WE ESTIMATE THAT 100,000 individuals from 10 million (1%) active divers are on insulin treatment. The Divers Alert Network found 1.5% with diabetes in a group of 1,180 divers in Project Dive Exploration. (1) This is a surprisingly high number because insulin-treated diabetes, in many countries, is a contraindication to diving. The risk of hypoglycemia is a major concern for divers with diabetes. A severe hypoglycemic event could result in major problems for the diver, as well as the diving partner. As a consequence, insulin treatment is an absolute contraindication for recreational diving in many countries.
The Continuous Glucose Monitoring System (CGMS[R], Medtronic, Minneapolis, MN) monitors subcutaneous glucose continuously and provides values, as well as the rate and direction of these values, every 5 min throughout the day and night.
The value of continuous glucose monitoring in the management of type 1 diabetes was recently evaluated and revealed that the use of continuous glucose monitoring was associated with improved metabolic control in motivated adults. (2)
In another recently published article, (3) we reported that the use of downloaded self-monitored blood glucose, CGMS, and repetitive plasma glucose (PG) in a monitoring schedule could be a tool to identify those subjects who are suitable for diving.
The aim of the present study was to evaluate the accuracy and reliability of the CGMS in diving conditions.
Research Design and Methods
Participants
Twelve individuals with type 1 diabetes and 12 healthy controls were included. Characteristics and study eligibility have previously been published. (3) Key characteristics are given in Table 1.
All the subjects gave written informed consent prior to participation in the study. The ethics committee at Uppsala University, Uppsala, Sweden, approved the study protocol.
The study was performed in 2007.
Design
The 24 participants were divided into 12 pairs of divers, with one diabetes subject and one control subject in each pair. Each diving pair performed five recreational scuba dives 50 min in duration on three consecutive days in a water temperature of 8-11[degrees]C. All the divers wore dry suits on every dive.
Throughout the study, the individuals with diabetes made appropriate dose reductions. The effects of physical exercise were discussed, and in some cases specific insulin dose adjustments were recommended. Doses per day were reduced between 0% to 45%. Those individuals who had a history of being less physical active before the study had to decrease their doses more than those who were more active. Those using continuous subcutaneous insulin infusion (CSII) disconnected their pump 10 min pre-dive and reconnected the pump immediately post-dive. It was recommended that the CSII-treated individuals use a temporarily reduced basal rate 2 h before diving. Prior to the dives, carbohydrates in the form of fruit were given in amounts depending on the individual glucose levels: 15 g when the PG was 140-230 mg/dL and 30 g if the PG was 70-140 mg/dL.
Each subject was provided with, and instructed how to use, a glucose/fructose formulation (Enervitene[R], Enervit, Zelbio, Italy) in case of hypoglycemic symptoms while diving. Repeated low glucose levels at -60min and -10min pre-dive (
Glucose measurements
PG measurements. Capillary blood was analyzed using a reference method, the HemoCue[R] Monitor, together with HemoCue[R] Monitor microcuvettes (HemoCue, Angelholm, Sweden). During the study, glucose was measured at -90, -60, and -10 min pre-dive and immediately post-dive. The medical staff performed all PG sampling during the project. All PG values, on average six to eight per day, were used to calibrate the CGMS.
CGMS. The CGMS Gold (Medtronic) was used on all subjects (for details, see Adolfsson et al. (3)). All CGMS results in the study were shown retrospectively. All the participants used capillary PG and the CGMS in parallel. Monitors were kept under each diver's dry suit.
The difference between glucose readings by the CGMS and PG is expressed as the mean absolute difference (MAD), where MAD = abs ([CGMS - PG]/PG) x 100. CGMS data are shown regarding frequency of hypo- (>180 mg/dL) and duration above (> 180 mg/dL), below low (
Data analysis
The SPSS Statistical Package version 14.0 (SPSS, Chicago, IL) was used for statistical analysis.
All PG values were compared with corresponding CGMS values (t test, two-tailed and Pearson s correlation, two-tailed).
Daily variations in MAD were evaluated with a paired t test and Wilcoxon s signed rank test (two-tailed). The MAD was also calculated and within the hyperglycemic range Differences in MAD between days were evaluated according to the multiple comparisons method (analysis of variance) and Bonferroni's test (post hoc tests).
Sensitivity and specificity for detecting hypoglycemia were calculated based on paired PG and CGMS readings. (4) The ability to detect hypoglycemia was also converted into predictive values. (5)
The analysis of variance test and post hoc test were used to evaluate differences in the distribution of the logged glucose values during the day, evening, and night, as well as during the time spent diving.
Results
Eighty-five percent of the sensors were used on all 3 days and all five dives. In four cases sensors were exchanged because of alarms and calibration errors. None of the sensors was changed on the first day, and no one needed to change the sensor more than once. On two occasions the sensor signal was disrupted during the dive. The replacement of sensors did not affect the recording in connection to diving or the statistical analysis. The survival function of the sensors is shown in a Kaplan-Meier diagram (Fig. 1).
