Risk assessment of moderate to severe alcohol withdrawal Predictors for seizures and delirium tremens

Transcription

1 Risk assessment of moderate to severe alcohol withdrawal Predictors for seizures and delirium tremens Results of a retrospective Cohort Study Florian Eyer, MD Toxicological Department Klinikum rechts der Isar Technische Universität Munich Germany

2 Background (1) Alcohol withdrawal syndrom (AWS) may cause serious complications Withdrawal seizures (5-10%): 6-48 h after the cessation of drinking Delirium tremens (5%): h after the last drink. Hillbom et al., 2003; Rathlev et al., 2006; Mayo-Smith et al., 2004

3 Background (2) Treatment strategies could be optimized if patients with a higher risk to develop WS or DT could be identified Complications may be prevented through prompt and intensive treatment (e.g. benzodiazepines, clomethiazole, antiepileptic drugs, etc.) Existing literature data suggesting associations between risk factors and critical events during AWS either lack empiric data are limited by inadequate sample size or lack of multivariable analyses Lee et al., 2005; Saitz et al., 1994; Cushman et al., 1987; Milne et al., 1991

4 Background (3) Reported risk factors for withdrawal seizures (WS) WS as the cause of admittance previous detoxification admissions CIWA-Ar Score>15 known structural brain lesions greater number of withdrawal episodes in the past Goddard et al., 1996; Ballenger et al., 1978; Clemmesen et al., 1984; Rathlev et al., 2000

5 Background (4) Reported risk factors for delirium tremens (DT) lower serum potassium prior complicated AWS (either WS or DT) prevalence of a current medical disease AWS despite and BAC>1g/L Greater number of drinks/24hr and more years of heavy drinking History of head injury Higher age Fiellin et al., 2000; Schuckit et al., 1995; Ferguson et al., 1996; Palmstierna et al., 2001

6 Treatment protocol of AWS during the study period Symptom triggered therapy with clomethiazole Thiamin 100 mg thrice daily or mg i.v. in high-risk patiens Clonidine µg p.o. 3-4 times daily (in case of hyperadrenergic activity) Either CBZ (200 mg p.o., thrice) or VPA (300 mg p.o. four times daily) to prevent seizures ICU-admission due to DT: Midazolam 1-12 mg/h i.v. for sedation Clonidine µg/h i.v. (hyperadrenergic activity) Haloperidol mg i.v. (productive hallucinations) Malcolm et al., 2001; Longo et al., 2002; Lum et al., 2006

7 Patient selection Secondary analysis of a cohort of adult patients initially screened to detect differences between the adjunct use of either CBZ (n=374) or VPA (n=453) during AWS All patients admitted to our department for alcohol detoxification between were eligible for this study Patients identified through computerized search of discharge diagnosis ICD-10 (F10.3 or F10.4) - Kodip version , 3M All patients fulfilled the ICD-10 criteria of alcohol dependence A total number of 827 patients (2691 screened patients) were included in this analysis Stepwise multivariate analysis was performed to account for differences in baseline parameters or treatment (AED) related effects between the groups Eyer et al., 2011

8 Patient selection Exclusion criteria Severity of AWS only mild (AWS-score <6) Dependence of benzodiazepines according to ICD-10 Positive screening results for opiates, amphetamine and cocaine Incomplete or inaccessibility of physical charts Lack of adequate documentation to support diagnosis of AWS or related complications

9 Results - Seizures (1)

10 Results - Seizures (1)

11 Results - Seizures (1)

12 Results - Seizures (1)

13 Results Seizures (2)

14 Results Seizures (2)

15 Results Seizures (2)

16 Results Seizures (2)

17 Results Delirium (3)

18 Results Delirium (3)

19 Results Delirium (3)

20 Results Delirium (3)

21 Results Delirium (3)

22 Results Delirium (3)

23 Results Delirium (3)

24 Results Delirium (4)

25 Results Delirium (4)

26 Results Delirium (4)

27 Results Delirium (4)

28 Results Delirium (4)

29 Results Delirium (4)

30 Results Delirium (4)

31 Results of the stepwise logistic regression model

32 Results of the stepwise logistic regression model

33 Results of the stepwise logistic regression model

34 Nomogram to predict the risk of seizures

35 Nomogram to predict the risk of seizures

36 Nomogram to predict the risk of seizures

37 Nomogram to predict the risk of seizures

38 Nomogram to predict the risk of seizures

39 Nomogram to predict the risk of seizures

40 Nomogram to predict the risk of seizures

41 Nomogram to predict the risk of seizures

42 Nomogram to predict the risk of seizures

43 Nomogram to predict the risk of seizures

44 Nomogram to predict the risk of seizures

45 Nomogram to predict the risk of seizures

46 Nomogram to predict the risk of seizures estimated risk of about 25%

47 Nomogram to predict the risk of delirium

48 Conclusions (1) Complications during AWS still do occur despite careful patient monitoring & intensified treatment In 61 patients (7.4%) AWS coursed with WS In 46 patients (5.6%) AWS coursed with DT There was no fatal outcome in both groups

49 Conclusions (2) Our data suggests that there are some easily determinable parameters at admission that may be suitable to predict a complicated course of AWS Using the applied nomogram, clinicians can estimate the percentage likelihood of patients to develop WS or DT Prevalence of structural brain lesions in the patients history does strongly warrant a careful observation and aggressive treatment of AWS

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