Abstract
Aims
Compensatory mechanisms in heart failure (HF) are triggered to maintain adequate cardiac output. Among them, hyperactivation of the sympathetic nervous system (SNS) is one of the main ones and carries a worse prognosis. The pupillary reflex depends on the SNS, and we can evaluate it through pupillometry. The aim of the study was to compare the differences in pupillary reflex between patients with acute HF and controls and to analyse whether these differences in pupillary reflex may offer a new and easy prognostic factor in such patients.
Methods and results
We prospectively and consecutively included 107 patients admitted with decompensated HF. Quantitative pupillometry was performed with the NeuroOptics pupillometry during the first 24 h after admission and prior to discharge. The results were compared with those of a group of 100 healthy volunteers who also underwent pupillometry. The maximum baseline pupil size (MBPS) and the minimum pupil diameter (MPD) were measured. Patients with decompensated HF have a higher MBPS (3.64 ± 0.81) and higher MPD (2.60 ± 0.58) than HF patients at discharge and in the control group (P‐value = 0.01 and 0.01, respectively). Also, HF patients presented an improvement in pupillometric values at discharge [MBPS (3.47 ± 0.79) and MPD (2.51 ± 0.58)] and showed no differences compared with the control group [MBPS (3.34 ± 0.82) and MPD (2.40 ± 0.53)] (P‐value = 0.19 and 0.14, respectively). In addition, MBPS provides a good independent predictor of in‐hospital and 1 month mortality in patients admitted with HF. Six patients (5.61%) died during hospital admission, and 11 patients (10.2%) died in the first month after discharge. Also, four patients (3.74%) were readmitted within 1 month of discharge. The receiver operating characteristic (ROC) curve for predicting in‐hospital mortality through MBPS was 0.823. No patient with an MBPS < 3.7 mm died. The ROC curve for predicting combined mortality or readmission within the first month for MBPS was 0.698.
Conclusions
Pupillometry may be a new, non‐invasive, and simple tool to determine the status of SNS, help in the prognostic stratification of acute HF patients, and improve therapeutic management.
Keywords: Pupillometry, Sympathetic nervous system, Diagnostic procedure on eye, Heart failure, Clinical finding
Introduction
Heart failure (HF) is a clinical syndrome characterized by the heart's inability to maintain an adequate cardiac output to satisfy the metabolic demands of the organism. 1 In reaction to this circumstance, a cascade of neurohormonal compensatory processes is initiated in an attempt to sustain sufficient cardiac output. 2 One of the main compensatory mechanisms is the hyperactivation of the sympathetic nervous system (SNS) with the consequent release of adrenaline and noradrenaline. 3 , 4 These neurohormones exert an influence on the pupillary reflex by interacting with the adrenergic receptors located within the iris dilator muscles, inducing pupillary dilation (mydriasis).
HF stands as the foremost cause of hospitalization among individuals older than 65, representing 1–2% of total hospital admissions in Western countries. 5 , 6 This condition affects over 60 million people globally and currently constitutes a worldwide pandemic, incurring substantial healthcare expenditures and diminishing patients' quality of life. 7 , 8
Given the widespread prevalence and implications of HF, its prompt recognition and effective management are imperative. A multidisciplinary approach, encompassing the collaborative efforts of various specialized healthcare professionals, is indispensable for better care. Additionally, it is not uncommon for HF patients to undergo episodes of clinical exacerbation, a phenomenon known as acute decompensation. In fact, approximately one in six HF patients experiences such decompensation within the initial 18 months after diagnosis. It is noteworthy that as the number of prior decompensations increases, the likelihood of recurrence tends to rise accordingly. 9
The pupillary reflex describes the initial constriction followed by subsequent dilation of the pupil in response to light due to the antagonistic actions of the iris sphincter and dilator muscles. As these muscles are innervated by the parasympathetic nervous system and the SNS, respectively, pupillary reflex parameters can be used as indicators of sympathetic or parasympathetic activity.
To date, there is no tool available to non‐invasively measure the status of the SNS (a pivotal player in the pathophysiology of HF). The exam of the pupillary reflex could be considered a new non‐invasive tool for better control of such patients.
