Highlights • Meta-analysis of 18 controlled experiments supported analgesic effects of alcohol.

• Alcohol resulted in a small increase in pain threshold.

• A moderate-large decrease in pain ratings was also observed.

• Higher blood alcohol content is associated with greater analgesia.

• Analgesic effects may contribute to alcohol dependence in those with persistent pain.

Abstract Despite the long-standing belief in the analgesic properties of alcohol, experimental studies have produced mixed results. This meta-analysis aimed to clarify whether alcohol produces a decrease in experimentally-induced pain and to determine the magnitude of any such effect. PubMed, PsycINFO, and Embase databases were searched from inception until April 21, 2016 for controlled studies examining the effect of quantified dosages of alcohol on pain response to noxious stimulation. Eighteen studies involving 404 participants were identified providing alcohol versus no-alcohol comparisons for 13 tests of pain threshold (n = 212) and 9 tests of pain intensity ratings (n = 192). Random effects meta-analysis of standardized mean difference (SMD) provided robust support for analgesic effects of alcohol. A mean blood alcohol content (BAC) of approximately .08% (3–4 standard drinks) produced a small elevation of pain threshold (SMD [95% CI] = .35 [.17–.54], P = .002), and a moderate to large reduction in pain intensity ratings (SMD [95% CI] = .64 [.37–.91], P < .0001), or equivalently, a mean reduction of 1.25 points on a 0- to 10-point pain rating scale. Furthermore, increasing BAC resulted in increasing analgesia, with each .02% BAC increment producing an increase of SMD = .11 for pain threshold and SMD = .20 for reduced pain intensity. Some evidence of publication bias emerged, but statistical correction methods suggested minimal impact on effect size. Taken together, findings suggest that alcohol is an effective analgesic that delivers clinically-relevant reductions in ratings of pain intensity, which could explain alcohol misuse in those with persistent pain despite its potential consequences for long-term health. Further research is needed to corroborate these findings for clinical pain states. Perspective This meta-analysis provides robust evidence for the analgesic properties of alcohol, which could potentially contribute to alcohol misuse in pain patients. Strongest analgesia occurs for alcohol levels exceeding World Health Organization guidelines for low-risk drinking and suggests raising awareness of alternative, less harmful pain interventions to vulnerable patients may be beneficial.

Key words Pain

alcohol

ethanol

analgesia

review

meta-analysis

47 Macfarlane G.J.

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Macfarlane T.V.

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Vincent A.

Clauw D.J.

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King C. Self-report of alcohol use for pain in a multi-ethnic community sample. 17 Egli M.

Koob G.F.

Edwards S. Alcohol dependence as a chronic pain disorder. A link between increased alcohol use and reduced chronic pain has emerged from several large population-based studies. Macfarlane and Beasleyreported that self-reported moderate to high (11–35 units per week) drinkers were approximately two-thirds as likely to report chronic widespread pain than infrequent drinkers. Furthermore, among those with pain, moderate to high drinkers were approximately a quarter as likely to report disabling pain. This relationship has been confirmed in a further study of chronic widespread painand extends to fibromyalgiaand knee pain; although any putative benefits of alcohol disappear for extreme levels of consumption.Moreover, the possibility that up to 25% of people with pain report self-medication with alcohol because of its perceived analgesic propertiesis troubling because of the health consequences of sustained alcohol use. However, although the relationship between pain and opiate misuse has been extensively studied, considerably less attention has been devoted to pain and alcohol use.

17 Egli M.

Koob G.F.

Edwards S. Alcohol dependence as a chronic pain disorder. 2 Apkarian A.V.

Neugebauer V.

Koob G.

Edwards S.

Levine J.D.

Ferrari L.

Egli M.

Regunathan S. Neural mechanisms of pain and alcohol dependence. 41 Knott C.S.

Coombs N.

Stamatakis E.

Biddulph J.P. All cause mortality and the case for age specific alcohol consumption guidelines: Pooled analyses of up to 10 population based cohorts. 18 Fillmore K.M.

Stockwell T.

Chikritzhs T.

Bostrom A.

Kerr W. Moderate alcohol use and reduced mortality risk: Systematic error in prospective studies and new hypotheses. Although these findings are suggestive of an analgesic effect of alcohol, causality cannot be determined from observational data and alternative explanations have been proposed. For example, chronic pain and alcohol dependence may share common neural circuitsand pain states could affect alcohol usage by influencing reward pathways that regulate consumption.Alternatively, deterioration in pain may lead to reduced alcohol intake because of increasing health concerns or medication contraindications. Classification decisions of level of alcohol use and inaccurate self-reporting may further influence findings.Fillmore et al,for example, showed that the link between alcohol use and heart disease disappeared when reclassifying ‘alcohol abstainers’ to exclude former drinkers.

17 Egli M.

Koob G.F.

Edwards S. Alcohol dependence as a chronic pain disorder. 58 Staahl C.

Olesen A.E.

Andresen T.

Arendt-Nielsen L.

Drewes A.M. Assessing analgesic actions of opioids by experimental pain models in healthy volunteers - an updated review. 34 Horn-Hofmann C.

Büscher P.

Lautenbacher S.

Wolstein J. The effect of nonrecurring alcohol administration on pain perception in humans: A systematic review. Understanding causal direction in the link between alcohol use and pain is important. If alcohol does produce analgesia, this may encourage alcohol dependence in those with pain,and suggests that efforts to promote alternative interventions for chronic pain with fewer negative health consequences (eg, physical therapy, exercise, controlled administration of pain medication) may be worthwhile. The use of experimental pain paradigms can help determine causality by studying the effect of measured dosages of alcohol on quantifiable indices of pain in response to noxious stimuli, and avoids many of the confounds present in clinical data.However, although experimental studies have offered some evidence for alcohol analgesia, findings are inconsistent and have exhibited substantial variation in effect sizes.

36 James M.F.

Duthie A.M.

Duffy B.L.

Mckeag A.M.

Rice C.P. Analgesic effect of ethyl alcohol. , 69 Woodrow K.M.

Eltherington L.G. Feeling no pain: Alcohol as an analgesic. 34 Horn-Hofmann C.

Büscher P.

Lautenbacher S.

