Spectrum of Occupational Injuries Presenting to the Emergency Department.

Dear Editor,

This study focused on occupational-related injuries with the objective of describing the demography of victims, the nature of occupation, areas of the body injured, severity of injuries in accordance with the New Injury Severity Score (NISS), management in emergency department (ED), and outcome of their hospital stay. According to section 2 (8) of the Indian constitution, the term “Employment injury” means a personal injury to an employee caused by accident or an occupational disease arising out of and in the course of his employment, whether the accident occurs, or the occupational disease is contracted within or outside the territories of India.[1] It is one of the leading causes of disability and death among employees that may results in poor economic status of the workers and their families. In addition to its adverse effects on the employee, it deteriorates the work productivity and the profit of the organization and the community.[234] Although prevention methods are available, many injuries still occur due to poor ergonomics, manual handling of heavy loads, misuse of equipment, general hazards, and inadequate safety training.[345] The severity of these injuries may vary from simple soft laceration to complex fractures, requiring a multidisciplinary team for management, where the ED physician plays an important role.[345]

Our study conducted in the ED of Christian Medical College describes the spectrum of injuries among various occupational sectors, the severity of injury based on the NISS, and outcome during the study period of 24 months (January 2017 to December 2018). The charts were reviewed, and the relevant details of history, clinical examination, laboratory, and radiological investigations were documented in the study form. Outcome of the patients from the ED with regard to admission, discharge, leave against medical advice (LAMA), and death were documented. The data were then analyzed using Statistical Package for the Social Sciences (SPSS) for Windows software released 2015, version 23.0, Armonk, New York. Some of the variables such as sex of the patient, occupation of the patient, and mode of injury were categorized and coded. A bivariate analysis was done to identify the relationship between these variables and the potential determinants. All possible determinants with P ≤ 0.05 in the bivariate analysis were used as candidates for multivariate logistic regression analysis to determine their significant association.

A total of 1,43,621 patients presented to the ED during the study period, of which 13,604 (9.47%) were trauma patients. Among these trauma patients, 603 (4.4%) patients presented with occupation-related injuries [Figure 1]. These patients' charts were screened and included into the study. Male predominance was observed as expected with 555 (92%) patients with a mean age of 35.4 (standard deviation [SD] 12.8) years. The triage priority was classified based on Glasgow Coma Scale (GCS), hemodynamic stability, and severity of injury. There were 76 (13%) victims categorized as priority 1 with NISS of 8 or more in 48 (63.2%) victims. NISS was eight or more in 48.7% (234 of 603) priority two patients and 18.1% (293 of 603) priority three victims. We noticed that approximately one-fifth of these cases were from small-scale industries, that is, 122 (20.2%) followed by construction sectors 105 (17.4%). Details of occupational sectors and mode of injury are given in Table 1. Approximately 19% (117) of patients sustained partial or complete amputation of upper limb digits, whereas 30 (5.0%) patients sustained degloving injury. Fractures and dislocations were seen in 36.8% (222) and 3% (18) of patients, respectively. The type of injuries sustained is shown in Figure 2. We noted that the upper limbs 426 (70.5%) were the most commonly involved body part of the body. Mild head injury (GCS 14–15) was seen in 56 (9.3%) patients, moderate head injury (GCS 9–13) was noted in 3 (0.5%) patients, and severe head injury (GCS ≤ 8) was noted in 2 (0.3%) patients. Details of the body part injured according to the triage priority levels are shown in Table 2. Bivariate and multivariate regression analyses for predictors of severity of injury based on NISS and between various indices are given in Table 3. Patients working in wood-related industries (adjusted odds ratio [OR]: 1.74 (1.04–2.93); P = 0.001) and those sustaining a sharp object injuries (adjusted OR: 1.45 (0.95–2.19); P = 0.082) had a higher  odds of sustaining severe injury as defined by NISS more than 8.

