Investigating the True Effect of Psychological Variables Measured Prior to Arthroplastic Surgery on Postsurgical Outcomes: A P-Curve Analysis

Niederstrasser, Nils Georg; Cook, Stephanie

doi:10.1016/j.jpain.2020.07.005

Cited by 7 publications

(7 citation statements)

References 87 publications

(107 reference statements)

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“…58,65 Indeed, psychological variables are well-established predictors of pain after total knee and hip arthroplasty, particularly depression, anxiety, and pain catastrophizing. 33,41 However, Werner et al showed that QST measures are stronger independent predictors of postsurgical pain than psychological factors. 68 Concomitantly, it is known that psychological distress and pain catastrophizing seem to contribute to heightened sensitivity to noxious stimuli.…”

Section: Discussionmentioning

confidence: 99%

Predictive value of quantitative sensory testing for acute and chronic postsurgical pain after total joint arthroplasty: a systematic review

Paredes

Pinto

Almeida

et al. 2021

Pain

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Quantitative sensory testing (QST) can be useful to identify high-risk patients for the development of chronic postsurgical pain. This systematic review aims to assess if presurgical sensory sensitivity measured using QST is associated with acute and chronic postsurgical pain after total joint arthroplasty. A systematic search was performed in September 2020 in PubMed, EMBASE, Web of Science, and Scopus, using terms related to total joint arthroplasty and QST. Prospective studies were included if they reported an association between presurgical QST and postsurgical pain in adults with osteoarthritis undergoing primary unilateral total joint arthroplasty. From 2994 identified studies, 18 met the inclusion criteria (1869 patients). Total knee arthroplasty was the most common surgery (16 studies), and pressure pain threshold was the most common test (11 studies), followed by dynamic measures (9 studies). Postsurgical pain was assessed at acute (5 studies), subacute (2 studies), and chronic (13 studies) time points. Risk of bias was assessed using the Quality in Prognosis Studies tool and evaluated as low to moderate in most domains. Fourteen studies reported at least one statistically significant association between QST and pain (acute: 4 studies, subacute: 1 study, and chronic: 9 studies). Pressure pain threshold was associated with postsurgical pain in 6 studies (of 11, 55%), heat pain threshold in 2 studies (of 6, 33%), conditioned pain modulation in 1 study (of 6, 17%), and temporal summation of pain in 5 studies (of 8, 63%). The predictive role of presurgical QST for postarthroplasty pain remains unclear, mainly because of heterogeneous methodologies and inconsistent results.

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Section: Discussionmentioning

confidence: 99%

Predictive value of quantitative sensory testing for acute and chronic postsurgical pain after total joint arthroplasty: a systematic review

Paredes

Pinto

Almeida

et al. 2021

Pain

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“…Considering Cohen's [91] benchmarks of g (h) = .05 (.20), g = .15 (.50), and g = .25 (.80) as small, medium, and large, respectively, effect sizes observed in the present study should be considered negligible [77]. Thus, p-hacking may not be as large a problem to the cumulative knowledge of organizational research as some have cautioned in other areas of research [20][21][22][24][25][26][27][30][31][32][33].…”

Section: Discussionmentioning

confidence: 67%

“…The p-curve [5] analyzes the complete distribution of pvalues (i.e., 0 � p � 1) drawn from independent studies of a given effect. Analyses of p-curves have appeared in a variety of disciplines (e.g., [20,[23][24][25][26][69][70][71][72]). In this analytic approach, right-skew indicates the presence of true effects (i.e., evidential value) and a bump in the curve just under .05 indicates p-hacking.…”

Section: Approaches For P-hacking Detectionmentioning

confidence: 99%

“…Given the problematic consequences of p-hacking, various approaches to detect and quantify p-hacking have been developed including case studies [15], z-and p-curve analyses [16][17][18], test-statistic distribution analysis [19], or critical bin comparison analyses [13]. Indeed, applications of these approaches have appeared in areas such as public administration [20], accounting [21,22], psychophysiology [23][24][25], medicine [26,27], behavioral ecology and evolution [28,29], and experimental psychology [30][31][32][33]. In all of these cases, evidence of p-hacking has been observed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tempest in a teacup: An analysis of p-Hacking in organizational research