Wolstein J. The effect of nonrecurring alcohol administration on pain perception in humans: A systematic review. As such, our current understanding of alcohol analgesia is limited. This is perhaps surprising considering the longstanding acceptance of the analgesic properties of alcohol and claims of an analgesic potency comparable with opiates.Because of the general use of small samples and variability in dosages, administration methods, and outcome measures in previous studies,our understanding of alcohol analgesia would be significantly advanced by meta-analysis of existing data to optimize power and provide robust estimates of effect size accounting for different sources of study heterogeneity.

We therefore conducted a meta-analysis of controlled experiments examining the effect of measured alcohol dosages versus no alcohol on response to noxious stimulation in human participants to determine the: 1) the existence of alcohol analgesia, 2) the magnitude of any analgesic effects, and 3) the effect of moderating variables.

Methods 51 Moher D.

Shamseer L.

Clarke M.

Ghersi D.

Liberati A.

Petticrew M.

Shekelle P.

Stewart L.A. PRISMA-P Group

Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-P 2015 statement for systematic review and meta-analysis protocols. Eligibility Criteria Studies were included that used: 1) adults given a controlled quantified dose of alcohol, 2) a comparative no alcohol control group/condition, 3) medically and neurologically healthy participants, 4) an experimental pain stimulus and an established pain assessment (eg, pain threshold), and 5) were published in an international peer-reviewed journal or conference abstract. 7 Brown R.A.

Cutter H.S. Alcohol, customary drinking behavior, and pain. Studies were excluded if samples consisted of chronic pain patients or those with a history of alcohol abuse, because these may represent heterogeneous groups with altered processing of sensory or noxious stimuli. Search Procedure Two reviewers (C.O., B.S.) independently searched PubMed, EMBASE, PsycINFO and CINAHL Plus from database inception until April 21, 2016 using the major search terms (ethanol or alcohol) and ((pain or nociception) or (analgesia or analgesi*)) and a number of secondary search terms relating to experimental pain stimuli including ‘pressure’ or ‘mechanical’ or ‘cold’ or ‘heat’ (see Appendix 1 for details). Search results were refined using limits of human studies and English language. Additional studies were identified by manually searching the reference lists of all relevant articles. Study Selection After removal of duplicates, 2 reviewers (C.O., B.S.) independently screened titles and abstracts and developed a list of potentially eligible full text articles. Two authors (C.O., B.S.) applied eligibility criteria and a final list of articles for inclusion was reached through consensus. Corresponding authors were contacted up to 3 times over a 6-week period to clarify results or to request additional data. Pain Outcomes 27 Gracely R.H. Studies of pain in human subjects. 27 Gracely R.H. Studies of pain in human subjects. 1 Apkarian A.V.

Bushnell M.C.

Treede R.D.

Zubieta J.K. Human brain mechanisms of pain perception and regulation in health and disease. Multiple assessment measures of pain threshold, pain tolerance, and pain rating scales were identified as outcomes, because these have been shown to be valid methods of quantifying pain that collectively capture different aspects of the pain experience.Pain threshold is the minimum amount of stimulation that evokes a report of pain, and pain tolerance is the point of maximum endurance,and both are typically measured in time or stimulation intensity. Whereas threshold involves low-intensity pain and is influenced primarily by sensory processes (eg, localization and initial detection), tolerance concerns near-maximal pain and is strongly influenced by affective mechanisms.Pain rating scales provide an easily interpretable index of subjective pain and typically assess sensory (eg, intensity) or affective (eg, discomfort) dimensions of pain on a 0 to 10 self-report scale. Study Quality 11 Ditre J.W.

Heckman B.W.

Zale E.L.

Kosiba J.D.

Maisto S.A. Acute analgesic effects of nicotine and tobacco in humans: A meta-analysis. Two raters (C.O., Nura Alkathiri) independently rated each study for methodological quality on a 13-item validity scale assessing methodological rigor, selection, and reporting bias ( Appendix 2 ). The scale was on the basis of items from Cochrane collaboration criteria, Preferred Reporting Items for Systematic Reviews and Meta-Analyses-P 2015 recommendations, PEDro guidelines as reported by Ditre et al,and was adapted for studies examined in the current review. Data Extraction 60 Stubbs B.

Thompson T.

Acaster S.

Vancampfort D.

Gaughran F.

Correll C.U. Decreased pain sensitivity among people with schizophrenia: A meta-analysis of experimental pain induction studies. , 61 Thompson T.

Correll C.U.

Gallop K.

Vancampfort D.

Stubbs B. Is pain perception altered in people with depression? A systematic review and meta-analysis of experimental pain research. 46 Lipsey M.

Wilson D. Practical Meta-Analysis. Two authors (C.O., B.S.) independently extracted and coded study data on a standardized extraction form used in several of our previous studieswith a few minor adaptations for the current topic. Means and SDs of pain measures were recorded, along with other key statistical information from which effect size can be computed.The following additional data were recorded for use in moderator analysis and to summarize study characteristics: sample (age, gender composition, weekly alcohol consumption, familial drinking history), alcohol manipulation (dosage, blood alcohol content [BAC] percentage; ie, g/dL, administration method), control group (inactive control/placebo), study design (within/between-groups), pain induction method (eg, electrical, pressure), and pain outcomes. 5 Borenstein M.

Hedges L.

Higgins J.

Rothstein H.R. Introduction to Meta-Analysis. 5 Borenstein M.

Hedges L.

Higgins J.

Rothstein H.R. Introduction to Meta-Analysis. 13 Dunlap W.P.

Cortina J.M.

Vaslow J.B.

Burke M.J. Meta-analysis of experiments with matched groups or repeated measures designs. 59 Stewart S.H.

Finn P.R.

Pihl R.O. A dose-response study of the effects of alcohol on the perceptions of pain and discomfort due to electric shock in men at high familial-genetic risk for alcoholism. 62 Thompson T.

Keogh E.

Chen M.J.

French C.C. Emotion-focused coping and distraction: Sex differences in the influence of anxiety sensitivity during noxious heat stimulation. , 63 Thompson T.

Keogh E.

French C.C. Sensory focusing versus distraction and pain: Moderating effects of anxiety sensitivity in males and females. , 64 Thompson T.

Keogh E.

French C.C.

Davis R. Anxiety sensitivity and pain: Generalisability across noxious stimuli. 28 Grissom R.J.