Pupillometry is a simple, non‐invasive, cost‐effective, and easy‐to‐handle technique that allows the study of the relationship between SNS dysfunction and changes in pupillary diameter. Additionally, it enables the acquisition of objective and reproducible measurements, making it a promising tool for the early detection and diagnosis of diseases. 10
The aim of this study was to compare the pupillary reflex response of patients diagnosed with acute HF with a control cohort of healthy subjects as a marker of SNS activity in these patients. Furthermore, it aims to assess the role of the pupillary reflex as a prognostic marker in HF.
Methods
This study is longitudinal and prospective, performing pupillometry on all consecutive patients admitted with acute HF within the initial 24 h of admission. Additionally, follow‐up pupillometry was carried out on these patients prior to discharge.
According to European guidelines, admission for acute HF was considered when patients presented with a rapid onset of symptoms such as dyspnoea or orthopnoea, as well as crackles or oedema resulting from structural or functional cardiac abnormalities.
For determining the sample size, we leaned on the study conducted by Catai et al., as they were the only ones to have previously explored the pupillary reflex in patients with HF with a sample of 870 patients with acute HF. 11 In this study, the standard deviation of the pupil area was around 5 mm2. To detect differences of 3 mm2 between groups, with a two‐sided significance level of 5% and a power of 80%, a sample size of 87 patients was calculated. We included 100 patients to compensate for possible losses in follow‐up. Additionally, in this study population, around 50% of patients experienced events. According to the rule of 10 events per variable, this would allow the inclusion of 5 variables in the multivariate analysis.
Patient recruitment began in September 2022 and concluded in January 2023. The study included 107 patients with acute HF over 18 years of age who were consecutively admitted to the cardiology department at Ramón y Cajal Hospital. Patients with novo or chronic acute HF were included. Cardiogenic shock, acute myocardial infarction, and concomitant infections were excluded from our sample. Follow‐up was done 1 month after discharge.
Patients exhibiting structural and functional abnormalities of the eye globe that may potentially affect the pupillary reflex (ocular prostheses, traumas, optic neuropathies, macular degenerations with low visual acuity, and cataract surgery) were excluded. Likewise, patients with autonomic dysfunctions that influence autonomic nervous system function and those with neurological pathologies that might disrupt the pupillary reflex pathway were also excluded.
In addition to patients diagnosed with HF, and as one of the primary objectives of the study was to assess whether the pupillary reflex response in HF patients differs from that in patients without HF, a control group without heart disease was also included. Pupillometric assessments were also performed in this control group, which consisted of 100 healthy volunteers free from heart disease, ophthalmological conditions, or any treatment or conditions that could potentially impact the pupillary reflex.
The NeurOptics NPi‐200 pupillometer was used to perform quantitative pupillometry on both cases and controls.
To ensure consistent results, pupillometry was conducted under uniform ambient lighting conditions for both groups, thus mitigating any potential influence stemming from variations in lighting conditions. All measurements were performed by the same observer.
The variables measured with the NeurOptics NPi‐200 pupillometer included maximum baseline pupil size (MBPS), minimum pupil diameter (MPD), percentage change between the two, latency time, constriction velocity, dilation velocity, and the pupillary neurological index that analyses the normal pupillary reflex response.
Different statistical tests were used to study the correlation between variables, depending on the data distribution. For variables with a normal distribution, the Pearson correlation test was used. For the variables that did not follow a normal distribution, we chose to use the Spearman correlation test. The receiver operating characteristic (ROC) curve was used to identify the optimal cut‐off value for the pupil parameters in order to detect events (readmission or mortality). For all calculations, a statistically significant difference was assumed if the P‐value was <0.05.
We declare that our study complies with the Declaration of Helsinki. The Ramón y Cajal Hospital and University of Alcalá ethics committee had approved the research protocol, and informed consent had been obtained from the subjects.
Results
A total of 107 patients (214 eyes) diagnosed with decompensated acute HF were prospectively and consecutively admitted to the cardiology ward and underwent quantitative pupillometry between September 2022 and January 2023. Finally, a total of 210 eyes were studied, with two right eyes and two left eyes excluded from the analysis due to the presence of ophthalmological pathology (ocular prostheses). These exclusions were made to ensure that the analysed data were limited to eyes without alterations or conditions that could influence the study's results.
In order to analyse differences between healthy subjects and HF patients, we performed pupillometry on patients with HF and controls without cardiac or ophthalmological pathology matched by age, sex, and clinical conditions to avoid bias.