Gupta

Bosco

2023

PLoS ONE

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We extend questionable research practices (QRPs) research by conducting a robust, large-scale analysis of p-hacking in organizational research. We leverage a manually curated database of more than 1,000,000 correlation coefficients and sample sizes, with which we calculate exact p-values. We test for the prevalence and magnitude of p-hacking across the complete database as well as various subsets of the database according to common bivariate relation types in the organizational literature (e.g., attitudes-behaviors). Results from two analytical approaches (i.e., z-curve, critical bin comparisons) were consistent in both direction and significance in nine of 18 datasets. Critical bin comparisons indicated p-hacking in 12 of 18 subsets, three of which reached statistical significance. Z-curve analyses indicated p-hacking in 11 of 18 subsets, two of which reached statistical significance. Generally, results indicated that p-hacking is detectable but small in magnitude. We also tested for three predictors of p-hacking: Publication year, journal prestige, and authorship team size. Across two analytic approaches, we observed a relatively consistent positive relation between p-hacking and journal prestige, and no relationship between p-hacking and authorship team size. Results were mixed regarding the temporal trends (i.e., evidence for p-hacking over time). In sum, the present study of p-hacking in organizational research indicates that the prevalence of p-hacking is smaller and less concerning than earlier research has suggested.

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“…Patients with PCS > 16 had a 2.67-times increased risk of poor outcome (< 50% improvement) compared to patients with PCS ≤ 15 [ 10 ]. In a systemic review, Niederstrasser and Cook [ 25 ] highlighted the importance of patients’ psychological profiles in terms of depression, anxiety and pain catastrophizing on pain intensity and function. Lewis et al [ 26 ] stated that pain catastrophizing was one of the strongest independent predictors of persistent pain after TKA.…”

Section: Discussionmentioning

confidence: 99%

Pain catastrophizing and pre-operative psychological state are predictive of chronic pain after joint arthroplasty of the hip, knee or shoulder: results of a prospective, comparative study at one year follow-up

Hardy

Sandiford

Ménigaux

et al. 2022

International Orthopaedics (SICOT)

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Purpose To assess the relationship between pre-operative psychological state, postoperative pain and function one year after total shoulder, hip or knee arthroplasty. Methods Patients undergoing shoulder, hip or knee arthroplasty between March 2014 and November 2015 were included. Pain catastrophizing score (PCS) was determined preoperatively, at six months and at one year follow-up. Joint pain at rest was quantified using a Visual Analogue Scale (0‒100). Depressive symptoms were measured using the Beck Depression Inventory or Geriatric Depression Score, situational anxiety and dispositional anxiety were measured using the State-Trait Inventory and joint function was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index for the hip and knee and Oxford Shoulder Score for the shoulder. Results A total of 266 patients were included (65% female; mean (± SD) age: 71.8 ± 10.3 years; mean body mass index: 27.5 ± 5.0 kg/m2). Pre-operative PCS was significantly correlated with pain > 30/100 at one year and with functional scores, for all joints. Multivariate analysis identified the following variables as risk factors for pain intensity > 30/100 at one year: pre-operative PCS > 20/52 (OR = 3.5 ± 1.1 [95% CI: 1.9‒6.6]; p = 0.0001), trait-anxiety score ≥ 46 (OR = 2.4 ± 0.9 [95% CI: 1.1‒5.2]; p = 0.03), pre-operative pain ≥ 60/100 (OR = 3.2 ± 1 [95% CI: 1.8‒6.1]; p = 0.0001) and pain for at least 3 years (OR = 1.8 ± 0.6 [95% CI: 1‒3.4]; p = 0.04). Conclusion Pre-operative pain catastrophizing and trait-anxiety are risk factors for post-operative pain after shoulder, hip and knee arthroplasty. Trial registration number www.clinicaltrials.gov NCT02361359.

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Investigating the True Effect of Psychological Variables Measured Prior to Arthroplastic Surgery on Postsurgical Outcomes: A P-Curve Analysis

Cited by 7 publications

References 87 publications

Predictive value of quantitative sensory testing for acute and chronic postsurgical pain after total joint arthroplasty: a systematic review

Predictive value of quantitative sensory testing for acute and chronic postsurgical pain after total joint arthroplasty: a systematic review

Tempest in a teacup: An analysis of p-Hacking in organizational research

Pain catastrophizing and pre-operative psychological state are predictive of chronic pain after joint arthroplasty of the hip, knee or shoulder: results of a prospective, comparative study at one year follow-up

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