12 h | 1568 (32.4) | 3266 (67.6) | 4834 |
| MLC | 1434 (29.7) | 3400 (70.3) | 4834 |
| Reached by ambulance | 1417 (29.3) | 3417 (70.7) | 4834 |
| Vitals unstable | 180 (3.72) | 4654 (96.28) | 4834 |
| Prehospital care | 175 (3.6) | 4659 (96.4) | 4834 |
| Influence of alcohol | 785 (16.23) | 4049 (83.77) | 4834 |
BPL=Below poverty line, MLC=Medico-legal case
Distribution of patients in study according to different criteria
| Site of accident | |
|---|---|
| City road | 1592 (32.93) |
| Not specified | 668 (13.81) |
| Village road | 544 (11.25) |
| House | 465 (9.62) |
| Farm | 432 (8.93) |
| Highway | 401 (8.29) |
| Workplace | 383 (7.92) |
| Other roads | 349 (7.2) |
| Total | 4834 |
| Associated injury | |
| Head injury | 1250 (25.85) |
| Chest injury | 512 (10.6) |
| Pelvic injury | 350 (7.24) |
| Abdominal injury | 150 (3.10) |
| Dorsolumbar spine injury | 145 (3) |
| Cervical spine injury | 89 (1.84) |
| Genitourinary injury | 10 (0.2) |
| None | 2328 (48.15) |
| Total | 4834 |
| Body region affected | |
| Head | 1250 (25.85) |
| Shoulder and arm | 707 (14.6) |
| Leg and ankle | 660 (13.65) |
| Forearm and elbow | 550 (11.37) |
| Foot | 500 (10.34) |
| Chest | 512 (10.06) |
| Hand and wrist | 470 (9.72) |
| Thigh and hip | 200 (4.13) |
| Abdomen | 150 (3.1) |
| Dorsolumbar spine | 145 (3) |
| Pelvis | 135 (2.79) |
| Cervical spine | 86 (1.84) |
| Exact diagnosis (fractures) | |
| Hand and carpals | 470 (9.72) |
| Radius | 375 (7.57) |
| Clavicle | 330 (6.82) |
| Tibia | 290 (5.99) |
| Fibula | 263 (5.44) |
| Ulna | 259 (5.35) |
| Femur | 200 (4.13) |
| Foot | 196 (4.05) |
| Humerus | 165 (3.41) |
| Dorsolumbar spine | 145 (3) |
| Acetabulum | 135 (2.79) |
| Cervical spine | 89 (1.84) |
Injury severity score and new injury severity score scores in different category of patients
| Not wearing helmet/seat belt (total=1638), | Wearing helmet/seat belt (total=386), | Under influence of alcohol (total=785), | Not under influence of alcohol (total=4049), | |
|---|---|---|---|---|
| NISS | ||||
| 0-5 | 950 (58) | 231 (59.9) | 487 (62.14) | 2720 (67.2) |
| 6-10 | 278 (17) | 80 (20.6) | 94 (11.9) | 648 (16) |
| 11-15 | 234 (14.3) | 46 (12) | 96 (12.31) | 344 (8.5) |
| 16-20 | 156 (9.5) | 26 (6.7) | 97 (12.35) | 304 (7.5) |
| 21-25 | 20 (1.2) | 3 (0.8) | 11 (1.3) | 33 (0.8) |
| ISS | ||||
| 0 | 372 (22.7) | 85 (21.9) | 189 (24) | 1182 (29.2) |
| 4 | 760 (46.4) | 172 (44.5) | 377 (48.1) | 2190 (54.1) |
| 9 | 311 (19) | 94 (24.3) | 113 (14.45) | 396 (9.8) |
| 16 | 177 (10.8) | 33 (8.7) | 97 (12.35) | 252 (6.2) |
| 25 | 18 (1.1) | 2 (0.6) | 9 (1.1) | 29 (0.7) |
| Associated injury | 693 (42.3) | 105 (27.1) | 246 (31.3) | 996 (24.6) |
| Deaths | 48 (2.93) | 7 (1.81) | 61 (7.77) | 46 (1.13) |
NISS=New injury severity score, ISS=Injury severity score