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AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
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BACKGROUND: Most hospital organizations have had to face the burden of managing the ongoing COVID-19 outbreak. One of the challenges in overcoming the influx of COVID-19 patients is controlling patient-to-staff transmission. Measuring the specific extent of ICU caregiver exposure to the virus and identifying the associated risk factors are, therefore, critical issues. We prospectively studied SARS-CoV-2 seroprevalence in the staff of a hospital in Lyon, France, several weeks after a first epidemic wave. Risk factors for the presence of SARS-CoV-2 antibodies were identified using a questionnaire survey. RESULTS: The overall seroprevalence was 9% (87/971 subjects). Greater exposure was associated with higher seroprevalence, with a rate of 3.2% [95% CI 1.1-5.2%] among non-healthcare staff, 11.3% [8.9-13.7%] among all healthcare staff, and 16.3% [12.3-20.2%] among healthcare staff in COVID-19 units. The seroprevalence was dramatically lower (3.7% [1.0-6.7%]) in the COVID-19 ICU. Risk factors for seropositivity were contact with a COVID-19-confirmed household (odds ratio (OR), 3.7 [1.8-7.4]), working in a COVID-19 unit (OR, 3.5 [2.2-5.7], and contact with a confirmed COVID-19 coworker (OR, 1.9 [1.2-3.1]). Conversely, working in the COVID-19-ICU was negatively associated with seropositivity (OR, 0.33 [0.15-0.73]). CONCLUSIONS: In this hospital, SARS-CoV-2 seroprevalence was higher among staff than in the general population. Seropositivity rates were particularly high for staff in contact with COVID-19 patients, especially those in the emergency department and in the COVID-19 unit, but were much lower in ICU staff. Clinical trial registration NCT04422977.
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WHAT WE ALREADY KNOW ABOUT THIS TOPIC: Muscle atrophy is common in the critically ill, and diaphragm atrophy occurs during mechanical ventilation. It is not known whether wasting of diaphragm and nondiaphragm muscle is related. WHAT THIS ARTICLE TELLS US THAT IS NEW: Ultrasound was used for serial assessment of diaphragm and pectoral muscle in 97 critically ill patients. Diaphragm and pectoral atrophy occurred in 48% and 29%, respectively, and was associated with septic shock (diaphragm) and steroid use (pectoral); atrophy of the two muscle types appears unrelated. BACKGROUND: Muscle atrophy occurs early during critical illnesses. Although diffuse, this atrophy may specifically affect the diaphragm under artificial inactivity accompanying invasive mechanical ventilation. The primary objective of this study was to highlight diaphragm atrophy during the first 5 days of critical illness. Monitoring of pectoral thickness (a nonpostural muscle with mainly phasic function) served as a control. METHODS: Diaphragm and pectoral thicknesses were measured by ultrasound within the first 24 h of admission in 97 critically ill patients, including 62 on mechanical ventilation. Thirty-five patients were reexamined at day 5. RESULTS: Baseline median (interquartile) values of diaphragm and pectoral thicknesses at day 1 were 2.4 (2.0, 2.9) and 5.9 (4.7, 7.2) mm, respectively (n = 97). Higher values of diaphragm thickness at baseline were positively associated with male sex, chronic obstructive pulmonary disease, and diabetes. Diaphragm and pectoral atrophies (defined as a decrease of 10% or more between day 1 and day 5) were detected in 48% (17 of 35) and 29% (10 of 34) respectively, and were uncorrelated with each other. Diaphragm atrophy was significantly more frequent in patients with septic shock and in those with mechanical ventilation, as compared with their respective counterparts (71% [10 of 14] vs. 33% [7 of 21], P = 0.027 and 71% [17 of 28] vs. 0% [0 of 7], P = 0.004, respectively), whereas pectoral atrophy was more common in patients treated with steroids as compared with their counterparts (58% [7 of 12] vs. 14% [3 of 22], P = 0.006). A statistically significant association between diaphragm atrophy and outcome was not found. Pectoral atrophy seemed associated with less successful weaning from mechanical ventilation at day 14 (12% [1 of 8] vs. 58% [11 of 19], P = 0.043). CONCLUSIONS: Ultrasound enables identification of specific early diaphragm atrophy that affects the majority of mechanically ventilated patients and septic shock patients. Diaphragm atrophy and pectoral muscle atrophy seem to be two unrelated processes.