Demographic data, clinical characteristics of the primary cardiovascular risk factors, and pharmacological treatment for the matched cases and controls cohort are detailed in Table 1 . No statistically significant differences were found.
Table 1.
Clinical and demographic characteristics of heart failure vs. control groups
| Variables | Heart failure group | Control group | P‐value |
|---|---|---|---|
| Mean ± SD | Mean ± SD | ||
| Age | 76.83 ± 8.59 | 75.90 ± 11.09 | 0.54 |
| Hypertension, n (%) | 75 (86.2%) | 72 (82.75%) | 0.53 |
| Atrial fibrillation, n (%) | 3 (3.44%) | 0 (0%) | 0.08 |
| Diabetes, n (%) | 24 (27.58%) | 24 (27.58%) | 1 |
| Chronic kidney disease, n (%) | 6 (6.89%) | 3 (3.44%) | 0.31 |
| Sacubitril/valsartan | 3 (3.4%) | 0 | 0.08 |
| Antialdosteronics | 6 (6.9%) | 9 (10.3%) | 0.42 |
| Beta‐blockers | 33 (37.9%) | 30 (34.5%) | 0.64 |
| Angiotensin‐converting enzyme inhibitors | 24 (27.6%) | 15 (17.2%) | 0.10 |
| Angiotensin antagonists | 12 (13.8%) | 18 (20.7%) | 0.23 |
| Diuretics | 36 (41.4%) | 36 (41.4%) | 1.00 |
| Calcium antagonists | 21 (24.1%) | 21 (24.1%) | 1.00 |
SD, standard deviation.
The measures of heart rate, blood pressure, and blood tests of HF patients were also collected, as shown in Table 2 .
Table 2.
Clinical and analytic characteristics of a heart failure sample
| Clinical variable | Mean ± SD |
|---|---|
| Heart rate (b.p.m.) | 96.5 ± 37.47 |
| Systolic blood pressure (mmHg) | 119.5 ± 23.33 |
| Diastolic blood pressure (mmHg) | 61.5 ± 2.12 |
| Ejection fraction (%) | 38.9 ± 10.04 |
| Oxygen saturation | 93.11 ± 4.91 |
| BNP | 1422.66 ± 1342 |
| Creatinine | 1.53 ± 1.26 |
| Haematocrit | 38.7 ± 7.06 |
| Sodium | 141 ± 45 |
| Potassium | 4.25 ± 0.61 |
SD, standard deviation.
The most frequent aetiology of HF was ischaemic cause in 33.60% of patients, valvular cause in 29.9% of patients, other aetiologies (toxicity, myocarditis, arrhythmias, etc.) in 23.40% of patients, and finally, cardiomyopathies in 13% of patients.
Pupillometric assessments were done in HF patients within the initial 24 h of hospital admission and shortly before their discharge.
As no significant differences were found between the pupillary measurements of the right and left eyes, both in the control group and in the cases upon admission and discharge, it was decided to obtain the mean of both eyes together to simplify the data.
Patients admitted with decompensated HF had a larger baseline pupil diameter, an increased pupil diameter during pupillary constriction following the light stimulus, and an increased pupillary dilation velocity.
However, the values of the pupillometric measurements in patients at discharge compared with controls did not show statistically significant differences in terms of basal pupillary diameter and minimum pupillary diameter. These data support the hypothesis that patients with decompensated HF have SNS hyperactivation that promotes mydriasis (pupillary dilation) over miosis (pupillary constriction). HF patients presented with a larger baseline pupil diameter and a larger diameter during constriction upon admission, indicating that patients with HF initially had greater mydriasis compared with the controls.
Furthermore, the absence of statistically significant differences between patients at discharge and controls showed that these patients were discharged with better control of their disease. This fact could help improve the therapeutic management of patients with HF (Table 3 ).
Table 3.
