INTRODUCTION:

Deep vein thrombosis is a condition that occurs when a blood clot forms in a vein deep inside the body which mainly affects the large veins in the lower leg and thigh. It is believed to be caused by altered physiologic mechanisms that are likely to occur with decreased mobility, surgery and traumatic injury.³When a clot breaks off and moves through the blood stream, it is called an emboli which can get stuck in the blood vessels in the brain, lungs, heart, or another area leading to severe damage. Risk for developing DVT can be assessed by well’s score. (Naghavi M, 2020)⁴

World Health Organization (WHO) 2022 released results from Phase I of the WHO Research in to Global Hazards of Travel (WRIGHT) project. Findings indicate that the risk of developing venous thromboembolism (VTE) approximately doubles after travel lasting four hours or more. However, the study points out that even with this increased risk, the absolute risk of developing VTE, if seated and immobile for more than four hours, remains relatively low at about 1 in 6000.The two most common manifestations of VTE are deep vein thrombosis and pulmonary embolism.⁵

In India it was reported that deep vein thrombosis (DVT) incidence rate ranges from 8% to 20%. In Maharashtra have reported incidence rate of DVT of lower limb was observed in age group between 16 years to 75 years. Deep vein thrombosis (DVT) affects 10% to 20%of normal medical patients, 20% to 50% of stroke patients and 80% of critically ill patients. Long-term post-thrombotic problems are predicted to affect up to 30% of DVT patients who are admitted to the hospital. (Khairy, 2022).⁶

Critically ill patients appeared to be at high risk of developing deep vein thrombosis during their ICU stay because they combine both general risk factors together with specific ICU risk factors of deep vein thrombosis, like sedation, immobilization, vasopressors or central venous catheter.⁷ Well’s criteria for DVT is a reliable clinical tool to assess the risk of DVT in ICU patients after 48 hours of admission. The Well’s tool enables us to reliably stratify patients into high DVT risk (>3), moderate DVT risk (1-2) and low DVT risk (< 1). (Foreman, 2021).⁸

Deep vein thrombosis can be prevented by either pharmacological intervention which includes anticoagulants and mechanical interventions which includes the use of compression stockings. Intermittent pneumatic compression devices are thought to reduce or prevent stasis through promotion of blood flow velocity and may decrease coagulation through fibrinolytic activity. As DVT is a life-threatening complication, staff nurses caring for patients must perform risk assessment and provide prophylaxis through mechanical devices to prevent it. (Vasan, 2020).⁹

The employment of appropriate prophylactic methods for DVT purely depends on a thorough patient assessment which in turn will influence the development of VTE. This assessment is primarily and essentially completed by nurses as they are the first point of contact of care. These assessment findings and score is utilised to communicate the risk to the consultants and employment of appropriate prophylaxis. (Levy, 2022).¹⁰ The investigators therefore felt the need to undertake an observational study to assess level of risk and preventive strategies of deep vein thrombosis among patients admitted in medical, surgical and cardiothoracic intensive care units of selected Hospital, Chennai.

PURPOSE:

The purpose of the study is to determine the the risk for deep vein thrombosis and the preventive strategies among patients admitted in critical care unit, Chennai.

NULL HYPOTHESES:

H1: There will be significant association between the background characteristics and risk for deep vein thrombosis among critical care patients.

H1: There will be significant association between the background characteristics and preventive strategies for deep vein thrombosis among critical care patients.

MATERIALS AND METHODS:

A cross sectional descriptive correlational research design was adopted for the study. The study was carried out on 50 samples of Critical Care Patients at Apollo Hospitals, Chennai After obtaining the setting permission and informed consent from participants, data was collected using validated tools such as background variable proforma of patients such as age, gender, religion, marital status, occupation, educational status, type of family and clinical variables of patients such as height, weight, BMI , Admitting services, Comorbidities, Length of Hospital stay and Lifestyle variables such as Smoking, Use of Alcohol Data was collected by interview method using questionnaire method. Wells criteria was used to assess the risk factors for DVT & checklist was used to assess the practice. The main data collection was done after determining feasibility and practicability by pilot study. The data was tabulated and analysed by using descriptive and inferential statistics.

RESULTS AND DISCUSSION:

Majority of the critical care patients were males (60%), moderate level workers (86%), married (92%), 46% were about graduates and 34% homemakers. Majority of the critical care patients were admitted MDCCU (50%) with cardiac problem (36%), cardiovascular comorbidities (64%) and were non alcoholics (92%) and non-smokers (96%).

