Clinical potential of pupillary light reflex and heart rate variability parameters as biomarkers for assessing pain relief effects on autonomic function: a prospective longitudinal study

Psychological states affecting initial pupil size changes after olfactory stimulation in healthy participants

Odor perception affects physiological and psychological states. Pupillary light reflex (PLR) parameters can be affected by olfactory stimulation and psychological states, although it remains unclear whether the olfactory stimulation-induced psychological changes can associate with PLR parameter changes. This study aimed to investigate effects of olfactory stimulation-induced psychological changes on PLR parameter changes with repeated measurements. We collected data on six mood subscales of the profile of mood states, and on five PLR parameter measurements from 28 healthy participants. Participants underwent a 10-min olfactory stimulation on different days with six odorants available with the T&T olfactometer. As obtained data were clustered, we used linear mixed-effects models for statistical analyses. The olfactory stimulation using the no-odor liquid did not affect mood states and the initial pupil size (INIT). The sweat odorant worsened all mood subscales including fatigue-inertia (Fatigue)/Vigor-Activity (Vigor), and decreased INIT compared to the no-odor liquid. When comparing INIT responses related to changes in mood subscales between the no-odor liquid and the sweat odorant, worsened states of Fatigue/Vigor were associated with decreased INIT in the sweat odorant. Fatigue/Vigor can be used as mental fatigue indicators. Thus, mental fatigue can be associated with decreased INIT in the olfactory stimulation.

Recommendation of using both initial pupil size and constriction latency in pupillary light reflex as objective indicators reflecting subacute pain-related mental fatigue

A previous study examining clinical subacute pain models under different methodological conditions showed that pain-induced mental fatigue can be associated with decreased initial pupil size (INIT)/shortened constriction latency (LAT) in the pupillary light reflex (PLR). We aimed to investigate the potential of INIT/LAT as objective indicators reflecting mental fatigue under the same methodological conditions. We recruited 118 patients planning to undergo three types of representative otolaryngological head and neck surgery procedures. We used the numerical rating scale (NRS) to assess subjective pain intensity and two mental fatigue-related mood categories of the Profile of Mood States, as well as INIT and LAT measurements (1) in the afternoon one day before surgery (pre1-surgery), (2) in the morning of the day of surgery (pre2-surgery), and (3) in the morning of the day following surgery (post-surgery). We assessed time point-dependent changes using one- or two-way analysis of variance, as well as responses of PLR parameters to mental fatigue using linear mixed-effects models (LMMs). As a result, NRS scores, the two mood categories, as well as LAT and INIT, showed significant time point-dependent changes. In post-hoc analyses, only INIT showed significant changes between the two pre-surgery time points. Thus, INIT values fluctuated even under pain-free conditions due to differences in the time of the day. LMMs demonstrated decreased INIT/shortened LAT related to mental fatigue. All surgical groups showed similar associations between mental fatigue and INIT/LAT findings. As each parameter has advantages and disadvantages, it is recommended to use both INIT and LAT as the indicators.

Comparison of the autonomic nervous system dysfunction between different chronic spine disorders: neck pain versus low back pain

OBJECTIVE

This study aims to compare heart rate variability (HRV) between patients with chronic neck pain and patients with chronic low back pain and to correlate the chronic pain variables with heart rate variability indices.

METHODS

This is a cross-sectional study. We divided the sample into two groups: neck pain (n=30) and low back pain (n=30). We used the Numeric Pain Rating Scale, Neck Disability Index, Roland-Morris Disability Questionnaire, Pain-Related Catastrophizing Thoughts Scale, Tampa Scale of Kinesiophobia, and Pain Self-Efficacy Questionnaire. For heart rate variability analysis, we used the following indices: mean RR, standard deviation of all RR intervals, mean heart rate, root mean square differences of successive RR intervals, triangular index, triangular interpolation of the interval histogram, low-frequency band in arbitrary units and in absolute values, high-frequency band in arbitrary units and in absolute values, standard deviation of the instantaneous beat-to-beat variability (standard deviation 1), long-term standard deviation of continuous RR intervals (standard deviation 2), and Stress Index. We used Student's t-test for comparisons and Spearman's coefficient for correlations.

RESULTS

We observe insignificant values in the differences between the groups. Disability and self-efficacy were correlated with heart rate variability only in patients with chronic neck pain, whereas catastrophizing and kinesiophobia showed greater correlations with heart rate variability in patients with chronic low back pain.

CONCLUSIONS

Autonomic dysfunction of individuals with chronic neck pain, when compared to patients with chronic low back pain, does present insignificant differences.