Pupillometric measurements for controls vs. heart failure patients during admission and controls vs. heart failure patients at discharge
| Group | Mean ± SD | P‐value | Group | Mean ± SD | P‐value | |
|---|---|---|---|---|---|---|
| NPi | Control | 4.38 ± 0.45 | 0.49 | Control | 4.38 ± 0.45 | 0.31 |
| HF cases admission | 4.34 ± 0.60 | HF cases discharge | 4.43 ± 0.33 | |||
| MBPS | Control | 3.34 ± 0.82 | <0.01* | Control | 3.34 ± 0.82 | 0.19 |
| HF cases admission | 3.64 ± 0.81 | HF cases discharge | 3.47 ± 0.79 | |||
| MPD | Control | 2.40 ± 0.53 | <0.01* | Control | 2.40 ± 0.53 | 0.14 |
| HF cases admission | 2.60 ± 0.58 | HF cases discharge | 2.51 ± 0.58 | |||
| PC | Control | 27.5 ± 8.43 | 0.41 | Control | 27.5 ± 8.43 | 0.30 |
| HF cases admission | 28.2 ± 7.48 | HF cases discharge | 28.5 ± 7.59 | |||
| VelCons | Control | 1.78 ± 0.68 | 0.17 | Control | 1.78 ± 0.68 | 0.15 |
| HF cases admission | 1.89 ± 0.80 | HF cases discharge | 2.25 ± 3.36 | |||
| VelMaxCons | Control | 2.70 ± 1.03 | 0.60 | Control | 2.70 ± 1.03 | 0.65 |
| HF cases admission | 2.76 ± 1.14 | HF cases discharge | 2.65 ± 0.89 | |||
| Lat | Control | 0.25 ± 0.04 | 0.98 | Control | 0.25 ± 0.04 | 0.08 |
| HF cases admission | 0.25 ± 0.04 | HF cases discharge | 0.32 ± 0.36 | |||
| VelDil | Control | 0.83 ± 0.30 | <0.001* | Control | 0.83 ± 0.30 | 0.01 |
| HF cases admission | 0.99 ± 0.31 | HF cases discharge | 0.94 ± 0.29 |
HF, heart failure; Lat, latency time; MBPS, maximum baseline pupil size; MPD, minimum pupil diameter; NPi, pupillary neurological index; PC, percentage change; SD, standard deviation; VelCons, constriction velocity; VelDil, dilation velocity; VelMaxCons, maximum constriction velocity.
Statistically significant difference of the results.
We also did not see any significant pupillometric value differences between coronary artery disease and HF patients vs. HF due to other aetiologies (valvulopathy and cardiomyopathy). The results are shown in Table 4 .
Table 4.
Pupillometric values in heart failure and coronary artery disease patients vs. non‐coronary artery disease patients
| HF aetiology | Admission | Discharge | |||
|---|---|---|---|---|---|
| x̄ ± σ | P‐value | x̄ ± σ | P‐value | ||
| NPi | Ischaemic | 4.32 ± 0.48 | 0.2 | 4.44 ± 0.31 | 0.4 |
| Cardiomyopathy | 4.54 ± 0.28 | 4.47 ± 0.19 | |||
| Valvulopathy | 4.38 ± 0.40 | 4.40 ± 0.29 | |||
| Other | 4.36 ± 0.50 | 4.26 ± 0.69 | |||
| MBPS | Ischaemic | 3.55 ± 0.81 | 0.8 | 3.28 ± 0.76 | 0.6 |
| Cardiomyopathy | 3.55 ± 0.88 | 3.12 ± 0.71 | |||
| Valvulopathy | 3.51 ± 0.75 | 3.18 ± 0.77 | |||
| Other | 3.49 ± 1.05 | 3.17 ± 0.83 | |||
| MPD | Ischaemic | 2.54 ± 0.57 | 0.8 | 2.48 ± 0.59 | 0.6 |
| Cardiomyopathy | 2.54 ± 0.58 | 2.39 ± 0.57 | |||
| Valvulopathy | 2.50 ± 0.50 | 2.36 ± 0.44 | |||
| Other | 2.52 ± 0.67 | 2.43 ± 0.64 | |||
| PC | Ischaemic | 25.76 ± 7.95 | 0.7 | 26.26 ± 7.43 | 0.3 |
| Cardiomyopathy | 28.14 ± 6.81 | 25.08 ± 6.75 | |||
| Valvulopathy | 27.42 ± 8.13 | 25.17 ± 8.73 | |||
| Other | 26.44 ± 8.01 | 23.40 ± 7.05 | |||