The mean scores for each component of the continuous variables among critical care patients such as Age in years (60.86+2.40), BMI (24.46+1.48), length of hospital stay (8.5+11.04), Days in ICU (6.94+8.67), Prothrombin time (13.7+2.75), Partial thromboplastin time (30.29+8.43), International Normalized Ratio (1.27 +0.31), Bleeding time (4.54+1.71), Clotting time (10.9+ 3.21) and D Dimer (0.59+1.07).

The majority of the critical care patients had low level risk for development of deep vein thrombosis (70%), 28% of them had moderate risk and 2% of them are high risk respectively.

Majority of the critical care patients had inadequate practice 86% followed by 14% moderate practice and none had adequate practice regarding prevention of deep vein thrombosis.

Joseph (2019) conducted retrospective audit on patients with thromboembolism. Caprini thrombosis risk assessment scale was employed for evaluating the risk of DVT. Rudolph Virchow is recognized as the first person to link the development of VTE to the presence of at least 1 of 3 conditions: venous stasis, vascular injury and hypercoagulability. The use of a well-designed risk assessment tool that measures the total VTE risk for an individual patient likely will prove much more helpful when considering a specific patient’s need for prophylaxis and follow-up evaluation.

The Itemwise analysis of risk for Deep Vein Thrombosis such a presence of clinical manifestation (12%), other diagnosis less likely than Pulmonary Embolism (12%), Heart rate > 100(28%), Immobilization (40%), previous history of Deep Vein Thrombosis/Pulmonary Embolism (4%), hemoptysis (4), Malignancy (0) for Deep Vein Thrombosis among critical care patients projects the mean score of risk for Deep Vein Thrombosis (1.83+2.01) and the mean percentage (14.64%).

The mean score of preventive strategies for Deep Vein Thrombosis, such as Early ambulation (0.44+0.82), Foot end elevation (1.04+0.99), Sequential Compression Device (0.88+0.99), Use of Stocking (0.24+0.64) and administration of Heparin (0.52+0.87).

There was no significant association of risk for Deep Vein Thrombosis with selected demographic variables and critical care patients like Age, Gender, Marital status, Education, Occupation and Nature of work. In this regard the research hypothesis H1“There will be no association between the selected background variables and risk for Deep Vein Thrombosis among critical care patients” was rejected.

Elavally et al., (2020) was conducted a retrospective audit of in-service department files was to assess the intervention and outcome measures. The audit included the laptop assisted teaching, post-test knowledge of nurses on VTE and their compliance on VTE assessment. The approach was descriptive. The instruments used were a 10 item knowledge questionnaire and a 24 item VTE risk assessment tool. Descriptive and inferential statistical methods were used for data analysis. The result showed that the knowledge of staff nurses and risk assessment compliance was good. There was a positive correlation between compliance and knowledge among staff nurses.

There was no significant association of preventive strategies for Deep Vein Thrombosis with selected demographic variables and critical care patients like Age, Gender, Marital status, Education, Occupation and Nature of work. In this regard the research hypothesis H1 “There will be no association between the selected background variables and preventive strategies for deep vein thrombosis among critical care patients” was rejected.

Table 1: Frequency and Percentage Distribution of Background Variables of Critical Care Patients N=50

Background Variables	f	%
Age 20 to 40	6	12
41 to 60	15	30
60 above	29	58
Gender
Male	30	60
Female	20	40
Marital status
Married	46	92
Single	4	8
Widow
Separated
Educational qualification
No formal education	1	2
Primary education	6	12
Secondary education	20	40
Graduate	22	44
Post Graduate	1	2
Occupation
Home Maker	17	34
Unemployed	5	10
Unorganized labors	10	20
Private employee	5	10
Government employee	8	16
Retired	5	10
Type of work
Heavy	6	12
Moderate	43	86
Sedentary	1	2

Table 2: Frequency and Percentage Distribution of Clinical Variables of Critical Care Patients N=50

