|Year : 2021 | Volume
| Issue : 3 | Page : 113-117
Risk factors associated with complicated alcohol withdrawal syndrome
Navdeep Banyal1, Harpreet Singh Dhillon2, Shibu Sasidharan3
1 Department of Psychiatry, Command Hospital, Eastern Command, Kolkata, West Bengal, India
2 Department of Psychiatry, Command Hospital, Chandimandir, Haryana, India
3 Department of Anaesthesiology and Critical Care, Command Hospital, Western Command, Chandimandir, Haryana, India
|Date of Submission||22-Jul-2021|
|Date of Decision||10-Sep-2021|
|Date of Acceptance||16-Nov-2021|
|Date of Web Publication||15-Jun-2022|
Harpreet Singh Dhillon
Department of Psychiatry, Command Hospital, Western Command, Chandimandir, Haryana
Source of Support: None, Conflict of Interest: None
Background: Alcohol withdrawal syndrome (AWS) is a frequent presentation in patients with alcohol dependence syndrome. Complicated alcohol withdrawal state (i.e., delirium and/or convulsions) is the most severe form with significant morbidity and mortality if left untreated. Therefore, it is imperative to identify the risk factors associated with complicated AWS for early diagnosis and swift management.
Materials and Methods: This study utilized a cross sectional design in a tertiary care center on 60 patients to identify the risk factors associated with complicated alcohol withdrawal. The data collected were subsequently subjected to statistical analysis with appropriate tests (Pearson Chi-square test, t-test).
Results: Out of the 60 patients, 30 developed complicated AWS. Amongst the demographic variables, patients with education <10th standard, unemployment and history of delirium tremens were found to be significant predictors of complicated AWS. Patients with complicated AWS consumed higher mean ± standard deviation (19.33 ± 1.77 vs. 11.87 ± 1.17) units of alcohol per day (P < 0.001). The duration of alcohol withdrawal lasted for 7.13 ± 4.17 days in complicated AWS compared to 5.23 ± 2.70 days in uncomplicated (P = 0.041). Tacycardia (P = 0.001), respiratory rate (P = 0.001), low platelet count (P < 0.001) and higher Erythrocyte sedimentaion rate (P < 0.001) were also found to be significant predictors of complicated AWS. Serum gamma-glutamyl transferase GGT values were higher in complicated AWS but the difference was not statistically significant.
Conclusion: This study found lower education, unemployment, history of delirium tremens, higher units of alcohol consumed per day, tacycardia, higher respiratory rate, lower platelet count and higher erythrocyte sedimentaion rate as significant predictors of complicated AWS.
Keywords: Alcohol dependence, complicated alcohol withdrawal syndrome, delirium tremens, risk factors
|How to cite this article:|
Banyal N, Dhillon HS, Sasidharan S. Risk factors associated with complicated alcohol withdrawal syndrome. J Med Soc 2021;35:113-7
| Introduction|| |
The latest Global Status Report on Alcohol and Health (2014) reported that 38.3% of the world population as current drinkers. The worldwide prevalence of current Alcohol Use Disorders is up to 14%. Alcohol withdrawal syndrome (AWS) is a frequent presentation in patients with alcohol dependence syndrome and complicated alcohol withdrawal state (ie., delirium and with or without convulsions) is the most severe form. There is a wide variation in the prevalence of complicated AWS ranging from 05 to 20%. Untreated complicated AWS carries a mortality rate as high as 20%, although prompt detection of risk factors along with appropriate management reduces mortality to <1%. However, in an Indian study among patients admitted to medico-surgical wards reported 13% mortality, which is much higher than the existing literature and could be explained by the presence of co-morbidities. The usual causes of death in complicated AWS are hyperthermia, cardiac arrhythmias, complications of withdrawal seizures, or concomitant medical disorders.