Figure 1

STROBE diagram

Table 1

Occupational sector and mode of injury

Variables	Frequency n=603 (%)
Occupational sectors
Small industries	122 (20.2)
Construction sectors	105 (17.4)
Agriculture sectors	98 (16.3)
Manufacturing sectors	93 (15.4)
Wood-related sectors	90 (14.9)
Transportation sectors	16 (2.7)
Electricity sectors	7 (1.1)
Unknown	72 (12.0)
Mode of injuries
Machine related	235 (39.0)
Sharp object at work	174 (28.9)
Heavy object at work	114 (18.9)
Fall from height	17 (2.8)
Electrical injuries	7 (1.2)
Burn injuries	29 (4.8)
Firecracker burst injuries	15 (2.4)
Cylinder and tyre burst injuries	10 (1.7)
Unknown	2 (0.3)

Figure 2

Pattern of injuries

Table 2

Triage priority level and regions of the body involved

Body parts involved	Priority 1 n =76 (13%)	Priority 2 n=234 (38%)	Priority 3 n=293 (49%)
Head face and neck	6 (7.9)	21 (9.0)	34 (11.6)
Thorax and abdomen	2 (2.6)	12 (5.1)	22 (7.5)
Spinal cord injury	1 (1.3)	1 (0.4)	6 (2.1)
Extremities--upper limbs	68 (89.4)	174 (74.4)	184 (62.8)
Extremities--lower limbs	5 (6.6)	35 (15.0)	71 (24.2)
Skin and soft-tissue injury	46 (60.5)	109 (46.6)	37 (12.6)

Table 3

Bivariate and multivariate logistic regression analysis of factors predicting severe trauma (NISS ≥8)

Variable	NISS > 8 Frequency (%)	NISS ≤ 8Frequency (%)	Bivariate analysis		Multivariate analysis
			P	Unadjusted OR (95% CI)	P	Adjusted OR (95% CI)
Male sex	203 (93)	354 (91.9)	0.603	1.19 (0.63-2.25)	Not analyzed	Not analyzed
Age <30 years	81 (37.2)	156 (40.5)	0.417	0.87 (0.62-1.22)	Not analyzed	Not analyzed
Machine-related industries	77 (35.3)	158 (41.0)	0.167	0.79 (0.56-1.11)	Not analyzed	Not analyzed
Agricultural sectors	32 (14.7)	66 (17.1)	0.431	0.83 (0.52-1.31)	Not analyzed	Not analyzed
Construction sectors	36 (16.5)	69 (17.9)	0.661	0.91 (0.58-1.41)	Not analyzed	Not analyzed
Sharp object	80 (36.7)	94 (24.4)	0.001	1.80 (1.25-2.57)	0.082	1.45 (0.95-2.19)
Wood-related work	47 (21.6)	43 (11.2)	0.001	2.19 (1.40-3.43)	0.037	1.74 (1.04-2.93)

The ED team alone treated and discharged 32 (5.3%) patients, whereas the remaining required evaluation and treatment by various trauma surgical teams. The trauma specialities that involved were hand and leprosy reconstruction surgery (HLRS) in 388 (64.3%) cases, orthopedics in 128 (21.2%) cases, plastic surgery in 44 (7.3%) cases, ear, nose, and throat (ENT) surgery in 18 (3.0%) cases, vascular surgery in 16 (2.9%) cases, neurosurgery in 16 (2.9%) cases, trauma-general surgery in 49 (8.1%), and spine surgery in 7 (1.2%) cases. Approximately, one-third of the total study population, that is, 205 (34%) required only minor emergency procedures such as wound wash, debridement, suturing, or nailing of the fractures in the minor theatre of the ED itself, whereas 223 (37%) patients required major surgical interventions in the operating room. One patient succumbed to the injury during resuscitation in the ED.

Occupational risk factors are responsible for 8.8% of the global burden of mortality due to unintentional injuries and 8.1% of disability adjusted life year (DALY).[5] The young mean age of our cohort with male predominance involving the potential bread earner of the families is an alarming factor. A significant proportion of patients presented with injuries involving the upper limbs (hand) being caught in machines, followed by injuries caused by sharp objects (axe, sickle, pickaxe, shovel, and spade). In most parts of India, farm operations are carried manually with hand-operated tools and equipment without any safety measures, thereby making them the main cause of nonfatal injuries. Although the profile of at-risk population has changed greatly over the past decade both qualitatively and quantitatively, the risk of occupational injury remains the same in small-scale industries. This is mainly because of urbanization and industrialization with labor-oriented markets, which depends on more automation and mechanization at workplace.[6]

Our study showed the severity of occupational injuries and the morbidity associated with them. We recommend identification of potential work-related hazards, injury-prone machinery, and unstable working conditions to prevent these injuries. Strict implementation of safety standards at all levels, that is, personal, administrative, and law enforcing levels, is the need of the hour.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.