Perioperative glycaemic control for people with diabetes undergoing surgery.
People with diabetes mellitus are at increased risk of postoperative complications. Data from randomised clinical trials and meta-analyses point to a potential benefit of intensive glycaemic control, targeting near-normal blood glucose, in people with hyperglycaemia (with and without diabetes mellitus) being submitted for surgical procedures. However, there is limited evidence concerning this question in people with diabetes mellitus undergoing surgery.
To assess the effects of perioperative glycaemic control for people with diabetes undergoing surgery.
For this update, we searched the databases CENTRAL, MEDLINE, LILACS, WHO ICTRP and ClinicalTrials.gov. The date of last search for all databases was 25 July 2022. We applied no language restrictions.
We included randomised controlled clinical trials (RCTs) that prespecified different targets of perioperative glycaemic control for participants with diabetes (intensive versus conventional or standard care).
Two authors independently extracted data and assessed the risk of bias. Our primary outcomes were all-cause mortality, hypoglycaemic events and infectious complications. Secondary outcomes were cardiovascular events, renal failure, length of hospital and intensive care unit (ICU) stay, health-related quality of life, socioeconomic effects, weight gain and mean blood glucose during the intervention. We summarised studies using meta-analysis with a random-effects model and calculated the risk ratio (RR) for dichotomous outcomes and the mean difference (MD) for continuous outcomes, using a 95% confidence interval (CI), or summarised outcomes with descriptive methods. We used the GRADE approach to evaluate the certainty of the evidence (CoE).
A total of eight additional studies were added to the 12 included studies in the previous review leading to 20 RCTs included in this update. A total of 2670 participants were randomised, of which 1320 were allocated to the intensive treatment group and 1350 to the comparison group. The duration of the intervention varied from during surgery to five days postoperative. No included trial had an overall low risk of bias. Intensive glycaemic control resulted in little or no difference in all-cause mortality compared to conventional glycaemic control (130/1263 (10.3%) and 117/1288 (9.1%) events, RR 1.08, 95% CI 0.88 to 1.33; I2 = 0%; 2551 participants, 18 studies; high CoE). Hypoglycaemic events, both severe and non-severe, were mainly experienced in the intensive glycaemic control group. Intensive glycaemic control may slightly increase hypoglycaemic events compared to conventional glycaemic control (141/1184 (11.9%) and 41/1226 (3.3%) events, RR 3.36, 95% CI 1.69 to 6.67; I2 = 64%; 2410 participants, 17 studies; low CoE), as well as those considered severe events (37/927 (4.0%) and 6/969 (0.6%), RR 4.73, 95% CI 2.12 to 10.55; I2 = 0%; 1896 participants, 11 studies; low CoE). Intensive glycaemic control, compared to conventional glycaemic control, may result in little to no difference in the rate of infectious complications (160/1228 (13.0%) versus 224/1225 (18.2%) events, RR 0.75, 95% CI 0.55 to 1.04; P = 0.09; I2 = 55%; 2453 participants, 18 studies; low CoE). Analysis of the predefined secondary outcomes revealed that intensive glycaemic control may result in a decrease in cardiovascular events compared to conventional glycaemic control (107/955 (11.2%) versus 125/978 (12.7%) events, RR 0.73, 95% CI 0.55 to 0.97; P = 0.03; I2 = 44%; 1454 participants, 12 studies; low CoE). Further, intensive glycaemic control resulted in little or no difference in renal failure events compared to conventional glycaemic control (137/1029 (13.3%) and 158/1057 (14.9%), RR 0.92, 95% CI 0.69 to 1.22; P = 0.56; I2 = 38%; 2086 participants, 14 studies; low CoE). We found little to no difference between intensive glycaemic control and conventional glycaemic control in length of ICU stay (MD -0.10 days, 95% CI -0.57 to 0.38; P = 0.69; I2 = 69%; 1687 participants, 11 studies; low CoE), and length of hospital stay (MD -0.79 days, 95% CI -1.79 to 0.21; P = 0.12; I2 = 77%; 1520 participants, 12 studies; very low CoE). Due to the differences within included studies, we did not pool data for the reduction of mean blood glucose. Intensive glycaemic control resulted in a mean lowering of blood glucose, ranging from 13.42 mg/dL to 91.30 mg/dL. One trial assessed health-related quality of life in 12/37 participants in the intensive glycaemic control group, and 13/44 participants in the conventional glycaemic control group; no important difference was shown in the measured physical health composite score of the short-form 12-item health survey (SF-12). One substudy reported a cost analysis of the population of an included study showing a higher total hospital cost in the conventional glycaemic control group, USD 42,052 (32,858 to 56,421) compared to the intensive glycaemic control group, USD 40,884 (31.216 to 49,992). It is important to point out that there is relevant heterogeneity between studies for several outcomes. We identified two ongoing trials. The results of these studies could add new information in future updates on this topic.