Decreased initial pupil size and shortened constriction latency due to negative mood states and mental fatigue in clinical subacute pain models

Previous clinical studies on pupillary light reflex parameters showed shortened constriction latency (LAT) and decreased initial pupil size (INIT) due to increased numeric rating scale (NRS) scores, reflecting subjective pain intensity, in subacute pain models. As noxious stimulation causes pupil dilation, decreased INIT (pupil constriction) was an unexpected finding. Pain-related negative moods and mental fatigue might have caused this finding. We aimed to investigate how psychological states affect LAT/INIT in two subacute pain models. For psychological assessment, we used the Profile of Mood States (POMS) and calculated the total mood disturbance (TMD) score using six mood categories. We collected data on NRS scores, POMS-related scores, LAT, and INIT through a longitudinal study. Using linear mixed-effects models, we evaluated the association of TMD scores with NRS scores, LAT, and INIT. Furthermore, we performed subanalyses targeting two mood categories that represent mental fatigue: Fatigue-Inertia (Fatigue) and Vigor-Activity (Vigor). We investigated whether obtained results can be identical in both models. In total, 141 patients were enrolled. Increased NRS scores were associated with increased TMD/Fatigue scores and decreased Vigor scores, being associated with shortened LAT/decreased INIT in both models. Score changes in NRS, TMD, Fatigue, and Vigor indicated that increased subjective pain intensity can be associated with negative mood states, especially mental fatigue. This study revealed that negative moods and mental fatigue induced by acute pain can be associated with shortened LAT/decreased INIT in both models, indicating clinical potential of LAT/INIT as objective indicators reflecting the psychological states for pain assessment.

Clinical potential of pupillary light reflex and heart rate variability parameters as objective indicators of tonsillectomy-induced pain

Establishing objective indicators of subjective pain intensity is important in pain assessment. Pupillary light reflex (PLR) and heart rate variability (HRV) indicate autonomic nervous system (ANS) activity and may serve as pain indicators because pain can affect ANS activity. In this prospective longitudinal study, we aimed to investigate the potential of PLR/HRV parameters as objective indicators of subjective pain intensity after tonsillectomy. Sixty-seven patients undergoing tonsillectomy were enrolled. Subjective pain intensity based on a numeric rating scale (NRS) and eight PLR/HRV parameters were assessed at five time points. We investigated the changes in the NRS values over time. We estimated regression coefficients reflecting parameter changes per unit change in the NRS score using linear mixed-effects models. The mean NRS score was 0 at two pre-surgery time points, 5 on postoperative days (PODs) 1 and 2, and 0 at postoperative week 3. Two parameters (initial pupil size [INIT] and constriction latency [LAT]) showed significant changes on POD1 and POD2 in comparison to baseline data measured at the pre-surgery time point. Among these parameters, only LAT showed no significant changes between POD1 and POD2. Significant regression coefficients with the narrowest 95% confidence intervals were observed for INIT and LAT. Increased NRS scores were associated with decreased INIT and shortened LAT. LAT was a robust indicator of subjective pain intensity. Our patients showed decreased INIT with increased NRS scores, indicating the predominance of the parasympathetic, not sympathetic, tone in pupils. Further studies are required to investigate factors causing this predominance.

Clinical potential of pupillary light reflex parameters as objective indicators reflecting chronic rhinosinusitis-specific quality of life: a 12-month prospective longitudinal study

Pupillary light reflex (PLR) and heart rate variability (HRV) parameters can be objective indicators of chronic rhinosinusitis (CRS) status from the viewpoint of autonomic nervous system activity. This study aimed to establish objective indicators for CRS using the 22-item Sino-Nasal Outcome Test (SNOT-22) and PLR/HRV parameters. Sixty-seven patients were prospectively and longitudinally followed up after surgical treatment. We investigated changes in SNOT-22 scores, representing CRS-specific quality of life (QOL). We prepared two models: linear regression model adjusting clinical factors as predictor variables (model 1) and linear mixed-effects model adjusting clinical factors and among-individual variability (model 2). We compared Akaike's information criterion (AIC) values and regression coefficients. The model with lower AIC values was defined as the better-fit model. Model 2 showed lower AIC values in all parameters (better-fit model). Three parameters showed opposite results between the two models. The better-fit models showed significances in the five PLR parameters but not in any HRV parameters. Among these PLR parameters, constriction latency can be the most robust indicator because of the narrowest 95% confidence intervals. Adjusting the among-individual variability while investigating clinical potential of PLR/HRV parameters to reflect CRS-specific QOL can improve the model fit, thereby reaching robust conclusions from obtained data.

Clinical factors affecting pupillary light reflex parameters: a single-centre, cross-sectional study

PURPOSE

To evaluate the effects of stimulus intensity, aging, sex, smoking and eye symmetry on pupillary light reflex (PLR) parameters.

METHODS

We evaluated 2812 eyes from 1406 subjects in a single-centre, cross-sectional study. PLR data were collected using four different stimulus intensities. We prepared two models for each of the eight PLR parameters, and defined the model with the lowest values of Akaike's information criterion (AIC) as being the best-fit. Model A was a linear regression model without adjustment for among-individual variability, while the Model B linear mixed-effects models (LMMs) were adjusted for among-individual variability. The regression coefficients of the two models were compared.

RESULTS

Model B showed the lowest AIC values for all parameters and the best fit. For light stimulus intensity, age and eye symmetry, the two models yielded similar results for all PLR parameters. For sex and smoking index, some PLR parameters showed the opposite results, i.e., Model A showed significant effects while Model B did not.

CONCLUSION

These results indicate that light stimulus intensity, aging, sex, smoking and eye symmetry are factors that affect PLR parameters. These should be adjusted when evaluating the clinical potential of PLR as a diagnostic tool. In addition, adjusting for among-individual variability due to LMMs can improve the model fit and reduce false positives. This can reveal the association between clinical factors and PLR parameters with increased accuracy.