Complicated AWS usually develops 48–72 h after the cessation of heavy drinking. The first symptom to appear in alcohol withdrawal is tremor (approx. 06 h after last drink), followed by palpitations and less frequently hallucinations at 12–24 h. The next major symptom is the alcohol withdrawal seizure, which is generally a grand mal type and can emerge any time after 24 h. Delirium tremens appear anytime after 48–72 h and can lead to significant morbidity if left untreated. This timeline for occurrence of symptoms of alcohol withdrawal has to be understood as it provides the health care providers with window of opportunity to halt its progression to complicated AWS. Therefore, it is imperative to identify the risk factors associated with AWS. The available literature documents various predisposing risk factors for complicated AWS e.g., advanced age of the patient, amount and duration of recent alcohol intake, history of withdrawal seizures/delirium tremens, abnormal liver function, co-existing infection, electrolyte abnormalities (e.g. hypokalemia, hypophosphatemia, hypomagnesemia, high blood urea nitrogen), raised mean corpuscular volume and carbohydrate deficient transferrin, low platelets, raised serum creatine phosphokinase levels or medical problems., This study was planned with the aim to assess early predictors of complicated AWS.
| Materials and Methods|| |
A cross-sectional, observational study was planned at the Department of Psychiatry in a tertiary care hospital. Ethics committee approval was obtained for the study. The study population included males between 18 and 60 years of age who fulfilled the International Classification of Diseases (ICD-10) diagnostic criteria for alcohol dependence syndrome and were currently in the state of alcohol withdrawal at the time of admission. Patients not consenting to the study or having relatives who did not give consent to the patients' participation in the study, with pre-existing medical or surgical comorbidities, and with other psychiatric disorders were excluded from the study. Confidentiality was assured and written informed consent was obtained from the subjects. Enrolment of cases was done after applying the inclusion and exclusion criteria. A total of 78 consecutive cases of alcohol dependence syndrome in alcohol withdrawal state admitted to a tertiary care hospital psychiatry ward were taken up for the study. Eighteen patients were excluded due to comorbid medical and psychiatric conditions the remaining 60 were included. The patients were divided into two groups; Group A included patients who were diagnosed with complicated alcohol withdrawal (ie, delirium and with or without convulsions) and Group B included uncomplicated alcohol withdrawal patients, as per the ICD-10 diagnostic criteria. Baseline demographic data of cases along with relevant investigations were entered in semi-structured socio-demographic and clinical datasheets. Amount of alcohol was calculated as per the type of spirit namely 30 ml of rum/whiskey/vodka/brandy (volume/volume alcohol content of 42.7%) contains approximately 10 g of alcohol (01 unit). The patients' demographic variables, detailed history of alcohol intake, present complications, history of complications, withdrawal features, drinking pattern, last drink, history of any other substance abuse, history of abstinence, treatment received for complications in the past, any medical or surgical illness, family history of dependence, and alcohol-related death (if any) were noted. The data collected in Groups A and B were subjected to statistical analysis with appropriate tests. (Pearson Chi-square test, t-test and Software The Statistical software IBM SPSS statistics 20.0 (IBM Corporation, Armonk, NY, USA) version were used for analysis).
| Results|| |
The demographic and alcohol related history is compared in [Table 1]. Out of the 60 patients, 30 developed complicated AWS. Amongst the demographic variables, patients with education <10th standard, unemployment and history of delirium tremens were found to have significantly higher percentage of complicated AWS. The 02 groups were comparable with respect to remaining socio-demographic variables [Table 1].
[Table 2] represents the comparison of clinical variables between complicated and uncomplicated AWS. Patients with complicated AWS consumed mean ± standard deviation 19.33 ± 1.77 units of alcohol per day compared to 11.87 ± 1.17 units per day in uncomplicated AWS (P < 0.001). The duration of alcohol withdrawal lasted for 7.13 ± 4.17 days in complicated AWS compared to 5.23 ± 2.70 days in uncomplicated (P = 0.041). Tacycardia (P = 0.001) and respiratory rate (P = 0.001) was also found to be significantly higher in patients with complicated AWS.
The comparison of biochemical parameters between the complicated and uncomplicated AWS is shown in [Table 3]. Patients with complicated AWS had significantly lower platelet count (P < 0.001) and higher Erythrocyte sedimentaion rate (P < 0.001). Serum gamma-glutamyl transferase values were higher in complicated AWS but the difference was not statistically significant.
| Discussion|| |
The present study attempted to identify socio-demographic, clinical and biochemical factors, which are predictive of a complicated AWS (alcohol withdrawal seizures and/or delirium tremens). Complicated AWS is associated with significant morbidity and mortality and hence early identification and pharmacological intervention will help in reducing the same.
