: Admission information for included and excluded participants 18 Stroke is the most common cause of long-term neurological disability worldwide (Feigin et al. 2014) . 60
Currently, half of all people who survive a stroke are left disabled, with a third relying on others to 61 assist with activities of daily living (Association 2016) . A major contributor to ongoing physical 62 disability is persistent difficulty in using the upper-limb (Broeks et al., 1999) . For many years it was 63 believed that spontaneous upper-limb recovery occurred in the first 3 months following a stroke, with 64 only small rehabilitation-induced improvements happening after this period (Krakauer et al. 2012) . Schallert, Hernandez, and Barth 1986) and retrospective human studies (Goldstein 1998 (Goldstein , 1995 indicate activation at GABA receptors is detrimental to motor recovery. Though carefully matched 78 placebo-controlled studies are the gold-standard for identifying the true effects of a given drug on 79 motor recovery, these trials are costly and practically difficult. They must combine chronic drug 80 administration with specific high-dose motor training (Kwakkel, Meskers, and Ward 2020) . 81
Retrospective analysis that examines how drug prescriptions influence patients' response to 82 rehabilitation programmes can provide a solution to some of these issues. In a naturalistic setting, 83 prescriptions of common drugs come hand-in-hand with the co-morbidities they are aiming to treat, 84 such as depression, epilepsy or spasticity. These issues may themselves impact on recovery, or 85 interact with effects of the drug, making it difficult to draw conclusions about specific drug effects. 86 4 Another potential issue surrounding retrospective analysis of existing datasets is that, without pre-90 registration, researchers can be biased to make arbitrary analysis decisions motivated by results. A 91 novel method, known as specification curve analysis (SCA), has been developed to tackle this problem 92 (Simonsohn, Simmons, and Nelson 2019 Patients were referred to the QSUL programme by primary care physicians. The inclusion criteria for 105 admission to the program was/is broad, focussing on whether patients were likely to achieve their 106 goals for their upper-limb. There were no restrictions on time since stroke/injury or other 107 demographic factors, but patients who experienced any of the following were not admitted: i) absent 108 movement throughout the limb; (ii) a painful shoulder limiting an active forward reach (mostly due to 109 adhesive capsulitis); (iii) severe spasticity or non-neural loss of range and (iv) unstable medical 110 conditions. For more information regarding patient admission see Ward et al., 2019. 111 Between April 2014 and March 2020, a total of 439 first-time patients had been admitted to the 3-112
week programme. Of these, 321 patients had completed the 6 week and 6 month follow-up. There 113 were several reasons that patients were not available for follow-up: some could not be contacted, 114 considered it too far to travel, or suffered intercurrent illnesses; a large number were due for follow-115 up after the UK COVID-19 lockdown in March 2020. A further 15 patients were excluded as they did 116 not have mood and/or fatigue measures recorded, and a final 29 patients were excluded as 117 prescription drug information was not supplied at referral. This left a total of 277 patients for whom 118 All rights reserved. No reuse allowed without permission. perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in Function of the affected upper-limb was assessed on admission, discharge, 6 weeks and 6 months 125 post-discharge using the following measures: Fugl-Meyer upper-limb (FM), Action Research Arm Test 126 (ARAT), and the Chedoke Arm and Hand Activity Inventory (CAHAI). The FM is a stroke-specific, 127 performance based impairment index. Here a modified version was used-excluding coordination and 128 reflexes-which specifically focussed on motor synergies and joint function. This had a maximum score 129 of 54 and the minimum clinically important difference (MCID) has been reported as 5.25 points (Page, 130 Fulk, and Boyne 2012). The ARAT assesses patients' ability to handle objects of differing size, weight 131 and shape. It has a maximum score of 57 and a MCID of 5.7 points (Van der Lee et al. 2001 ). Finally, 132 the CAHAI focuses on how the arm and hand are incorporated into bilateral activities of daily living. 133
The maximum score is 91 and though no MCID has been reported the minimum detectable change 134 has been reported as 6.2 points (Barreca et al. 2005 All rights reserved. No reuse allowed without permission.