Kim J.J. Effect sizes for research. A broad practical approach. A number of decisions were made when computing effect sizes from extracted data: 1) When a study reported data from multiple independent groups of participants (eg, with/without a family history of alcoholism), effect sizes were computed for each subgroup and included in the meta-analysis as independent samples following the recommendations of Borenstein et al.2) A few studies assessed pain multiple times in the same participants (k = 3 studies reported multiple alcohol concentrations, k = 1 study used multiple pain inductions). In these instances, a mean pooled effect size was calculated for the overall meta-analysis, with individual effect sizes also computed for different alcohol concentrations for use in moderation analysis. Effect size variance was calculated using the reported mean correlation of pain scores, or if not presented, using an imputed correlation of r = .75.This value was chosen because it represents a reasonably typical test-retest correlation,was reported by the study with the largest sample in the current meta-analysisand approximates the correlation obtained from a pool of over 300 participants undergoing repeated pain testing in our own laboratory.3) For 1 study that reported an effect as significant at P < .001, a conservative effect size estimate was derived from rounding to P = .001. 4) For a few studies (k = 2) that applied an experimental aggression paradigm, pain scores only from the ‘low provocation’ group were recorded to minimize any potential influence of this paradigm on group differences. 5) For 1 study that reported semi-interquartile ranges rather than SDs, these were converted to SDs by applying a multiplication factor of .75 on the basis of the assumption of normality. Sensitivity Analysis Potential consequences of key decisions in the previous section were assessed with sensitivity analysis. In particular, the effect of using r = .75 as the imputed correlation when study correlations had not been reported, was examined by repeating analyses using a wide range of alternative coefficients in .05 increments from r = .30 to .90. Meta-Analysis 5 Borenstein M.

Hedges L.

Higgins J.

Rothstein H.R. Introduction to Meta-Analysis. 9 Cohen J. Statistical Power Analysis for the Behavioral Sciences. 53 Morris S.B.

Deshon R.P. Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs. The standardized mean difference between alcohol and control groups was computed for each study using Hedges' g formula.This is equivalent to Cohen d, but with a correction for small sample bias, and can be interpreted in the same way, with .20, .50, and .80 approximately corresponding to small, medium, and large effects.Effect sizes were computed using the original (unadjusted) SDs for within-group as well as between-groups designs.Hedges' g was coded so that positive values indicated an analgesic effect of alcohol (ie, increased pain threshold/tolerance or decreased pain ratings). 15 Eccleston C. The attentional control of pain: Methodological and theoretical concerns. 2 and τ to quantify the extent of heterogeneity. I2 estimates the proportion of total variation in effect size due to true heterogeneity, with values of 25%, 50%, and 75% indicating possible low, moderate, and high heterogeneity, 33 Higgins J.P.

Thompson S.G. Quantifying heterogeneity in a meta-analysis. A random effects model was used as heterogeneity in effect sizes was likely because of the methodological variation typically evident in experimental pain research.Cochran Q was used to assess the presence of heterogeneity and Higgins' Iand τ to quantify the extent of heterogeneity. Iestimates the proportion of total variation in effect size due to true heterogeneity, with values of 25%, 50%, and 75% indicating possible low, moderate, and high heterogeneity,and τ estimates the SD of the different population effect sizes. 35 Inthout J.

Ioannidis J.P.

Borm G.F. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard Dersimonian-Laird method. Model parameters were estimated using restricted maximum likelihood with separate tests conducted for each outcome. Meta-analysis was only performed for outcomes when more than 5 studies were available, because fewer studies can lead to unreliable parameter estimates for random effects.Pain ratings were only analyzed for studies where stimulation intensity was identical for both groups (ie, where a fixed-intensity/fixed-time paradigm was used), to avoid confounding of any group differences in pain ratings with differences in stimulation intensity. Publication Bias 16 Egger M.

Davey Smith G.

Schneider M.

Minder C. Bias in meta-analysis detected by a simple, graphical test. 14 Duval S.

Tweedie R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. To assess whether overall effect size estimates could be potentially inflated by publication bias, funnel plots of study effect sizes against standard errors/sample size were examined. If the plot suggested asymmetry because of the absence of small sample studies with small effect sizes (ie, those most likely to be nonsignificant), this suggests potential publication bias. Asymmetry was tested statistically with the Egger bias test,with P < .05 indicating asymmetry. If results were consistent with possible publication bias, a trim and fill methodwas used. This involves estimating a revised effect size after trimming smaller (less precise) studies, and then filling in imputed values from the presumed missing studies to create a symmetrical plot and a more accurate estimate of variance. Meta-Regression 32 Higgins J.P.

Green S. Cochrane Handbook for Systematic Reviews of Interventions. If heterogeneity was present and data were available for approximately 10 comparisons or more,meta-regression was conducted to examine whether the effects of alcohol were influenced by several variables. Primary moderators were BAC and drinking frequency (mean weekly alcohol consumption), with the rationale that both factors were likely to influence analgesic effects. Secondary moderators were gender composition, time between alcohol administration and pain testing, type of control (active placebo/passive control), and alcohol administration method, and were examined in an exploratory approach, in that it was determined a priori that any significant effects could only be considered preliminary. Study quality was also examined as a potential influence on effect size, with overall quality ratings and key individual design variables of counterbalancing and experimental blinding entered as moderators. Separate analyses were conducted for each moderator. 65 Viechtbauer W. Conducting meta-analyses in R with the metafor package. 55 R Core Team

R. A Language and Environment for Statistical Computing. All analyses were performed using the metaforpackage in R.

Results Database Searches Figure 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram—alcohol pain studies. Initial database searches yielded 1,816 unique hits with 7 potentially relevant records identified through manual searching of reference lists. After screening of abstracts, 28 articles were retained for full text review. Three author groups were contacted to request clarification of or additional data and responses were received from all 3. Overall, of the 28 articles, 10 were excluded, with reasons for exclusion and a summary of the study selection process shown in Fig 1 . Altogether, 18 studies were retained for analysis. Study Characteristics and Study Quality 19 Finn P.R.

Pihl R.O. Men at high risk for alcoholism: The effect of alcohol on cardiovascular response to unavoidable shock. , 21 Finn P.R.

Zeitouni N.C.