High-certainty evidence indicates that perioperative intensive glycaemic control in people with diabetes undergoing surgery does not reduce all-cause mortality compared to conventional glycaemic control. There is low-certainty evidence that intensive glycaemic control may reduce the risk of cardiovascular events, but cause little to no difference to the risk of infectious complications after the intervention, while it may increase the risk of hypoglycaemia. There are no clear differences between the groups for the other outcomes. There are uncertainties among the intensive and conventional groups regarding the optimal glycaemic algorithm and target blood glucose concentrations. In addition, we found poor data on health-related quality of life, socio-economic effects and weight gain. It is also relevant to underline the heterogeneity among studies regarding clinical outcomes and methodological approaches. More studies are needed that consider these factors and provide a higher quality of evidence, especially for outcomes such as hypoglycaemia and infectious complications.
Bellon F
,Solà I
,Gimenez-Perez G
,Hernández M
,Metzendorf MI
,Rubinat E
,Mauricio D
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《Cochrane Database of Systematic Reviews》
Continuous glucose monitoring with FreeStyle Libre PRO sensor in patients with type 2 diabetes and end-stage renal failure on haemoDIALysis (FSLPRO-DIAL pilot study).
For end-stage renal disease (ESRD) patients with diabetes on haemodialysis, diabetes control is difficult to achieve. Hypoglycaemia is a major problem in these frailty subjects. Continuous glucose monitoring (CGM) devices appear therefore to be a good tool to help patients monitor their glycaemic control and to help practitioners optimize treatment. We aimed to compare the laboratory value of Hba1c with the sensor-estimated value of Hba1c (= glucose management indicator, GMI) in ESRD patients with type 2 diabetes (T2D) (with or without insulin treatment) on haemodialysis. Secondly, we aimed to identify CGM-derived monitoring parameters [time in range, time in hypo/hyperglycaemia, glycaemic variability (coefficient of variation, CV)] to identify patients at risk of frequent hypo- or hyperglycaemia.
The FSLPRO-DIAL pilot study (NCT04641650) was a prospective monocentric cohort study including 29 subjects with T2D who achieve the protocol. Inclusion criteria were: age ≥ 18 years, haemodialysis duration for at least 3 months, type 2 diabetes with no change in treatment for at least 3 months. Demographic data and blood sample were collected at the day of inclusion. Freestyle Libre pro IQ sensor (blinded CGM) was inserted for 14 days. After this period, all CGMs data were collected and analysed.
Data were available for 27 patients. Mean age was 73 ± 10, mean BMI 27.2 kg/m2, mean duration of diabetes 16.9 years and mean dialysis duration 2.9 years. Twenty-four subjects were treated with insulin. Mean HbA1c was 6.6% (SD 1.2), and mean GMI was 6.7% (SD 0.9) (no significant difference, p = 0.3). Twelve subjects (44.4%) had a discordance between HbA1c and GMI of < 0.5%, 11 (40.8%) had a discordance between 0.5 and 1%, and only 4 (14.8%) had a discordance of > 1%. Mean time in range (70-180 mg/dl) was 71.9%, mean time below range (< 70 mg/dl) was 5.6%, and mean time above range (> 180 mg/dl) was 22.1%. Mean CV was 31.8%. For 13 out of 27 patients, we reduced antidiabetic treatment by stopping treatments or reducing insulin doses.
In this pilot study, there was no global significant difference between HbA1c and GMI in this particular cohort with very well-controlled diabetes. However, the use of the sensor enabled us to identify an excessive time in hypoglycemia in this fragile population and to adapt their treatment.
