We conducted a cohort study to determine whether grip recovery, which was defined as postoperative value/preoperative value, could be a better indicator than grip strength and grip/weight at predicting postoperative complications 30 days after hospital discharge in postoperative patients.
The trial was performed at a cardiovascular hospital in China. Our research was conducted from October (2018) to January (2019). During this time, we enrolled patients and recorded their information at baseline. Then we followed up on complications at 30 days after discharge in postoperative patients. Patients, who were scheduled for primary elective cardiac surgeries (including CABG, valve replacement, other cardiac surgeries except for aortic dissection), and who had the ability to provide informed consent, were eligible. Exclusion criteria were: 1) age <50 years old, 2) vision impairment without corrective lenses at the time of the tests, 3) diabetic neuropathy involving the hands, 4) refusal to participate in our study follow-up, 5) surgery-related bone trauma and deformation of the hand joints (i.e. surgical diseases affecting muscle strength and grip strength), 6) history of stroke, and 7) undergoing a repeat operation. The methodological sessions were carried out in accordance with the approved guidelines and regulations. The participants were fully informed of research nature and signing an informed consent form to participate. This study was approved by the Tianjin Medical University ethics committee.
During the study period, 271 patients participated and underwent surgery. Of these people, 237 met the requirements, and 34 patients were lost to follow-up or had incomplete data. In the end, 212 patients were included in this study. And 69.3% of them were male. The average age of this population was 64.5±6.1 years old. Among the patients, 134 patients underwent CABG surgery, 12 patients underwent aortic valve replacement surgery, 39 underwent non-aortic valve replacement surgery, and 27 patients underwent other surgeries. All the operations were performed by the same team. All surgeons had at least 5 years of experience.
Preoperative and perioperative assessments
Demographics and preoperative factors were prospectively recorded during a standardized interview. Preoperative sociodemographic variables, including age, gender, weight, height, body mass index (calculated as weight in kilograms divided by height in meters squared), marital status, educational level, and occupation were assessed. Marital status was classified as married or not married/single. Educational level was defined as age at completion of schooling and divided into 4 categories: <1 yr of schooling, 1-6 y, 7-12 y, and ≥13 y. Behavioral characteristics included smoking and drinking habits. Information on smoking (never, former smoker, or current smoker) and drinking (never, former drinker, occasional drinker, or everyday drinker) were also obtained from the questionnaire. Physical activity was assessed using the short form of the International Physical Activity Questionnaire (IPAQ). History of myocardial infarction, hypertension and diabetes mellitus were recorded from the medical records. Type of surgical procedure, current diagnoses, pulmonary status, duration of surgery, duration of Intensive Care Unit (ICU) stay, and duration of mechanical ventilation were also recorded. All surgery-related information was reported by the computer record. We used EuroSCORE to evaluate the surgical risk of patients and adjusted for it in our logistic models. EuroSCORE has been widely used for evaluating operative risk, and its validity and reliability have been verified for cardiac surgery (22, 23).
Performance-based assessments consisted of several physical tests. We had described the methods for gait function and grip strength in detail in our previous study (24). Gait function was assessed with the 4-m walk test. To measure walking speed, two groups of recording laser transmitter receiver timers were placed at the beginning and the end of a 4-meter course. Patients were asked to cover a distance of 4-m distance at the usual uniform speed. Grip (kg) was used as a measure of muscle strength and quantified using a handheld dynamometer (GRIP-D; Takei Ltd, Niigata, Japan). Participants were asked to exert their maximum effort twice by using their dominant hand, and the average value of grip strength was recorded. This method of standardization had been previously recommended in order to normalize and improve physical function testing results (25). To avoid measurement error, the assessment was conducted by postgraduate students in the health field who received special training for administering all tests. Every project was carried out by one trained staff member to complete the data collection of all the subjects.
Measurement of recovery
On the fifth postoperative day, we assessed postoperative patients by monitoring heart rate and blood pressure during a 6 minute walk distance (6MWD) test. We also recorded the distance they could walk in 6 minutes. We calculated the percentage of the estimated 6MWD. Previous studies had verified the reliability and validity of the 6MWD for evaluating heart disease (26). In order to measure postoperative hospitalization time, we also recorded the patient's surgery date and hospital discharge date and then calculated the interval in days.
Grip strength recovery
Grip strength was measured during the preoperative and postoperative period (i.e. fifth day after surgery). Before this study we had carried out a preliminary experiment and had found that on the fifth day after surgery patients were able to return to their preoperative walking abilities and that their grip strength plateaued. Figure 1 shows the relative value of grip strength on admission, preoperatively, and seven days after surgery. We found that the rate of grip strength recovery becomes smoother on the fifth, sixth, and seventh days. Thus, we measured grip strength on the fifth day to represent average grip strength value. Grip recovery was defined as postoperative value/preoperative value. To determine the best predictors, we analyzed the relationship between grip strength, grip strength/body weight, grip recovery, and complications.
Postoperative follow-up and definition of complications
Follow-up occurred at 30 days after hospital discharge. Patients were asked to undergo postoperative cardiac ultrasounds, chest radiographs, routine blood tests, etc. Complications were defined as death, needing for reoperation, atrial fibrillation, deep sternal infection, pulmonary complications, stroke, sensory changes, renal failure requiring treatment, dehydration, multisystem organ failure, and readmission to the hospital within 30 days (14, 15). Complications during follow-up did not include those that occurred during the perioperative period or postoperative complications that occurred during hospitalization immediately after the surgery. All results were obtained at outpatient care appointments at our hospital or a field hospital. All reexamination results and complications were reviewed by medical staff. Patients without reexamination information were reached by phone for feedback. Missing follow-up data were excluded. Thirty-six patients had 30-day complications, and 176 people were normal.
Differences between continuous variables were examined using t-tests with the Bonferroni correction. We used the chi square test on categorical variables. Data was presented as means (with 95% confidence intervals) or as percentages. Table 1 shows characteristics of patients with or without 30 day complications. Receiver-operating characteristic (ROC) curve analyses were performed to determine the optimal cutoff values for grip strength, grip/weight and grip recovery with complications as the outcome variable (Table 2). The receiver-operating characteristic curve was a graph of sensitivity plotted against (1 − specificity) over all possible diagnostic cutoff values. The optimal cutoff values were obtained from the maximal Youden’s index, calculated as (sensitivity + specificity − 1), and then the best combination of sensitivity and specificity was chosen. Logistic analyze was used to assess the relationship between optimal grip factors and complications 30 days after hospital discharge (Table 3). Covariates were added sequentially to the model to evaluate associations at different levels of adjustment. Crude analyze was unadjusted. Multivariable adjusted model 1 was adjusted for age, gender, and body mass index (BMI). To exclude the impact of surgery related-complications on grip strength and other complications, multivariable adjusted model 2 was adjusted for age, gender, BMI, EuroSCORE, smoking, drinking, hypertension, diabetes, hyperlipidemia, surgery duration, length of ICU stay, assisted ventilation time, and drainage time. In order to verify that grip recovery was the best predictor, we relisted the cutoff point of grip recovery to observe postoperative correlation factors (Table 4). Values under 83.92% were defined as predicting a low chance of recovery. Differences were defined as significant when P<0.05. All statistical analyses were performed using SPSS V19.0 software package (SPSS Inc, China).