| VelCons | Ischaemic | 1.44 ± 0.58 | 0.3 | 1.51 ± 0.56 | 0.7 |
| Cardiomyopathy | 1.47 ± 0.47 | 1.47 ± 0.50 | |||
| Valvulopathy | 1.73 ± 0.80 | 1.54 ± 0.71 | |||
| Other | 1.52 ± 0.71 | 1.33 ± 0.51 | |||
| VelMaxCons | Ischaemic | 2.22 ± 0.86 | 0.5 | 2.21 ± 0.79 | 0.5 |
| Cardiomyopathy | 2.35 ± 0.86 | 2.18 ± 0.79 | |||
| Valvulopathy | 2.63 ± 1.22 | 2.27 ± 1.09 | |||
| Other | 2.38 ± 1.08 | 1.99 ± 0.74 | |||
| Lat | Ischaemic | 0.28 ± 0.05 | 0.1 | 0.33 ± 0.23 | 0.6 |
| Cardiomyopathy | 0.29 ± 0.03 | 0.32 ± 0.07 | |||
| Valvulopathy | 0.27 ± 0.05 | 0.30 ± 0.15 | |||
| Other | 0.27 ± 0.03 | 0.28 ± 0.04 | |||
| VelDil | Ischaemic | 0.80 ± 0.29 | 0.9 | 0.86 ± 0.23 | 0.4 |
| Cardiomyopathy | 0.90 ± 0.22 | 0.78 ± 0.19 | |||
| Valvulopathy | 0.91 ± 0.28 | 0.81 ± 0.30 | |||
| Other | 0.82 ± 0.27 | 0.81 ± 0.27 | |||
HF, heart failure; Lat, latency time; MBPS, maximum baseline pupil size; MPD, minimum pupil diameter; NPi, pupillary neurological index; PC, percentage change; VelCons, constriction velocity; VelDil, dilation velocity; VelMaxCons, maximum constriction velocity.
Another objective was to evaluate the role of the pupillary reflex as a prognostic marker of the disease.
Six patients died in‐hospital during admission (5.61%), and 11 patients died in the first month after discharge (10.2%). Four patients (3.74%) were readmitted within 1 month of discharge.
The ROC curve for predicting in‐hospital mortality through MBPS was 0.823. Among the patients who passed away, all had a baseline pupillary diameter at admission of ≥3.8 mm. No patient with an MBPS < 3.7 mm died. A value of 3.8 [area under the curve (AUC) 0.82] demonstrated a sensitivity of 100% and a specificity of 71.1% in detecting events (Figure 1 ).
Figure 1.
Receiver operating characteristic (ROC) curve in‐hospital and 1 month mortality in heart failure patients.
The ROC curve for predicting combined mortality or readmission within the first month through MBPS was 0.698 (Figure 2 ).
Figure 2.
Receiver operating characteristic (ROC) curve combined mortality and readmission in heart failure patients.
Furthermore, we used the maximum baseline pupillary size to search for correlations with other clinical, laboratory, and echocardiographic parameters reflecting SNS activity, systolic dysfunction, and diastolic dysfunction. No statistically significant correlations were found. Heart rate was the variable with which pupillary size correlated the most, and it had a weak correlation (+0.24). Therefore, we can say that the basal maximum size is an independent prognostic marker of mortality.
In order to analyse the possible influence of beta‐blockers on the pupillometric data, we compared the pupil‐registered values of patients taking such medications with those of non‐treated patients.
There were no significant differences between both groups, even considering the beta‐blocker administered. This is explained by the different adrenergic receptors present in the heart (beta) and iris (alpha) (Table 5 ).
Table 5.