Henry Z
,Villar E
,Chauvet C
,Belloi A
,Prunescu I
,Doroszewski F
,Luyton C
,Marchand L
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Treatment regimens and glycaemic outcomes in more than 100 000 children with type 1 diabetes (2013-22): a longitudinal analysis of data from paediatric diabetes registries.
Advances in paediatric type 1 diabetes management and increased use of diabetes technology have led to improvements in glycaemia, reduced risk of severe hypoglycaemia, and improved quality of life. Since 1993, progressively lower HbA1c targets have been set. The aim of this study was to perform a longitudinal analysis of HbA1c, treatment regimens, and acute complications between 2013 and 2022 using data from eight national and one international paediatric diabetes registries.
In this longitudinal analysis, we obtained data from the Australasian Diabetes Data Network, Czech National Childhood Diabetes Register, Danish Registry of Childhood and Adolescent Diabetes, Diabetes Prospective Follow-up Registry, Norwegian Childhood Diabetes Registry, England and Wales' National Paediatric Diabetes Audit, Swedish Childhood Diabetes Registry, T1D Exchange Quality Improvement Collaborative, and the SWEET initiative. All children (aged ≤18 years) with type 1 diabetes with a duration of longer than 3 months were included. Investigators compared data from 2013 to 2022; analyses performed on data were pre-defined and conducted separately by each respective registry. Data on demographics, HbA1c, treatment regimen, and event rates of diabetic ketoacidosis and severe hypoglycaemia were collected. ANOVA was performed to compare means between registries and years. Joinpoint regression analysis was used to study significant breakpoints in temporal trends.
In 2022, data were available for 109 494 children from the national registries and 35 590 from SWEET. Between 2013 and 2022, the aggregated mean HbA1c decreased from 8·2% (95% CI 8·1-8·3%; 66·5 mmol/mol [65·2-67·7]) to 7·6% (7·5-7·7; 59·4mmol/mol [58·2-60·5]), and the proportion of participants who had achieved HbA1c targets of less than 7% (<53 mmol/mol) increased from 19·0% to 38·8% (p<0·0001). In 2013, the aggregate event rate of severe hypoglycaemia rate was 3·0 events per 100 person-years (95% CI 2·0-4·9) compared with 1·7 events per 100 person-years (1·0-2·7) in 2022. In 2013, the aggregate event rate of diabetic ketoacidosis was 3·1 events per 100 person-years (95% CI 2·0-4·8) compared with 2·2 events per 100 person-years (1·4-3·4) in 2022. The proportion of participants with insulin pump use increased from 42·9% (95% CI 40·4-45·5) in 2013 to 60·2% (95% CI 57·9-62·6) in 2022 (mean difference 17·3% [13·8-20·7]; p<0·0001), and the proportion of participants using continuous glucose monitoring (CGM) increased from 18·7% (95% CI 9·5-28·0) in 2016 to 81·7% (73·0-90·4) in 2022 (mean difference 63·0% [50·3-75·7]; p<0·0001).
Between 2013 and 2022, glycaemic outcomes have improved, parallel to increased use of diabetes technology. Many children had HbA1c higher than the International Society for Pediatric and Adolescent Diabetes (ISPAD) 2022 target. Reassuringly, despite targeting lower HbA1c, severe hypoglycaemia event rates are decreasing. Even for children with type 1 diabetes who have access to specialised diabetes care and diabetes technology, further advances in diabetes management are required to assist with achieving ISPAD glycaemic targets.
None.
For the Norwegian, German, Czech, Danish and Swedish translations of the abstract see Supplementary Materials section.
Zimmermann AT
,Lanzinger S
,Kummernes SJ
,Lund-Blix NA
,Holl RW
,Fröhlich-Reiterer E
,Maahs DM
,Ebekozien O
,Rompicherla S
,Warner JT
,Pons Perez S
,Robinson H
,Craig ME
,Johnson S
,Akesson K
,Thorén A
,Eeg-Olofsson K
,Ranjan AG
,Madsen M
,Witsch M
,Bratke H
,Alonso GT
,Sumnik Z
,Neuman V
,Cinek O
,Skrivarhaug T
,Svensson J
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