The current study found history of delirium tremens to be significantly predictive of complicated AWS. The frequency of complicated AWS was found to be higher in patients with history of alcohol withdrawal seizure, although the difference was not significant. These findings are consistent with a recent systematic review in which history of withdrawal seizures during prior alcohol cessation episodes appeared to be less useful in predicting risk of complicated AWS than a history of delirium tremens. The pathophysiological basis of predicting complicated AWS in future can be explained by the phenomenon of 'kindling'. Kindling is a process of sensitization and enhanced neuronal excitability, which happens after repeated episodes of alcohol withdrawals. The cumulative excitotoxicity due to repeated kindling could explain the development of complicated AWS.
Unemployment and lesser education were also significantly predictive of complicated AWS consistent with previous studies. This could be explained by the lack of awareness and unregulated consumption pattern of non-standardized cheap country liquor amongst the unemployed and less educated. Schnohr et al., reported a relationship between education level and substance abuse and stated that individuals with low levels of educations often suffer from heavy dependence on smoking, drinking, physical inactivity and obesity. Another significant predictor of complicated AWS was the maximum units of alcohol consumed per day. The group with complicated AWS consumed 19.33 (±1.77) units compared to 11.87 (±1.17) in the uncomplicted group (P < 0.001). These findings are in consonance with previous studies., The underlying pathophysiology is that excessive quantities of alcohol consumption disrupt the neuronal stability, up-regulates the N-methyl-D- aspartate receptors causing neuronal hyperexcitability and greater vulnerability for development of delirium and lowering of seizure threshold.
The age of the patients was not a significant factor in predicting the complicated AWS in current study. This is in accordance with a number of previous studies, which found no association between age and complicated AWS., However, Lukan et al. and Bower et al. reported that higher age could be a significant risk factor for complicated AWS possibly due to longer duration and higher amount of alcohol consumption along with presence of co-morbid medical conditions., Patients in the current study were relatively younger without any significant difference in age between the 02 groups (P = 0.094).
Tachycardia is a hallmark of autonomic excitability and was found to be significant predictors of complicated AWS in the current study. This is in agreement with a systematic review which found that heart rate had a very small effect size for identifying groups of patients more likely to have severe alcohol withdrawal.
Among the biochemical parameters, low platelet counts and higher erythrocyte sedimentation rate (ESR) were found to be significant predictors of complicated withdrawal in the current study. The association between thrombocytopenia and complicated AWS was consistent with a recent meta-analysis of 15 studies and previous studies. ,, ESR is an inflammatory marker and higher ESR was positively associated with complicated AWS. These findings were however contrary to a recent study which reported negative association between heavy alcohol consumption and ESR.
The study had limitations of being a cross sectional study with a relatively smaller sample size of male participants only. A multicenter prospective study with a larger sample size involving patients of both sexes can help prepare the robust guidelines to evaluate early predictors.
| Conclusion|| |
Complicated alcohol withdrawal is associated with significant morbidity and mortality and reliable early predictors can considerably reduce the same with early diagnosis and swift management. This study found lower education, unemployment, history of delirium tremens, higher units of alcohol consumed per day, tacycardia, higher respiratory rate, lower platelet count and higher erythrocyte sedimentaion rate as significant predictors of complicated AWS.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organization. Global Status Report on Alcohol and Health 2018. Geneva Switzerland: World Health Organization; 2019.
Poznyak V, Fleischmann A, Rekve D, Rylett M, Rehm J, Gmel G. The World Health Organization's global monitoring system on alcohol and health. Alcohol Res 2014;35:244.
Eyer F, Schuster T, Felgenhauer N, Pfab R, Strubel T, Saugel B, et al
. Risk assessment of moderate to severe alcohol withdrawal – Predictors for seizures and delirium tremens in the course of withdrawal. Alcohol Alcohol 2011;46:427-33.
Wright T, Myrick H, Henderson S, Peters H, Malcolm R. Risk factors for delirium tremens: A retrospective chart review. Am J Addict 2006;15:213-9.