Pupillometric values between heart failure patients and controls with and without beta‐blocker treatment
| Group | Mean ± SD | P‐value | Group | Mean ± SD | P‐value | Group | Mean ± SD | P‐value | |
|---|---|---|---|---|---|---|---|---|---|
| NPi | Controls without BB | 4.40 ± 0.40 | 0.14 | Admission without BB | 4.41 ± 0.44 | 0.49 | Discharge without BB | 4.44 ± 0.35 | 0.23 |
| Controls with BB | 4.6 ± 0.41 | Admission with BB | 4.37 ± 0.53 | Discharge with BB | 4.37 ± 0.46 | ||||
| MBPS | Controls without BB | 3.21 ± 0.72 | 0.23 | Admission without BB | 3.49 ± 0.89 | 0.79 | Discharge without BB | 3.18 ± 0.90 | 0.73 |
| Controls with BB | 2.96 ± 0.63 | Admission with BB | 3.53 ± 0.86 | Discharge with BB | 3.22 ± 0.72 | ||||
| MPD | Controls without BB | 2.35 ± 0.46 | 0.04 | Admission without BB | 2.54 ± 0.64 | 0.71 | Discharge without BB | 2.41 ± 0.65 | 0.98 |
| Controls with BB | 2.08 ± 0.36 | Admission with BB | 2.51 ± 0.55 | Discharge with BB | 2.41 ± 0.52 | ||||
| PC | Controls without BB | 26.1 ± 8.45 | 0.52 | Admission without BB | 26.00 ± 7.6 | 0.25 | Discharge without BB | 25.3 ± 8.87 | 0.79 |
| Controls with BB | 28.2 ± 10.4 | Admission with BB | 27.04 ± 8.71 | Discharge with BB | 24.9 ± 7.87 | ||||
| VelCons | Controls without BB | 1.69 ± 0.71 | 0.68 | Admission without BB | 1.56 ± 0.70 | 0.89 | Discharge without BB | 1.47 ± 0.64 | 0.17 |
| Controls with BB | 1.60 ± 0.66 | Admission with BB | 1.55 ± 0.72 | Discharge with BB | 1.86 ± 3.00 | ||||
| VelMaxCons | Controls without BB | 2.57 ± 1.00 | 0.66 | Admission without BB | 2.36 ± 1.03 | 0.68 | Discharge without BB | 2.17 ± 0.93 | 0.87 |
| Controls with BB | 2.42 ± 1.09 | Admission with BB | 2.42 ± 1.12 | Discharge with BB | 2.19 ± 0.91 | ||||
| Lat | Controls without BB | 0.26 ± 0.04 | 0.30 | Admission without BB | 0.27 ± 0.05 | 0.77 | Discharge without BB | 0.58 ± 2.58 | 0.40 |
| Controls with BB | 0.27 ± 0.03 | Admission with BB | 0.28 ± 0.05 | Discharge with BB | 0.32 ± 0.29 | ||||
| VelDil | Controls without BB | 0.87 ± 0.30 | 0.24 | Admission without BB | 0.86 ± 0.33 | 0.58 | Discharge without BB | 0.83 ± 0.31 | 0.51 |
| Controls with BB | 0.79 ± 0.15 | Admission with BB | 0.84 ± 0.29 | Discharge with BB | 0.80 ± 0.28 |
BB, beta‐blocker; Lat, latency time; MBPS, maximum baseline pupil size; MPD, minimum pupil diameter; NPi, pupillary neurological index; PC, percentage change; SD, standard deviation; VelCons, constriction velocity; VelDil, dilation velocity; VelMaxCons, maximum constriction velocity.
Discussion
This study provides evidence that patients with decompensated HF exhibit altered pupillometric values compared with controls. Patients with HF upon admission showed a larger maximum baseline pupillary diameter, a greater minimum pupillary diameter, and an increased pupillary dilation velocity.
These findings could be explained by the fact that in decompensated HF, the low cardiac output situation favours hyperactivation of the SNS with consequent catecholaminergic release of norepinephrine, which would stimulate the alpha‐adrenergic receptors of the iris, resulting in pupillary mydriasis (dilation) over miosis (constriction).
Patients with HF at discharge did not exhibit statistically significant differences in terms of pupillary diameter when compared with the control group. Essentially, when the acute phase of the disease is under control, HF patients do not differ from healthy individuals. Intrahospital management likely plays a role in regulating sympathetic activation and catecholaminergic secretion in the heart, which explains the absence of differences between discharged patients and controls. Pupillometry may prove valuable in the intrahospital management of these patients and in controlling the acute phase of the disease.
To date, the pupillary reflex has not been previously considered a prognostic factor. This reflex can be non‐invasively assessed and measured, and it can be used as an important marker of risk.
In our study, we obtained an AUC to predict in‐hospital mortality through the maximum baseline pupillary diameter of 0.823. A value above 3.8 for MBPS had 100% sensitivity in predicting in‐hospital mortality. Therefore, MBPS is a promising prognostic marker for mortality in patients with HF.