Pihl R.O. Effects of alcohol on psychophysiological hyperreactivity to nonaversive and aversive stimuli in men at high risk for alcoholism. , 54 Ralevski E.

Perrino A.

Acampora G.

Koretski J.

Limoncelli D.

Petrakis I. Analgesic effects of ethanol are influenced by family history of alcoholism and neuroticism. Table 1 Characteristics of included studies S tudy S tudy D esign T otal N A lcohol G roup or C ondition , n C ontrol G roup or C ondition , n A lcohol A dministration P opulation P ain I nduction M ean BAC, % P ain M easure Q uality A ssessment R ating Arout et al 3 Arout C.A.

Perrino A.C.

Ralevski E.

Acampora G.

Koretski J.

Limoncelli D.

Newcomb J.

Petrakis I.L. Effect of intravenous ethanol on capsaicin-induced hyperalgesia in human subjects. W 18 18 18 Intravenous NFH Chemical .04

.10 Pain threshold 11 Ralevski et al-a 54 Ralevski E.

Perrino A.

Acampora G.

Koretski J.

Limoncelli D.

Petrakis I. Analgesic effects of ethanol are influenced by family history of alcoholism and neuroticism. W 31 31 31 Intravenous NFH Electric .04

.10 Pain threshold; pain tolerance 12 Ralevski et al-b 54 Ralevski E.

Perrino A.

Acampora G.

Koretski J.

Limoncelli D.

Petrakis I. Analgesic effects of ethanol are influenced by family history of alcoholism and neuroticism. W 17 17 17 Intravenous FH Electric .04

.10 Pain threshold; pain tolerance 12 Duarte et al 12 Duarte R.

Mcneill A.

Drummond G.

Tiplady B. Comparison of the sedative, cognitive, and analgesic effects of nitrous oxide, sevoflurane, and ethanol. W 8 8 8 Drink NFH Pressure .084 Pain threshold; intensity ratings 11 Führer and Hammer 22 Führer M.

Hammer J. Duodenal chemosensitivity and mechanosensitivity in humans during acid and ethanol perfusion. W 9 9 9 Intravenous NFH Chemical pressure NA Pain threshold 7 Zacny et al 71 Zacny J.P.

Camarillo V.M.

Sadeghi P.

Black M. Effects of ethanol and nitrous oxide, alone and in combination, on mood, psychomotor performance and pain reports in healthy volunteers. W 11 11 11 Drink NFH Cold pressor .031

.062 Intensity ratings 11 Stewart et al 59 Stewart S.H.

Finn P.R.

Pihl R.O. A dose-response study of the effects of alcohol on the perceptions of pain and discomfort due to electric shock in men at high familial-genetic risk for alcoholism. PP 81 63 18 Drink Mixed Electric .063

.085

.088 Intensity ratings; discomfort ratings 12 Lau and Pihl 44 Lau M.A.

Pihl R.O. Alcohol and the Taylor aggression paradigm: A repeated measures study. W 17 17 17 Drink NFH Electric .11 Pain threshold 7 Finn et al-a 21 Finn P.R.

Zeitouni N.C.

Pihl R.O. Effects of alcohol on psychophysiological hyperreactivity to nonaversive and aversive stimuli in men at high risk for alcoholism. W 12 12 12 Drink FH Electric .09 Intensity ratings 11 Finn et al-b 21 Finn P.R.

Zeitouni N.C.

Pihl R.O. Effects of alcohol on psychophysiological hyperreactivity to nonaversive and aversive stimuli in men at high risk for alcoholism. W 12 12 12 Drink NFH Electric .09 Intensity ratings 11 Gustafson 29 Gustafson R. Alcohol and the validation of experimental aggression paradigms: The Taylor reaction time procedure. B 24 12 12 Drink NFH Electric .058 Pain threshold intensity ratings; discomfort ratings 10 Gustafson and Kallmen 31 Gustafson R.

Kallmen H. Alcohol and unpleasant stimulation: Subjective shock calibration and pain and discomfort perception. W 8 8 8 Drink NFH Electric .076 Pain threshold intensity ratings; discomfort ratings 8 Woodrow and Eltherington 69 Woodrow K.M.

Eltherington L.G. Feeling no pain: Alcohol as an analgesic. W 14 14 14 Drink NFH Pressure .07 Pain threshold; pain tolerance 10 Finn and Pihl 20 Finn P.R.

Pihl R.O. Risk for alcoholism: A comparison between two different groups of sons of alcoholics on cardiovascular reactivity and sensitivity to alcohol. W 20 20 20 Drink FH Electric .078 Intensity ratings; discomfort ratings 10 Cutter and O'Farrell 10 Cutter H.S.

O'Farrell T.J. Experience with alcohol and the endogenous opioid system in ethanol analgesia. W 20 20 20 Drink NA Cold pressor .06 Intensity ratings 10 Finn and Pihl-a 19 Finn P.R.

Pihl R.O. Men at high risk for alcoholism: The effect of alcohol on cardiovascular response to unavoidable shock. W 12 12 12 Drink NFH Electric .10 Intensity ratings; discomfort ratings 11 Finn and Pihl-b 19 Finn P.R.

Pihl R.O. Men at high risk for alcoholism: The effect of alcohol on cardiovascular response to unavoidable shock. W 12 12 12 Drink FH Electric .09 Intensity ratings; discomfort ratings 11 Finn and Pihl-c 19 Finn P.R.

Pihl R.O. Men at high risk for alcoholism: The effect of alcohol on cardiovascular response to unavoidable shock. W 12 12 12 Drink FH Electric .10 Intensity ratings; discomfort ratings 11 Gustafson 30 Gustafson R. Alcohol and aggression: A validation study of the Taylor aggression paradigm. B 36 18 18 Drink NFH Electric .067 Pain threshold intensity ratings; discomfort ratings 9 Saddler and James 57 Saddler J.M.

James M.F.

Harington A.P. Naloxone does not reverse ethanol analgesia in man. W 8 8 8 Intravenous NFH Pressure .087 Pain threshold 10 James et al 36 James M.F.

Duthie A.M.

Duffy B.L.

Mckeag A.M.

Rice C.P. Analgesic effect of ethyl alcohol. W 7 7 7 Intravenous NFH Pressure .11 Pain threshold 7 Chapman et al 8 Chapman L.F.

Dingman H.F.

