Biased pain evaluation due to automated heuristics driven by symptom uncertainty may undermine pain treatment; medical evidence moderators are thought to play a role in such circumstances. We explored, in this cross-sectional survey, the effect of such moderators (e.g., nurse awareness of patients’ pain experience and treatment) on the agreement between inpatients’ self-reported pain and nurses’ pain ratings using a numerical rating scale. We assessed the mean of absolute difference, agreement (κ-statistics), and correlation (Spearman rank) of inpatients and nurses’ pain ratings and analyzed congruence categories’ (CCs: underestimation, congruence, and overestimation) proportions and dependence upon pain categories for each medical evidence moderator ( analysis). Pain ratings agreement and correlation were limited; the CCs proportions were further modulated by the studied moderators. Medical evidence promoted in nurses overestimation of low and underestimation of high inpatients’ self-reported pain. Knowledge of the negative influence of automated heuristics driven by symptoms uncertainty and medical-evidence moderators on pain evaluation may render pain assessment more accurate. Biased pain evaluation due to automated heuristics driven by symptom uncertainty may undermine pain treatment; medical evidence moderators are thought to play a role in such circumstances. We explored, in this cross-sectional survey, the effect of such moderators (e.g., nurse awareness of patients’ pain experience and treatment) on the agreement between inpatients’ self-reported pain and nurses’ pain ratings using a numerical rating scale. We assessed the mean of absolute difference, agreement (κ-statistics), and correlation (Spearman rank) of inpatients and nurses’ pain ratings and analyzed congruence categories’ (CCs: underestimation, congruence, and overestimation) proportions and dependence upon pain categories for each medical evidence moderator ( analysis). Pain ratings agreement and correlation were limited; the CCs proportions were further modulated by the studied moderators. Medical evidence promoted in nurses overestimation of low and underestimation of high inpatients’ self-reported pain. Knowledge of the negative influence of automated heuristics driven by symptoms uncertainty and medical-evidence moderators on pain evaluation may render pain assessment more accurate.

Patients undergoing elective primary total hip replacement and spinal anesthesia may encounter significant hemodynamic instability Objective: The study is aimed at observing the haemodynamic modifications after spinal anaesthesia during total hip replacement in patients managed to "preload independence" with goal directed fluid therapy (GDFT) and monitored non-invasively with Clearsight. Thirty patients, aged 50-80 years, with an American Society of Anaesthesiologists' (ASA) score II-III, undergoing elective primary total hip replacement and spinal anaesthesia were enrolled. Patients were monitored with the EV1000 platform and the Clearsight finger-cuff and managed with a goal directed fluid therapy. The 79% of the population showed preload independence at baseline. After spinal, the 93% did not show a significant mean arterial pressure reduction. In our population, 79% reported a decrease >10% of the stroke volume during surgery, while 66% in the Recovery Room. Patients showed an improvement in mean arterial pressure, systemic vascular resistances indexed (SVRI), stroke volume (SV) and stroke volume indexed (SVI) at spinal resolution compared to baseline. Our cohort population showed hemodynamic stability throughout the study period, with increased SV and decreased SVRI at spinal resolution compared to basal values. Further randomized prospective studies are advocated in the same setting.

Iontophoretic transdermal fentanyl for the management of acute perioperative pain in hospitalized patients. . ???aop.label???. doi: 10.1517/14656566.2016.1146684

Objectives: Variable prevalence and treatment of breakthrough pain (BTP) in different clinical contexts are partially due to the lack of reliable/validated diagnostic tools with prognostic capability. We report the statistical basis and performance analysis of a novel BTP scoring system based on the naïve Bayes classifier (NBC) approach and an 11-item IQ-BTP validated questionnaire. This system aims at classifying potential BTP presence in three likelihood classes: “High,” “Intermediate,” and “Low.” Methods: Out of a training set of n=120 mixed chronic pain patients, predictors associated with the BTP likelihood variables (Pearson’s χ² and/or Fisher’s exact test) were employed for the NBC planning. Adjusting the binary classification to a three–likelihood classes case enabled the building of a scoring algorithm and to retrieve the score of each predictor’s answer options and the Patient’s Global Score (PGS). The latter medians were used to establish the NBC thresholds, needed to evaluate the scoring system performance (leave-one-out cross-validation). Results: Medians of PGS in the “High,” “Intermediate,” and “Low” likelihood classes were 3.44, 1.53, and −2.84, respectively. Leading predictors for the model (based on score differences) were flair frequency (∆S=1.31), duration (∆S=5.25), and predictability (∆S=1.17). Percentages of correct classification were 63.6% for the “High” and of 100.0% for either the “Intermediate” and “Low” likelihood classes; overall accuracy of the scoring system was 90.9%. Conclusion: The NBC-based BTP scoring system showed satisfactory performance in classifying potential BTP in three likelihood classes. The reliability, flexibility, and simplicity of this statistical approach may have significant relevance for BTP epidemiology and management. These results need further impact studies to generalize our findings.

Background: Differential diagnosis of low back pain (LBP) is complex and a prominent issue at all health-care levels; guidance may come from patients’ history cues and clinical examination signs. Human and animal studies report that diagnosis of lumbar radicular pain (LRP) may come from evaluating subjective responses of injured lumbar nerves to a strain applied at the buttock. The Buttock Applied Strain (BUAS-test) test may guide the differential diagnosis of LBP. Following an ex-adiuvantibus criterion, clinical improvement of LRP, diagnosed with the BUAS-test and congruently treated, may support this test diagnostic ability. Methods: Among 258 LRP patients, who, upon first visit (V1), tested positive on the BUAS-test (with/without positive Straight Leg Raising Test, SLRT), the effect of gabapentin prescription on painDETECT (PD) questionnaire and Brief Pain Inventory (BPI) outcomes was quantified in the follow-up visit (V2). To support BUAS-test diagnostic ability, we hypothesized that, at V2, >50% of the sample would present negative PD outcome, significant ( t-test) and ⩾2 points V2-V1 differences for each of the BPI-item’s score. We used multinomial logistic regression (MLR) and χ ² analyses to evaluate the PD-V2 outcomes’ dependence upon independent variables. Results: Of the sample, 77% reported a negative PD-V2 outcome. V2-V1 differences of all BPI items were significant and >2 points. PD-V2 outcomes showed significant associations with SLRT-V1 and PD-V1, respectively, but not with gender, age group or pain site. MLR showed a significant relationship between SLRT-V1 and PD-V2 outcomes. Conclusion: Among LRP patients, diagnosed by the BUAS-test and treated with gabapentin, all prespecified endpoints were reached. These results may be considered a piece of ex-adiuvantibus evidence for the BUAS-test ability to diagnose LRP. While positive BUAS-test implies potential LRP, the co-presence with positive SLRT may imply a severer LRP condition. Further prospective research, in different settings and direct clinical measures, is needed.