Clinical Variables
Health Status Variable	f	%
Admitting services
Medical ICU	4	8
Surgical ICU	12	24
Cardiac ICU	8	16
Orthopedic ICU	1	2
MDCCU	25	50
Comorbidities
Cardiovascular problems	32	64
Respiratory problems	18	36
Reason for Admission in CCU
Diabetes Mellitus	18	36
Respiratory problem	6	2
Cardiac problem	5	10
Neuro problem	1	2
Trauma problem	3	6
Others	17	34
Lifestyle variables
Habit of Smoking
Yes	2	4
No	48	96
Habit of alcohol
Yes	4	8
No	46	92

Table 3: Frequency and Percentage Distribution of level of Risk for Deep Vein Thrombosis among Critical Care Patients N = 50

Levels of risk for deep vein thrombosis	Score	f	%
High	>6.0	1	2
Moderate	2.0 to 6.0	14	28
Low	<2.0	35	70

Table 4: Frequency and Percentage Distribution of Preventive Strategies for Deep Vein Thrombosis among Critical Care Patients

N=50

Preventive strategies	Score	f	%
Healthy strategies	6 to10	0	0
Moderate strategies	6	7	14
Unhealthy strategies	0 to 6	43	86

Table 5: Itemwise Analysis of Risk for Deep Vein Thrombosis among Critical Care Patients N=50

Parameters of risk for Deep Vein Thrombosis	f	%
Clinical symptoms of DVT (leg swelling, pain with palpation)	6	12
Other diagnosis less likely than pulmonary embolism	6	12
Heart rate >100	14	28
Immobilization (>3 days) or surgery in the previous four weeks	20	40
Previous DVT/PE	2	4
Hemoptysis	2	4
Malignancy	-

Table 6: Mean and Standard deviation of Preventive Strategies for Deep Vein Thrombosis among Critical Care Patients N=50

Items	Obtainable score	Mean	SD	Mean %
Mechanical Modalities Early ambulation	2	0.44	0.82	22
Foot End Elevation	2	1.04	0.99	52
Sequential Compression Device	2	0.88	0.99	44
Stocking	2	0.24	0.64	12
Pharmacological Modalities Heparin	2	0.52	0.87	26
Total Score	10	3.12	4.31	31

Table 7: Association between Selected Background Variables and Risk for Deep Vein Thrombosis among Critical Care Patients N=50

Background Variables	Risk
Demographic variables	Up to mean	Above mean	Chi square	P value
Age in years
<60	15	6	0.03	0.85
>60	20	9	0.03	0.85
Gender
Male	22	8	0.39	0.53
Female	13	7	0.39	0.53
Marital status
Married	32	14	0.05 Yates = 0.1165	0.82
Unmarried	3	1	0.05 Yates = 0.1165	0.82
Educational Qualification
Educated	30	13	0.007 Yates = 0.1266	0.92
Uneducated	5	2	0.007 Yates = 0.1266	0.92
Occupation
Employed	22	6	2.22	0.13
Unemployed	13	9	2.22	0.13
Type of work
Heavy	4	2	0.03 Yates = 0.0812	0.84
Moderate	31	13	0.03 Yates = 0.0812	0.84

Table 8: Association between Selected Background Variables and Preventive Strategies for Deep Vein Thrombosis among Critical Care Patients N = 50

Background Variables	Preventive Strategies
Demographic variables	Up to mean	Above mean	Chi square	P value
Age in years
<60	10	11	0.27	0.59
>60	16	13	0.27	0.59
Gender
Male	14	16	0.85	0.35
Female	12	8	0.85	0.35
Marital status
Married	24	22	0.007	0.93
Unmarried	2	2	0.007	0.93
Educational Qualification
Educated	24	19	1.79	0.18
Uneducated	2	5	1.79	0.18
Occupation
Employed	13	15	0.79	0.37
Unemployed	13	9	0.79	0.37
Type of work
Heavy	5	1	2.36	0.12
Moderate	22	22	2.36	0.12

ACKNOWLEDGEMENT:

I would like to thank all the participants for supporting me to conduct this study. I would like to thank my research guide and clinical guide who helped me throughout the study. I would like to extend my heartfelt thanks for all who has directly or indirectly helped me during my study period.

CONFLICT OF INTEREST:

The author declares no conflict of interest

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Received on 16.04.2024 Revised on 09.08.2024

Accepted on 03.10.2024 Published on 08.03.2025

Available online from March 12, 2025

Res.J. Pharmacology and Pharmacodynamics.2025;17(1):8-12.

DOI: 10.52711/2321-5836.2025.00002

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