Ginzberg S.P. Failure of systemic analgesic agents to alter the absolute sensory threshold for the simple detection of pain. W 15 15 15 Drink NFH Heat .07 ∗ ∗ Estimated using the Widmark equation. Pain threshold 6 Total W = 19, PP = 1, B = 2 404 356 311 Drink = 16, intravenous = 6 NFH = 16, FH = 5, Mixed = 1 Electric = 13, pressure = 5, cold = 2, chemical = 2, heat = 1 Mean BAC = .078% Threshold = 13, tolerance = 3, intensity = 13, discomfort = 8 Mean = 9.9 Abbreviation: NA, not available. NOTE. For study design: W = within groups; B = between groups; PP = pre-post (pre-post in alcohol and placebo groups); for population: NFH = no family history of alcoholism; FH = family history of alcoholism. Hyphenated letters (-a, -b, -c) suffixed to reference indicates different subsample data within the study. The 18 retained studies comprised a total of N = 404 participants and provided data for 22 group comparisons, because 3 studiesreported data for an additional 4 independent samples. Key study characteristics are presented in Table 1 . Of the 18 studies, data were missing for mean weekly alcohol consumption (missing k = 13), age (k = 10), gender (k = 3), and BAC (k = 2), otherwise all key data were reported. Most studies (k = 16, 89%) used a within-subjects design, 14 of which provided a minimum interval between testing of alcohol and control conditions of 1 day. Mean time between alcohol administration and pain testing was 42 minutes (SD = 17, range = 15–90). 35 Inthout J.

Ioannidis J.P.

Borm G.F. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard Dersimonian-Laird method. The following number of independent alcohol versus control comparisons was available for analysis: pain threshold (k = 13, n = 212), pain tolerance (k = 3, n = 62), pain ratings of intensity (k = 9, n = 192), and discomfort (k = 5, n = 137). Because the number of comparisons available for tolerance and pain discomfort did not exceed 5,these outcomes are not considered further. The studies that provided pain threshold data were different to those that provided pain ratings, generally reflecting the experimental choice between a threshold and a fixed-stimulus paradigm, where stimulation intensity is fixed for all participants (4 of the 13 pain threshold studies also reported pain intensity ratings, but ratings from these studies were not included in analysis of pain intensity because of inherent confounding with group differences in stimulus intensity—see the section on Meta-Analysis ) Study characteristics for these 2 sets of studies are presented in more detail in the sections on Pain Threshold and Pain Intensity Ratings Ratings of study quality showed acceptable agreement across 2 raters for overall quality ratings, intra-class correlation(A, 1) = .75, and across individual items (κ = .61–1.00) with 100% consensus reached where any disagreement had occurred. Mean overall study quality scores were high, mean = 9.9 (on a 0–13 scale), with most studies (89%) randomizing order/group allocation and 61% of studies using subject/experimenter blinding (see Appendix 2 for all item ratings). Pain Threshold 67 Watson P.E.

Watson I.D.

Batt R.D. Prediction of blood alcohol concentrations in human subjects. Updating the Widmark equation. 39 Kalinowski A.

Humphreys K. Governmental standard drink definitions and low-risk alcohol consumption guidelines in 37 countries. The 13 independent comparisons for pain threshold consisted of 182 participants in the alcohol group/condition and 182 participants in the control group/condition (mean age = 24.3 years, 79% male). Noxious stimulation was applied using a variety of modalities (electric = 5, pressure = 5, chemical = 2, heat = 1). Two methods of alcohol administration were used (drink = 7, intravenous = 6), with studies providing alcohol administered through drink reporting a mean dosage of 1.07 mL/kg. Mean BAC at testing was .079% (range = .058–.110). On the basis of the inverse Widmark equation,this is approximately equivalent to 3 to 4 standard drinks at consumption time for a typical male, or 2 to 3 standard drinks for a typical female (where standard drink is on the basis of the U.S. definition of 14 g ethanol (eg, 1 × 150 mL glass of 12% wine or 1 × 330 mL glass of 5% beer, although definitions of a standard drink varies across countries). Alcohol was compared with either a placebo/pseudoplacebo (k = 4), usually a negligible alcohol dose, or an inactive control (k = 9). Overall study quality scores ranged from 6 to 12 (mean = 8.9, SD = 2.02). Pain Intensity Ratings The 9 independent comparisons for pain intensity ratings consisted of 174 participants in the alcohol group/condition and 129 participants in the control group/condition (mean age = 27.2 years, 98% male). Two stimulus modalities were used (electric = 7, cold = 2) to deliver noxious stimulation with a mean baseline pain intensity rated as 5.3 (SD = 1.1) points on a 0- to 10-point scale. Alcoholic drink was the sole method of alcohol administration with a mean dosage of .94 mL/kg. Mean BAC was .082% (range = .047–.100), approximately equivalent to 3 to 4 (male) or 2 to 3 (female) standard drinks. Alcohol was compared with either a placebo/pseudoplacebo (k = 3) or an inactive control (k = 6). Overall study quality scores ranged from 10 to 12 (mean = 10.83, SD = .75). Meta-Analysis: Pain Threshold 9 Cohen J. Statistical Power Analysis for the Behavioral Sciences. Figure 2 Forest plot for pain threshold. Meta-analysis indicated an overall analgesic effect of alcohol versus control, with significantly higher pain threshold recorded after alcohol administration, g = .35, 95% confidence interval (CI), .17 to .54, z = 3.75, P = .002, representing a small analgesic effect. Fig 2 shows a forest plot of the 13 individual pain threshold comparisons, and shows that only 1 comparison reported increased pain (ie, reduced pain threshold) in the alcohol condition, with 12 comparisons reporting decreased pain. Meta-Analysis: Pain Intensity Ratings 9 Cohen J. Statistical Power Analysis for the Behavioral Sciences. Figure 3 Forest plot for pain intensity ratings. Meta-analysis indicated significantly reduced pain intensity ratings (k = 9) after alcohol administration; g = .64, 95% CI, .37 to .91, z = 4.71, P < .0001, representing a moderate to largeanalgesic effect. A forest plot of the 9 individual comparisons is shown in Fig 3 . Because pain intensity was rated on a homogenous 11-point scale in all studies, where 0 = no pain and 10 = maximum pain, meta-analysis was repeated on the raw (unstandardized) ratings. Results were, naturally, consistent with analysis of the standardized difference (mean difference = 1.25, 95% CI, .70 to 1.80, z = 4.45, P < .0001), and indicated a decrease from 5.30 (no alcohol) to 4.05 (alcohol) points, or a reduction of 1.25 points or a decrease of approximately 24%. 43 Konstantopoulos S. Fixed effects and variance components estimation in three-level meta-analysis. Although analysis was performed on independent samples of participants, several studies were carried out by the same research laboratories, inviting the possibility of data dependency (eg, due to a common methodology). Meta-analysis was accordingly rerun including laboratory as a second-order random factor,with a common coding given to comparisons obtained from the same laboratory. In line with the fairly wide distribution of effects sizes from the same laboratories illustrated in Fig 3 , this additional analysis indicated no systematic effect of research laboratory and no substantive change in effect size or confidence intervals (g = .61, 95% CI, .37–.85, P < .0001). Sensitivity Analysis 22 Führer M.