The overall correlation between the CGMS and PG was 0.93 [+ or -] 0.04 (n = 12) within the diabetes group. The overall MAD within the group with diabetes was 14.4 [+ or -] 6%, and the corresponding figures for each day were 23.2 [+ or -] 19.3% on day 1,11.6 [+ or -] 4.5% on day 2, and 11.2 [+ or -] 5.7% on day 3. There was a significant difference between days 1 and 2 (P = 0.034) and days 1 and 3 (P = 0.05), whereas there was no significant difference between days 2 and 3 (P = 0.556) (Wilcoxon s signed rank test).
The MAD within the hypoglycemic range (>180mg/dL).
The overall MAD within the control group was 8.6 [+ or -] 1.7%, and corresponding figures for each day were 8.2 [+ or -] 1.9% on day 1, 8.8 [+ or -] 2.1% on day 2, and 8.7 [+ or -] 3.2% on day 3.
The mean glucose value recorded by the CGMS, plotted versus time for both groups, is presented in Figure 2. For the group with diabetes, the mean subcutaneous glucose values became lower over time, with lowest levels recorded during the evening and at night as well as post-dive.
The numbers of high and low excursions were calculated. In the group with diabetes, the mean number of high excursions (>180mg/dL) during the 3 days was 5.2 (range, 0-7). Low excursions (
In Table 2 the relationships among all hypoglycemic episodes, detected by PG and CGMS, at -60 min and -10 min pre-dive, as well as immediately post-dive, are shown.
The ability of detecting hypoglycemia pre- and post-dive was calculated. Sensitivity was 0.64, and specificity was 0.94, whereas the positive predictive value was 0.39, and the negative predictive value was 0.98. At four occasions hypoglycemia was detected by PG but not with CGMS.
During the dives CGMS detected low excursions on 10 occasions.
During dives 1 and 2, one episode of hypoglycemia was detected, and during dive 3 none was detected. Four episodes of hypoglycemia were detected during both dive 4 and dive 5.
The distribution of glucose levels was calculated as percentage of total time spent above limit (>180mg/dL), within limit (70-180mg/dL), and below low limit (
Discussion
The function of the CGMS at pressure was assessed in a bench test in a pressure chamber prior to the trial. All monitors were tested with both test probes and with sensors inserted in individuals with and without diabetes. All the monitors displayed good function and no mechanical damage during the bench test, performed to a depth of 24m. The function of CGMS was assessed analyzing the ISIG-signal (amperage). These measurements were stable during ambient pressure, and after download no interruption of this signal was seen.
In 2003, Boyne et al. (6) showed that the interstitial glucose has a lag of 4-10 min compared to PG. Moreover, it has been shown that the subcutaneous glucose levels, measured with the microdialysis technique, are similar to PG levels during normoglycemia but significantly lower than blood glucose during hypoglycemia. (7) In a recent published article by Kovatchev et al. (8) this matter is further evaluated. The average observed time lag between blood glucose and interstitial glucose was 12.5 min, whereas the longest lag (16.8 min) was seen when blood glucose was falling. The number of calibrations performed every day in this study is higher than the recommendation of three calibrations daily. The accuracy could have been slightly improved by the more frequent calibration, although the timing is more important than the frequency. (9) Calibrations done post-meals, -60 min pre-dive, and immediately post-dive could in fact have impaired the accuracy because meals and diving (physical activity) could have caused rapid alterations in glucose levels, together with the above-mentioned lag between PG and CGMS.
Opinions differ on the optimal way of expressing the accuracy of continuous glucose sensors. The present options are the continuous glucose-error grid analysis (10) or statistical methods, like those used in this study. (11)
In our study the total MAD improved significantly on days 2 and 3 compared with day 1. This is known from clinical practice and could be explained by more stabilized environment around the sensor. It is speculated that after insertion, bleeding or local swelling could have an effect on the signal. The sensor tip itself may also have to be entirely wetted in order to perform well.
Besides calculating the overall MAD (14.4%), we also calculated MAD within the hypoglycemic range (27.4%) and the hyperglycemic range (7.7%).
A similar pattern was seen when Kovatchev et al. (12) compared four continuous glucose monitors and showed that the clinical accuracy was similar in euglycemia but decreased slightly during hypoglycemia. An increased MAD in the hypoglycemic range could be caused by a high rate of glucose changes together with a longer time lag between blood glucose and interstitial glucose. In this study, examining diving, both of these factors may have cooperated.
The mean sensor survival time was >48 h without deterioration in accuracy, and the CGMS signal was only disrupted at two occasions during dives. Survival of the sensors in this study is higher compared to the results when CGMS was used during other forms of physical exercise: soccer, cross-country skiing/floorball, and golf (Adolfsson et al., manuscript submitted for publication). The reason could be that diving is associated with less perspiration and less mechanical impact through physical contact, reducing the risk of sensor dislodgement. The sensor itself has also been continuously improved.
In this study with well-informed buddy divers we allowed participants to start diving on lower glucose levels than those suggested by the Divers Alert Network, 150-300 mg/dL. (13) We wanted to evaluate the risk of having hypoglycemia related to diving. Therefore, we had to touch upon the risk of having hypoglycemic events but on the same time not jeopardize the individual's security.
Disclaimer:This information is not a tool for self-diagnosis or a substitute for professional care.
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