Grover S, Sharma A, Kate N, Mattoo SK, Basu D, Chakrabarti S, et al
. Symptom profile and outcome of delirium associated with alcohol withdrawal syndrome: A study from India. Am J Addict 2013;22:503-9.
Schuckit MA. Recognition and management of withdrawal delirium (delirium tremens). N Engl J Med 2014;371:2109-13.
Perälä J, Kuoppasalmi K, Pirkola S, Härkänen T, Saarni S, Tuulio-Henriksson A, et al
. Alcohol-induced psychotic disorder and delirium in the general population. Br J Psychiatry 2010;197:200-6.
Muncie HL Jr., Yasinian Y, Oge' L. Outpatient management of alcohol withdrawal syndrome. Am Fam Physician 2013;88:589-95.
Chandini S, Sequeira AZ, Mathai PJ. Factors associated with delirium tremens: A retrospective chart study. Muller J Med Sci Res 2013;4:86. [Full text]
Malik R, Dhillon HS, Sahu VK, Sasidharan S, Dhillon GK. Study of relationship between serum creatine phosphokinase levels with severity of alcohol withdrawal. Arch Ment Health 2021;22:63. [Full text]
Wood E, Albarqouni L, Tkachuk S, Green CJ, Ahamad K, Nolan S, et al
. Will this hospitalized patient develop severe alcohol withdrawal syndrome?: The rational clinical examination systematic review. JAMA 2018;320:825-33.
Reoux JP, Saxon AJ, Malte CA, Baer JS, Sloan KL. Divalproex sodium in alcohol withdrawal: A randomized double-blind placebo-controlled clinical trial. Alcohol Clin Exp Res 2001;25:1324-9.
Monte-Secades R, Blanco-Soto M, Díaz-Peromingo JA, Sanvisens-Bergé A, Martín-González MC, Barbosa A, et al
. Epidemiological and sociodemographic factors associated with complicated alcohol withdrawal syndrome. Rev Clin Esp (Barc) 2017;217:381-6.
Schnohr C, Højbjerre L, Riegels M, Ledet L, Larsen T, Schultz-Larsen K, et al
. Does educational level influence the effects of smoking, alcohol, physical activity, and obesity on mortality? A prospective population study. Scand J Public Health 2004;32:250-6.
Sarkar S, Choudhury S, Ezhumalai G, Konthoujam J. Risk factors for the development of delirium in alcohol dependence syndrome: Clinical and neurobiological implications. Indian J Psychiatry 2017;59:300-5.
] [Full text]
Monte R, Rabuñal R, Casariego E, Bal M, Pértega S. Risk factors for delirium tremens in patients with alcohol withdrawal syndrome in a hospital setting. Eur J Intern Med 2009;20:690-4.
Lechtenberg R, Worner TM. Total ethanol consumption as a seizure risk factor in alcoholics. Acta Neurol Scand 1992;85:90-4.
Lee JH, Jang MK, Lee JY, Kim SM, Kim KH, Park JY, et al
. Clinical predictors for delirium tremens in alcohol dependence. J Gastroenterol Hepatol 2005;20:1833-7.
Lukan JK, Reed DN Jr., Looney SW, Spain DA, Blondell RD. Risk factors for delirium tremens in trauma patients. J Trauma Acute Care Surg 2002;53:901-6.
Brower KJ, Mudd S, Blow FC, Young JP, Hill EM. Severity and treatment of alcohol withdrawal in elderly versus younger patients. Alcohol Clin Exp Res 1994;18:196-201.
Goodson CM, Clark BJ, Douglas IS. Predictors of severe alcohol withdrawal syndrome: A systematic review and meta-analysis. Alcohol Clin Exp Res 2014;38:2664-77.
Kim DW, Kim HK, Bae EK, Park SH, Kim KK. Clinical predictors for delirium tremens in patients with alcohol withdrawal seizures. Am J Emerg Med 2015;33:701-4.
Alende-Castro V, Alonso-Sampedro M, Vazquez-Temprano N, Tuñez C, Rey D, García-Iglesias C, et al
. Factors influencing erythrocyte sedimentation rate in adults: New evidence for an old test. Medicine (Baltimore) 2019;98:e16816.
[Table 1], [Table 2], [Table 2]