Hammer J. Duodenal chemosensitivity and mechanosensitivity in humans during acid and ethanol perfusion. 8 Chapman L.F.

Dingman H.F.

Ginzberg S.P. Failure of systemic analgesic agents to alter the absolute sensory threshold for the simple detection of pain. Rerunning meta-analysis replacing imputed correlations of r = .75 with r = .30 to .90 produced summary effect sizes ranging from g = .29 to .39 for pain threshold and g = .61 to .69 for pain intensity. This result suggests choice of imputed correlation had minimal effect on the effect size estimates. A minimal increase in effect size from the original g = .35 for pain threshold was observed when excluding Führer and Hammer,g = .39, who used atypical pain induction, and Chapman et al,g = .38, who reported semi-IQRs rather than SDs. Publication Bias A suggestion of asymmetry in the funnel plot of pain threshold was confirmed by Egger test (P = .019), indicating potential publication bias. Trim and fill estimates produced a revised effect size estimate of g = .31, 95% CI, .09 to .53, P = .005, compared with the original estimate of g = .35. No obvious asymmetry was evident in the funnel plot of pain intensity with Egger test nonsignificant, P = .27. Meta-Regression Significant heterogeneity emerged for pain threshold (Q = 31.61, df 12 , P = .002; I2 = 65%; τ = .26) and pain intensity (Q = 42.57, df 8 , P < .001; I2 = 79%; τ = .35), with the values of I2 suggesting moderate to high effect size inconsistency across studies. Therefore, meta-regression analyses were conducted to identify potential moderators. Study Quality 20 Finn P.R.

Pihl R.O. Risk for alcoholism: A comparison between two different groups of sons of alcoholics on cardiovascular reactivity and sensitivity to alcohol. Effect size was not moderated by overall quality ratings or use of subject/experimenter blinding for pain threshold and pain intensity, or randomization/counterbalancing for pain threshold, Ps = .10 to .54. Only 1 within-group study of pain intensityreported no counterbalancing (with the no alcohol condition always occurring first), so moderation analysis could not be reliably performed. Nevertheless, it is interesting to note that this study yielded the only negative study effect size for pain intensity (g = −.13). Primary Moderator: Alcohol Concentration and Drinking Frequency 66 Viechtbauer W.

Cheung M.W. Outlier and influence diagnostics for meta-analysis. 20 Finn P.R.

Pihl R.O. Risk for alcoholism: A comparison between two different groups of sons of alcoholics on cardiovascular reactivity and sensitivity to alcohol. 67 Watson P.E.

Watson I.D.

Batt R.D. Prediction of blood alcohol concentrations in human subjects. Updating the Widmark equation. To examine whether alcohol analgesia was amplified for higher alcohol concentrations, meta-regression was performed with BAC as a moderator. For pain threshold, increasing BAC was significantly associated with increased analgesia, B = 5.50, 95% CI, .03 to 10.96, P = .048. For pain intensity, 1 study outlier with a high externally studentized residualof z = 3.84 was excluded, with its removal being further justified by this being the only study failing to use counterbalancing.Subsequent analysis found that higher BAC was significantly associated with increased analgesia (ie, decreased pain ratings, B = 9.84, 95% CI, 2.64–17.04, k = 11, P = .007). Because a BAC of .02 approximately corresponds to 1 standard drink,regression coefficients were rescaled and indicated that every 1 standard drink resulted in an increase in Hedges' g of .11, 95% CI, .01 to .22, for elevated pain threshold and .20, 95% CI, .05 to .34 for reduced pain intensity. A moderator plot of BAC against effect size for pain intensity is shown in Fig 4 Figure 4 Pain intensity: Study effect size according to BAC (point sizes proportional to study weights). 2 indicated that variation in study BAC accounted for 65% of heterogeneity in pain intensity ratings and 25% of heterogeneity in pain threshold, leaving relatively low (I2 = 34%) and moderate (I2 = 52%) levels of effect size inconsistency in each measure, respectively. Drinking frequency (mean weekly alcohol consumption) was not examined as a moderator because of insufficient data. 32 Higgins J.P.

Green S. Cochrane Handbook for Systematic Reviews of Interventions. Values of pseudo-Rindicated that variation in study BAC accounted for 65% of heterogeneity in pain intensity ratings and 25% of heterogeneity in pain threshold, leaving relatively low (I= 34%) and moderate (I= 52%) levels of effect size inconsistency in each measure, respectively. Drinking frequency (mean weekly alcohol consumption) was not examined as a moderator because of insufficient data. Other Moderators Alcohol was associated with increased analgesia in studies with a higher proportion of male participants for pain threshold (k = 9, B = .006, P = .005) but not for pain ratings (k = 9, P = .36). After rerunning this analysis controlling for BAC, gender composition remained significant (P = .043), suggesting any heightened analgesic effect in studies with more men was not a product of any differences in alcohol concentrations. Time interval between alcohol and pain stimulation, type of control group, stimulus modality, method of administration, and familial alcoholism did not moderate alcohol effects for either pain outcome (k = 9–14, P = .34–.93).