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The copyright holder for this this version posted October 23, 2020. ; https://doi.org/10.1101/2020.10.21.20215038 doi: medRxiv preprint demographic information, e.g. age and sex, and neurological information, e.g. time since stroke/injury 139 (at admission) and whether their dominant arm was affected, was also recorded. 140
Primary care physicians supplied each patient's prescribed drugs at the time of referral. Drugs acting 141 on the CNS were grouped into three categories: GABA agonists, antiepileptics (acting on sodium or 142 calcium channels), and antidepressants. Patients were coded as 'on' a category if they prescribed any 143 one (or more) of the drugs within the category. Dose or prescription directions were not recorded. 144
The specific drugs included in each category were: GABA agonists (n=49) -baclofen (n=41), perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted October 23, 2020. To assess the effect of each drug prescriptions on improvement, all three upper-limb measures were 180 again examined, and the same set of covariates were either included or excluded. There are a variety 181 of different ways improvement could be modelled: an outcome model, predicting the final T 6month 182 score from the T admission score; an absolute recovery model, examining the change in score from 183 T admission to T 6month ; or a relative recovery model, predicting the amount of recovery achieved relative to 184 the amount possible ((T 6month -T admission )/(Max Score -T admission )). This creates a total of 288 possible 185 models all of which test the hypothesis that the drug prescription status influences motor 186 improvement from the QSUL. Again, all outcome scores were proportions of the maximum possible 187 score, and recovery scores were calculated using these proportions. 188 SCA models were also run to test the influence of HADS score on improvement. Models were the 189 same as for testing for the effect of drug prescriptions, except all drugs were either included or 190 excluded together, and NFI was included or excluded independent to HADS score. 191
Hypothesis testing of SCA 192 In each SCA, a certain proportion of the models examined will report an effect that reaches statistical 193 significance (p<0.05). However, SCA aims to examine the evidence as a whole, summing across all the 194 different individual models. In order to assess the statistical significance of the sum of evidence from 195 a given SCA, a permutation method was used to generate the distribution of p-values, given the null 196 hypothesis that the dependent variable (drug prescription) of interest has no effect on the 197 independent variable (admission/improvement score) (Rohrer, Egloff, and Schmukle 2017). For each 198 All rights reserved. No reuse allowed without permission. perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted October 23, 2020. ; https://doi.org/10.1101/2020.10.21.20215038 doi: medRxiv preprint SCA, in 500 permutations, the independent variables were shuffled, while keeping the dependent 199 variables and covariates un-shuffled. The total number of models with a significant effect of the 200 dependant variable, for each permutation of the SCA was then extracted. A p-value for each SCA was 201 calculated as the proportion of these permutations that had at least as many significant models as the 202 original data. 203
Differences between included and excluded participants 205 To assess whether there were any differences in the demographics of participants who were included 206 in the analysis compared with those who were excluded, t-tests and chi-square tests were performed, 207 with full results reported in Table 1 significantly worse on admission to the QSUL (p<0.002). Of the 96 separate models run in the 217 admission SCA, 84 reported a significant effect of this drug category, and across all three of the 218 different admission measures GABA agonist prescription was found to negatively impact scores (see 219 Figure 3A ). The mean value of the regression coefficients (β ) for significant results was -0.085, with a 220 range of -0.115 to -0.066. This equates to a mean of 8.5% (range 6.6 -11.5%) reduction in admission 221 scores in patients with a GABA agonist prescription relative to those without. Mean β across all 222 models was -0.083 (range -0.115 to -0.062). 223 All rights reserved. No reuse allowed without permission. perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted October 23, 2020. ; https://doi.org/10.1101/2020.10.21.20215038 doi: medRxiv preprint 224 Using SCA to examine the effect of GABA agonist prescription on programme-related improvements 225 in motor function did not generate sufficient evidence to reject the null hypothesis (p=0.266, 11/288 226 models significant, mean β = -0.026, range -0.104 to 0.01; see Figure 2B ). 227 All rights reserved. No reuse allowed without permission.
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The copyright holder for this this version posted October 23, 2020. The results of the SCA revealed no overall significant effect of antiepileptic prescription on admission 238 scores (p=0.152, 2/96 models significant, mean β = -0.039, range -0.066 to -0.022). (see Figure 4A ). 239
However, SCA of antiepileptic prescription on improvements revealed an effect approaching 240 significance (p=0.052, 77/288 models significant, mean β = -0.032, range -0. 159 perpetuity.
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The copyright holder for this this version posted October 23, 2020. ; https://doi.org/10.1101/2020.10.21.20215038 doi: medRxiv preprint two-sample t-test of HADS scores, than those without (t(88)=2.76, p=0.007) (see Figure 6A ). This was 275 not however the case for GABA agonist (t(66)=1.46, p=0.148) or antiepileptic prescriptions 276 (t(136)=1.01, p=0.312). NFI score also did not differ by antidepressant prescription (t(91)=0.80, 277 p=0.425). 278
To follow-up, a median split was performed on the HADS scores in patients without antidepressant 279 prescription. These three groups (OnAD, OffAD-HighHADS, OffAD-LowHADS) had significantly 280 different HADS scores (ANOVA : F(2,274)=142.3, p<0.001) , and pairwise comparison showed that the 281 AD+ group had significantly higher HADS score than the OffAD-LowHADS (Tukey HSD: diff=7.89, 282 p<0.001) and significantly lower HADS than the OffAD-HighHADS group (Tukey HSD: diff=-2.44, 283 p=0.004) (see Figure 6A ). Visual inspection of the motor score data on the three measures, across the 284 timepoints separated by these three groups again demonstrates the negative effect of antidepressant 285 prescription on recovery even relative to the OffAD-HighHADS (see Figures 6B-D) . Visually demonstrating that patients with antidepressant prescriptions have poorer improvement than those without, even when comparing against only those with high HADS scores.