MBPS was an independent prognostic marker of mortality in our sample. Heart rate was the variable with which pupillary size correlated the most, and it had a weak correlation (+0.24).
Heart rate and pupillary size are influenced by SNS activity. Classically, tachycardia has been defined as a marker of a worse prognosis for HF. Tachycardia increases oxygen consumption, reduces ventricular filling time, and decreases cardiac output. In our patients with HF, the mean heart rate was 96.5 ± 37.47 b.p.m. We saw a weak positive correlation of +0.24 (the larger the baseline pupil size, the higher the heart rate) in patients with HF, which would support that both variables are influenced by the SNS.
Even if there is a clear correlation, it is weak due to the fact that heart rate can be easily influenced by other factors such as standing or supine position, dehydration, daily physical activity, acute emotions, breathing mechanics, and movement. 11 In addition, heart rate is influenced by cardiac abnormalities and variables such as atrial fibrillation, preload and afterload, and specific drugs such as beta‐blockers that do not affect the iris sphincter muscle.
Finally, the pupillary reflex can also be used to predict readmissions due to cardiac decompensation. The ROC curve for predicting combined mortality or readmission within the first month through MBPS was 0.698.
The ability of the pupillary reflex to predict readmissions due to cardiac decompensation could have a significant impact on patient care. Being able to anticipate readmissions would allow for risk stratification of patients, implementation of earlier or intensified therapeutic strategies, and personalized decision‐making in their follow‐up, ultimately improving quality of life, reducing morbidity and mortality, and decreasing the burden of hospital readmissions.
Up to the present time, this represents the first prospective study analysing the pupillary reflex in patients with HF in comparison with healthy subjects. Nozaki et al. have been the sole researchers to have previously investigated the pupillary reflex in HF. 12 , 13 However, it is a retrospective study. On the other hand, another clear limitation is that pupillometry was performed 7 days after patients were discharged. It is conceivable that the in‐hospital therapeutic management of patients could have influenced the results. Additionally, the group with a smaller pupillary area consisted of a higher percentage of diabetic patients, which is a potential cause of autonomic dysfunction. Moreover, it represents a younger cohort and is composed of an Asian population. Lastly, the study only takes into account the baseline pupillary area without considering other pupillometric variables of interest.
One of the main limitations of our study is the lack of standardized guidelines regarding pupillometric methodology. There are no universal rules concerning the conditions for measuring the pupillary reflex. This could hinder the comparison of results with other studies. In our study, we used the same conditions during the exam that we believe are crucial for interpreting results. Additionally, all cardiac patients with any ocular conditions that could potentially alter the pupillary reflex had to be excluded. Studies with a larger sample size are needed to better generalize the results.
Conclusions
In conclusion, pupillometry is a non‐invasive, portable, automatic, cost‐effective, and easy‐to‐handle technique that allows for objective and reproducible measurements of pupillary reflex dynamics. Pupillometry could be considered a new, simple, and valuable tool for evaluating the status of the SNS in patients with acute HF. Patients admitted with decompensated HF showed a larger maximum baseline pupillary diameter, a greater pupillary diameter during constriction following the light stimulus, and an increased pupillary dilation velocity compared with controls. This supports the hypothesis that in patients with decompensated HF, the condition of reduced cardiac output promotes hyperactivation of the SNS. Furthermore, pupillometry could greatly assist in improving the therapeutic management of patients with HF. The ability of the pupillary reflex to predict mortality and readmissions due to cardiac decompensation would allow for risk stratification of patients, implementation of earlier or intensified therapeutic strategies, and personalized decision‐making in their follow‐up, ultimately improving quality of life, reducing morbidity and mortality, and decreasing the burden of hospital readmissions.
In addition, further longitudinal studies would be required to track patients over time and assess whether changes in the pupillary reflex correlate with changes in cardiac function or long‐term prognosis.
Conflict of interest
The authors declare that there is no conflict of interest.
Funding
The authors did not receive funding to write and publish this case.
Zamorano, M. , Monteagudo, J. M. , González, E. , Rayo, I. , Fernández, S. , Castillo, M. , Zhou, Q. , de la Villa, P. , and Zamorano, J. L. (2024) Pupil reflex as a marker of activity and prognosis in heart failure: a longitudinal and prospective study. ESC Heart Failure, 11: 1947–1954. 10.1002/ehf2.14746.
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