Discussion To the best of our knowledge, the current study is the first meta-analysis to investigate the pain-relieving effects of alcohol assessed in controlled experimental studies. Eighteen studies of healthy individuals were examined, which provided data for 13 pain threshold comparisons (alcohol n = 182, control n = 182) and 9 pain intensity comparisons (alcohol n = 174, control n = 129). Several key findings emerged supporting an analgesic effect of alcohol: 1) Overall pain threshold was elevated after alcohol administration, although the magnitude of this effect was small (standardized mean difference = .35), 2) Ratings of pain intensity were reduced after alcohol administration, with a moderate to large effect (SMD = .64) observed, 3) A dose-response relationship emerged, with every .02% increment in BAC (approximately equivalent to 1 standard drink) associated with heightened analgesia for pain threshold (SMD increase = .11) as well as pain intensity (SMD increase = .20). Primary experimental studies investigating alcohol analgesia have yielded inconsistent findings, exemplified by the fact that only approximately half of the individual pain threshold studies in the current review were significant in and of themselves. The use of small samples and methodological variation, especially in alcohol dosage, are likely to contribute to this inconsistency and have led to uncertainty in establishing whether, and to what extent, alcohol produces relief from pain. The current study represents the first meta-analysis of these studies and provides robust evidence for the analgesic effects of alcohol. The reliability of these findings is endorsed by the use of sound experimental procedures (counterbalancing, subject/experimenter blinding, etc) by most of the reviewed studies and with effect sizes seemingly robust to suboptimal study quality. Furthermore, analgesic effects are unlikely to be attributable to participant expectancy bias, because effect sizes were similar for placebo (negligible alcohol dosage to reproduce taste and smell) and standard control comparisons. Pain-dampening effects of alcohol were also unaffected by method of alcohol administration (oral/intravenous), type of pain stimulation, and family history of alcoholism. Although some evidence suggested that analgesic effects for pain threshold may be amplified in men, this finding should be treated extremely cautiously because of the exploratory nature of the analysis as well as because only a limited number of studies included female participants. Nevertheless, this preliminary finding may have important ramifications and warrants further empirical investigation in primary research. Strength of Analgesic Effects and Implications 58 Staahl C.

Olesen A.E.

Andresen T.

Arendt-Nielsen L.

Drewes A.M. Assessing analgesic actions of opioids by experimental pain models in healthy volunteers - an updated review. Whereas analgesic effects of alcohol were relatively weak for pain threshold, moderate to large effects emerged for ratings of pain intensity at .08% BAC (3–4 standard drinks for male and 2–3 for female participants), and this was amplified at higher BAC (although analgesic efficacy cannot be ascertained outside of the study data range of .03–.11% BAC). These results mimic those typically seen for opiates where more pronounced analgesia is observed for suprathreshold levels of pain. 26 Gerbershagen H.J.

Rothaug J.

Kalkman C.J.

Meissner W. Determination of moderate-to-severe postoperative pain on the numeric rating scale: A cut-off point analysis applying four different methods. 6 Breivik H.

Collett B.

Ventafridda V.

Cohen R.

Gallacher D. Survey of chronic pain in Europe: Prevalence, impact on daily life, and treatment. 37 Jensen M.P.

Smith D.G.

Ehde D.M.

Robinsin L.R. Pain site and the effects of amputation pain: Further clarification of the meaning of mild, moderate, and severe pain. 48 Machado G.C.

Maher C.G.

Ferreira P.H.

Pinheiro M.B.

Lin C.W.

Day R.O.

Mclachlan A.J.

Ferreira M.L. Efficacy and safety of paracetamol for spinal pain and osteoarthritis: Systematic review and meta-analysis of randomised placebo controlled trials. 52 Moore R.A.

Straube S.

Aldington D. Pain measures and cut-offs - ‘no worse than mild pain’ as a simple, universal outcome. 23 Furlan A.D.

Sandoval J.A.

Mailis-Gagnon A.

Tunks E. Opioids for chronic noncancer pain: A meta-analysis of effectiveness and side effects. 58 Staahl C.

Olesen A.E.

Andresen T.

Arendt-Nielsen L.

Drewes A.M. Assessing analgesic actions of opioids by experimental pain models in healthy volunteers - an updated review. The fact that alcohol analgesia was observed for moderate pain, with a mean pain intensity rating of 5.3 of 10 for the studies reviewed in this study, may have implications for typical real-world pain experienced outside of the laboratory. Pain intensity ratings of 5 of 10 approximate several types of acute pain responses (eg, soft tissue injury and postoperative painand chronic pain conditions), and represent the threshold at which pain has a serious effect on functioning in cancer pain.Moreover, the reduction of 1.25 points on the 0 to 10 point scale meets the definition of a minimal clinically important difference of .9 of 10 (or 9 of 100) used by several authors; although minimal clinically important difference thresholds as high as 3 of 10 have also been suggested.In addition, analgesic effects of alcohol on pain intensity are comparable with opioids for chronic pain, with SMD = .60 reported in a meta-analytic review.Collectively, these findings suggest that alcohol may be an effective analgesic for nonlaboratory pain. However, it is important to emphasize that clinical pain differs from experimental pain on a number of key dimensionsand although suggestive, the analgesic effects observed for experimental pain cannot be generalized to clinical pain states without further rigorous empirical investigation. 40 Kim C.H.

Vincent A.

Clauw D.J.

Luedtke C.A.

Thompson J.M.

Schneekloth T.D.

Oh T.H. Association between alcohol consumption and symptom severity and quality of life in patients with fibromyalgia. , 45 Lawton J.

Simpson J. Predictors of alcohol use among people experiencing chronic pain. 68 Wise R.A.

Koob G.F. The development and maintenance of drug addiction. 25 Gatch M.B. Ethanol withdrawal and hyperalgesia. 70 World Health Organization

Global Status Report on Alcohol and Health—2014. 41 Knott C.S.

Coombs N.

Stamatakis E.

Biddulph J.P. All cause mortality and the case for age specific alcohol consumption guidelines: Pooled analyses of up to 10 population based cohorts. 17 Egli M.

Koob G.F.

Edwards S. Alcohol dependence as a chronic pain disorder. 24 Furtwaengler N.A.

