Patients
This prospective observational study was conducted at Jinling Hospital, which is a large Chinese tertiary-level teaching hospital. The hospital ethics committee approved this trial (2022NZKY-013-01), which was registered with the Chinese Clinical Trial Registry (registration number: ChiCTR2200057164, registration date:01/03/2022). All participating patients provided written informed consent.
Eligible patients were individuals 18–64 years of age with an ASA physical status of I-II who were scheduled to undergo elective surgery under general anesthesia. Patients were excluded if they had a history of eye diseases, eye surgery, neuromuscular dysfunction, diabetes mellitus, hypertension, thyroid dysfunction, pupil malformations, used drugs that impact pupil size, used alpha or beta-blockers, had a scheduled operative duration of < 30 minutes, were scheduled to undergo neurosurgery, or were undergoing surgical procedures in the lateral or prone position. If patients experienced failed arterial catheterization, secondary tracheal intubation, a loss of mean arterial pressure (MAP) or heart rate (HR) data, or a loss of pupil data, they were withdrawn from testing.
Pupillary measurements
All patients waited in the anesthetic preparation room before entering the operating room and receiving anesthesia induction. Patients were instructed to rest in the supine position for 10 minutes in the preparation room before receiving pupillary examinations. Between 9 and 12 AM, a single researcher tested all pupillary light reflex responses in order to reduce the potential effect of diurnal variation on the results. Pupillary measurements were made with an infrared pupil camcorder (LRCP 10910; resolution: 1080p; focal length: 8 mm; angle: 45° undistorted) [15, 16] that was positioned 25 cm above the right pupil and captured images at 30 frames/s. Light reflection was achieved using a yellow LED light source (color temperature: 5000 K) at an equivalent height. Camcorder video data were continuously relayed to a computer during the measurement process, with image data being processed in an automated manner using Adobe Premiere Pro, v 14.0.0 (Adobe, USA). Pupil parameters in the resultant images were measured by two researchers using ImageJ v 1.51 J8 (National Institutes of Health, USA), which was able to enhance pupillary contours in processed images in an automated manner with a 0.1 mm measurement sensitivity (Fig. 1).
After computer recordings were complete, the Baseline Pupil Diameter (BPD), Minimum Pupil Diameter (MPD), Pupil Constriction Latency (PCL), Pupil Constriction Time (PCT); Average Constriction Velocity (ACV) [\(ACV=\frac{BPD- MPD}{PCT}\)], Maximum Constriction Velocity (MCV), and Constriction Ratio (%) [\(CR=\left(\frac{MPD}{BPD}\right)\ast 100\%\)] were recorded.
Anesthesia management
All patients fasted beginning at 10 PM on the day before the scheduled surgery, and no patients had been premedicated. All patients were subjected to electrocardiogram, respiratory rate, blood pressure, pulse, airway pressure, and end-tidal CO2 monitoring. Patients were initially infused with Ringer’s acetate solution (10 ml/kg/h), and induction was administered at 5 min post-arterial puncture with all patients undergoing a standard rapid sequence induction: 0.04 mg/kg midazolam, 0.3 μg/kg sufentanil, 2 mg/kg propofol and cisatracurium 0.15 mg/kg. At 3 minutes following the administration of the muscle relaxant, an experienced anesthesiologist performed endotracheal intubation using a Disposcope endoscope.
Blood pressure measurements
All patients underwent invasive blood pressure monitoring via non-operative radial artery catheterization. Following admission to the operating room, an experienced anesthesiologist inserted a 22-gauge arterial catheter (B. Braun, Germany) into each patient, with puncture sites being selected using the 1–2 cm of the styloid process where the radial pulse was most pronounced. The catheter was then connected to a pressure sensor (B. Braun, Germany), flushed using heparinized saline, and MAP was then recorded every 1 min by the monitor (Mindray, China).
Data collection
Patient characteristics including age, sex, weight, height, current medications, and comorbid diseases were collected from hospital records. MAP and HR were recorded every 1 min from before anesthesia induction until 10 min following tracheal intubation, with baseline MAP being defined as that taken the data recorded 1 min before induction.
PIH was defined as a > 30% reduction in MAP or any recorded MAP < 65 mmHg for at least 1 min during the interval from induction until 10 min post-intubation. Patients were separated into PIH and non-PIH groups based on whether or not they experienced any hypotensive episodes during this interval.
Sample size calculations
Based on the results of a prior study, it was determined that 22 patients would be required in the two groups to detect differences in pupil constriction velocity, while 30 patients would be required to resolve differences in baseline pupil diameter [14]. As the incidence of PIH among 130 patients undergoing general anesthesia in our hospital was 50%, the minimum number of cases required for the construction of a logistic regression model (Model 1) was 60. To account for a dropout rate of 10%, a sample size of 67 was thus required to provide sufficient statistical power to the present study.
Statistical analysis
Microsoft Excel (v 2202, Microsoft, USA) was used to collect data. The Kolmogorov-Smirnov test was used to assess the normality of collected data, with normally distributed results being reported as means ± standard deviation (\(\overline{\mathrm x}\) ± s) and compared via independent sample t-tests, while non-normally distributed data were reported as the median [interquartile range] and compared via Mann-Whitney U tests. Categorical data were compared using chi-square tests and reported as numbers (%). Pearson correlation coefficients (r) were used to assess the association between pupil measurements and the percentage MAP decrease.
The relationship between pupillary parameters and PIH incidence was assessed using two multivariate logistic regression models. Considering a strong association between pupil parameters and age, age was included individually as a variable in model 1 [17]. While Model 2 was adjusted for other variables based on the results of our studies and other prior large-scale retrospective analyses, including age, sex, albumin levels, BMI, ASA grade, and baseline MAP [5, 18, 19]. Receiver operating characteristic (ROC) curves were then used to assess the ability of pupillary parameters to predict PIH based on the results of these analyses.
SPSS v24.0 (IBM, USA) and MedCalc v19.0 (MedCalc Software, Belgium) were used for all statistical analyses, with P < 0.05 as the threshold of statistical significance.