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The copyright holder for this this version posted October 23, 2020. scores, around a 6-10% reduction relative to those not prescribed the drug. Despite the large effect 303 size, this difference is somewhat difficult to interpret. The drugs in the GABA agonist category are 304 prescribed for diverse problems, for example baclofen (prescribed to 84% of the GABA agonist group) 305 for spasticity or benzodiazepines (18% of GABA agonist group) for anxiety, insomnia and seizures. 306 Clearly any differences in admission scores could be attributed either to the underlying co-morbidity 307 for which the drug is prescribed, the effects of drug itself, or an association between the co-morbidity 308 and increased stroke severity. While there were some control measures recorded at admission, e.g. 309 HADS and NFI scores, there were not any measures of spasticity or sleep quality which might be 310 relevant for assessing differences between those on and off GABA agonists. 311 perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted October 23, 2020. ; https://doi.org/10.1101/2020.10.21.20215038 doi: medRxiv preprint agonist baclofen impairs aspects of motor learning in healthy humans (Johnstone et al., 2020) ; and 317 GABA antagonists can improve post-stroke motor recovery in rats (Clarkson et al. 2010; Schallert, 318 Hernandez, and Barth 1986). Given these findings, and another early retrospective study finding a 319 negative impact of benzodiazepine prescription on motor function recovery (Goldstein, 1995, though 320 see Nadeau et al., 2014) , caution has previously been advised in the prescription of GABA agonists, 321 particularly benzodiazepines, post-stroke (Hesse and Werner 2003) . 322
Yet in this data set, patients who were taking GABA agonists performed as expected, even despite co-323 morbidities which could additionally hamper potential for improvement from the programme. The 324 result reported here should not, however, be taken as evidence that these drugs do not have 325 detrimental effects on motor rehabilitation-patients were often advised to take these medications at 326 night likely minimising their potential to interact with rehabilitation. Rather, this result should be 327 interpreted as the absence of negative effect of GABA agonists when they are prescribed 328 appropriately. It could also be argued that the symptoms which these drugs seek to treat, e.g. 329 spasticity or insomnia, may themselves worsen rehabilitative potential more than the drugs if left 330 unresolved (Fleming et al. 2020) . 331 Sodium and calcium channel blocking antiepileptics did not impact admission scores 332 or motor improvements on the QSUL programme.
Stroke is the cause of 10% of all epilepsy cases (Feyissa, Hasan, and Meschia 2019) and so a great deal 334 of stroke patients, 29% in this data-set, are prescribed antiepileptics targeting sodium and calcium 335 channels. Here we found that there were no significant differences in admission motor scores in 336 patients prescribed antiepileptics versus those who were not. Comparing improvements on the QSUL 337 programme between the groups also resulted in a non-significant difference, however there was a 338 trend towards a decrease in improvements for patients on antiepileptics. Closer examination of this 339 finding shows that it was driven only by poorer improvements on one measure, the ARAT, with very 340 little effect on the CAHAI or FM, suggesting that this was not a robust effect across motor measures. 341
Though classic antiepileptic treatments, such as phenytoin or phenobarbital, have been suggested to 342 be detrimental to motor recovery in retrospective studies (Goldstein 1995) , there is little evidence for 343 any influence of modern antiepileptic drugs on patient outcomes (Nadeau et al. 2014 ). In fact some 344 animal studies have even found neuroprotective benefits of Na channel blockers (Wang, Fessler, and 345 Chuang 2011). The results presented here align with a lack of significant effect of this class of drugs 346 on rehabilitation-induced motor improvements when prescribed appropriately. 347 All rights reserved. No reuse allowed without permission. perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted October 23, 2020. ; https://doi.org/10.1101/2020.10.21.20215038 doi: medRxiv preprint Patients prescribed antidepressants do significantly worse on the QSUL programme. Here antidepressants (the vast majority of which were SSRIs, ~80%) were paired with rehabilitation, 373 and so might be predicted to boost recovery. Some speculative reasons could be proposed for this 374 divergence in findings: it may be that the beneficial effect of SSRIs does not persist in conjunction 375 with depressive symptoms; or it could be that the antidepressant prescription is a better measure of 376 trait depression, across the 6 month duration of the follow-up, than the one-time HADS score at 377 admission, and the negative impact of these depressive symptoms may outweigh any positive impact 378 of the drug. Further research is needed to identify a mechanistic explanation for this effect, but there 379 All rights reserved. No reuse allowed without permission. perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted October 23, 2020. ; https://doi.org/10.1101/2020.10.21.20215038 doi: medRxiv preprint is still value in the observation that patients with antidepressant prescriptions tend to do worse on 380 intensive rehabilitation programmes. Identifying those patients who may respond less well to the 381 treatment is the first step in developing methods to improve interventions for these patients. perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted October 23, 2020. ; https://doi.org/10.1101/2020.10.21.20215038 doi: medRxiv preprint