De Visser R.O. Lack of international consensus in low-risk drinking guidelines. 25 Gatch M.B. Ethanol withdrawal and hyperalgesia. One clinical implication of the current findings is that the analgesic properties of alcohol are likely to contribute to the increased usage of alcohol observed in pain patients.Alcohol dependence may develop on the basis of negative reinforcement models of drug addiction,with pain relief representing the reinforcement, and maintenance encouraged by the hyperalgesia that follows analgesia after alcohol withdrawal.Alcohol is also easily accessible and relatively inexpensive and this is likely to further encourage its use as an analgesic in preference to alternative drugs of abuse or more difficult to obtain treatments. However, excessive alcohol consumption can present significant threats to long-term health, having shown associations with heart disease, liver disease, cancer, mental health problems,mortality,and an increased risk for developing future chronic pain conditions.The current findings suggest that the level of alcohol consumption needed to provide sustained moderate to large analgesia for persistent or recurrent pain exceeds the World Health Organization's guidelines of <20 g ethanol (less than 2 standard drinks) a day.In addition, continued analgesia may require increasing levels of consumption because tolerance to alcohol's analgesic effects with repeated exposure has been shown in rats and is also likely to occur in humans; although a lack of available data on average weekly alcohol consumption in the current review precluded an empirical investigation of this possibility. As such, efforts to promote alternative pain management strategies (eg, physical therapy, exercise, controlled use of pain medication) with fewer long-term health consequences may prove extremely beneficial. However, the analgesic effects of alcohol may also provide leads for the search of less toxic and nonaddictive forms of analgesia. 67 Watson P.E.

Watson I.D.

Batt R.D. Prediction of blood alcohol concentrations in human subjects. Updating the Widmark equation. 67 Watson P.E.

Watson I.D.

Batt R.D. Prediction of blood alcohol concentrations in human subjects. Updating the Widmark equation. An additional, experimental implication is that alcohol consumption should be restricted before pain testing to optimize reliability of pain assessment. Although alcohol elimination is affected by several factors, such as sex and body weight,an abstinence period of 5 hours may constitute a reasonable practical guideline, because .10% BAC will reduce to approximately .02% BAC (approximately one standard drink) after this time. Mechanisms of Action 38 Jørgensen H.A.

Hole K. Does ethanol stimulate brain opiate receptors? Studies on receptor binding and naloxone inhibition of ethanol-induced effects. , 50 Mogil J.S.

Marek P.

Yirmiya R.

Balian H.

Sadowski B.

Taylor A.N.

Liebeskind J.C. Antagonism of the non-opioid component of ethanol-induced analgesia by the NMDA receptor antagonist Mk-801. 54 Ralevski E.

Perrino A.

Acampora G.

Koretski J.

Limoncelli D.

Petrakis I. Analgesic effects of ethanol are influenced by family history of alcoholism and neuroticism. , 69 Woodrow K.M.

Eltherington L.G. Feeling no pain: Alcohol as an analgesic. Although analgesic mechanisms cannot be determined from the current data, animal models suggest that alcohol may inhibit nociceptive transmission centrally via nonopioid pathways by binding to N-methyl-D-aspartate receptors at the spinal cord level in mice,and similar mechanisms could be present in humans. Alternatively, analgesia could be mediated by the anxiolytic properties of alcohol,although this possibility has received limited empirical evaluation. Clearly, future research is required to disentangle the mechanisms through which alcohol confers an analgesic effect, which could serve as a lead to novel treatments for pain. Limitations 49 Melzack R.

Wall P.D. Handbook of Pain Management: A Clinical Companion to Wall and Melzack's “Textbook of Pain.”. 58 Staahl C.

Olesen A.E.

Andresen T.

Arendt-Nielsen L.

Drewes A.M. Assessing analgesic actions of opioids by experimental pain models in healthy volunteers - an updated review. The current meta-analysis was restricted to studies investigating response to noxious stimuli (especially electrical) in healthy participants and this represents a notable limitation. Clinical pain differs from experimentally-induced pain on psychological (eg, affect, perceived controllability)as well as physical (eg, duration, central sensitization)components, which may limit the clinical generalizability of the current findings. Nevertheless, if alcohol analgesia is partially mediated through emotional blunting, it may be that analgesia is actually enhanced for clinical pain states because of the greater negative affect produced by these states. An additional limitation is that a lack of available data on average alcohol consumption precludes conclusions on whether analgesic effects are attenuated by previous or chronic alcohol exposure. Future Studies 58 Staahl C.

Olesen A.E.

Andresen T.

Arendt-Nielsen L.

Drewes A.M. Assessing analgesic actions of opioids by experimental pain models in healthy volunteers - an updated review. 58 Staahl C.

Olesen A.E.

Andresen T.

Arendt-Nielsen L.

Drewes A.M. Assessing analgesic actions of opioids by experimental pain models in healthy volunteers - an updated review. Despite these limitations, the current findings provide strong support for substantive analgesic effects of alcohol on acute pain on the basis of laboratory studies, which provide a level of control not easily achievable in clinical research and which help establish causality. Further research is needed to determine clinical generalizability, and additional insights may be gained with the use ischemic and dermal capsaicin experimental pain models that evoke several aspects of clinical pain while preserving experimental control.In addition, the inclusion of an anxiety measure in experimental as well as clinical studies would permit an examination of the extent to which alcohol analgesia is mediated by its anxiolytic effects. Finally, future studies should routinely assess average alcohol consumption to estimate whether analgesic efficacy is diminished with sustained alcohol use, and assess the effect of variables such as pain duration, intensity, and age, which have been suggested to affect the efficacy of other analgesics.

Conclusions To the authors' knowledge, this is the first meta-analysis to examine the effect of alcohol on experimentally induced pain. Results provide robust evidence that alcohol is an effective analgesic for short-term pain, with small effects observed for pain threshold and moderate to large effects for ratings of pain intensity that exceed the threshold for clinical significance. These findings provide support for alcohol analgesia as a possible mechanism for promoting alcohol dependence in people with persistent pain and could help explain the relationship between alcohol use and chronic pain. Further research is needed to corroborate these findings in clinical pain states and to assess how the mechanisms of alcohol-related analgesia could be harnessed to develop novel, less toxic, and nonaddictive pain treatments.

Acknowledgments The authors thank Dr. Nura Alkathiri for providing independent ratings of study quality, and Dr. Gordon Drummond, Dr. Brian Tiplady, Dr. Johann Hammer, and Dr. Caroline Arout for their helpful responses to data requests.

Supplementary Data Appendix 1 Appendix 2