Protective and risk factors of recurrent severe hypoglycemia in adults with type 1 diabetes: A cross-sectional analysis of baseline data from the PR-IAH study

doi:10.21203/rs.3.rs-1984365/v1

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Research Article

Protective and risk factors of recurrent severe hypoglycemia in adults with type 1 diabetes: A cross-sectional analysis of baseline data from the PR-IAH study

https://doi.org/10.21203/rs.3.rs-1984365/v1

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Background

Severe hypoglycemia (SH) remains a central problem in the management of type 1 diabetes (T1D); however, little is known about the protective and risk factors associated with recurrent SH (RSH). This study aimed to identify the protective and risk factors for RSH in adults with T1D.

Methods

This cross-sectional study enrolled 287 adults with T1D (mean age: 50.3 ± 14.5 years, male: 36.2%, diabetes duration: 17.6 ± 11.2 years, mean HbA1c: 7.7 ± 0.9%) and divided them into non-SH (n = 262), solitary SH (n = 17), and RSH (n = 8) groups. Impaired awareness of hypoglycemia (IAH) assessed using the Gold’s method, diabetic complications, fear of hypoglycemia, diabetes distress, hypoglycemia problem solving abilities, and treatment data were collected.

Results

The overall SH rate was 16.7/100 person-years. The odds ratios of diabetic peripheral neuropathy and IAH were associated with an increased risk of RSH (odds ratio [OR]: 5.53 ,95% confidence interval [CI]: 1.18–25.98 and OR: 4.82 [95% CI:1.09–21.23], respectively); hypoglycemia problem-solving perception score was associated with a decreased risk of RSH (OR: 0.35 [95% CI: 0.18–0.69]). The rate of rtCGM use decreased as the SH category increased, but no difference was found in the rate of isCGM use.

Conclusion

We identified the protective factors, such as hypoglycemia problem-solving perception, in addition to the risk factors for RSH in adults with T1D.

Trial registration:

University hospital Medical Information Network (UMIN) Center: UMIN000039475)、Approval date 13 February 2020

severe hypoglycemia

impaired awareness of hypoglycemia

type 1 diabetes

Hypoglycemia is a frequent complication of diabetes that limits therapy intensification efforts and increases morbidity and mortality. With recurrent hypoglycemia, the counterregulatory response to decreased blood glucose levels is blunted, resulting in hypoglycemia-associated autonomic failure [1, 2]. The mechanisms underlying these blunted effects are poorly understood. Severe hypoglycemia (SH) remains a major problem in the management of type 1 diabetes (T1D). SH is defined as a condition with serious cognitive dysfunction, such as convulsions and coma, requiring assistance from another person in order to recover from the episode. This condition is considered lethal and is the cause of death in 4–10% of children and adolescents with T1D [3]. Repeated exposure to glucose levels below 3 mmol/l can blunt physiological warning signs, leading to impaired awareness of hypoglycemia (IAH), which increases the risk of SH by three- to six-folds [4–6]. In particular, recurrent SH (RSH) deteriorates cognitive dysfunction characterized by severe memory and cognitive processing speed impairment in adults with diabetes [7, 8]. RSH was associated with a fear of hypoglycemia and diabetic peripheral neuropathy (DPN) in 71 adults with T1D [9]. RSH remains a problem in patients with T1D, despite the major advances in therapeutic options such as continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) [10]. However, the association between protective and risk factors and RSH in adults with T1D is still not fully understood [11]. Recently, hypoglycemia problem-solving abilities have been evaluated using a validated questionnaire [12]. This hypoglycemia problem-solving scale (HPSS) has 24 items and seven subscales: problem-solving perception, detection control, identifying problem attributes, setting problem-solving goals, seeking preventive strategies, evaluating strategies, and immediate management. On the contrary, older age, long diabetes duration, low body mass index, better glycemic control, and need for nursing care are candidate risk factors for RSH [13–15]. This study aimed to identify the protective and risk factors for RSH in adults with T1D.

This exploratory and cross-sectional study was approved by the National Hospital Organization (NHO) Central Research Ethics Committee (R2-0117002) and performed in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.

Participants and settings

Between February 2020 and March 2022, we enrolled adult patients with IAH from the NHO collaborating centers in Japan. The following seven institutions participated in this study: NHO Mie Hospital, NHO Kyoto Medical Center, NHO Osaka National Hospital, NHO Himeji Medical Center, NHO Hyogo-Chuo National Hospital, NHO Okayama Medical Center, and NHO Kokura Medical Center. The participants were divided into IAH and non-IAH (control) groups.

Patients with T1D, with a diabetes duration of ≥1 year, aged ≥20 years, and who attended a collaborating center were included in the study. Meanwhile, patients who received non-insulin therapy, were using anti-dementia drugs, and were considered as inappropriate cases as judged by the research director or coordinators were excluded.

Diabetic complications

Diabetic retinopathy, diabetic nephropathy, and DPN were managed by certified diabetologists according to the treatment guidelines for diabetes in 2018–2019. Diabetic retinopathy was assessed by an ophthalmologist using retinal photography. Retinopathy was classified as absent, simple, preproliferative, or proliferative. Nephropathy was classified into stages 1–5 based on the estimated glomerular filtration rate, presence of albuminuria, or hemodialysis stage [16]. DPN was considered present based on the criteria after the diagnosis of diabetes and excluded polyneuropathy, except for diabetic polyneuropathy, which was determined to be positive in the presence of at least two of the following three criteria: 1) subjective symptoms (numbness, pain, or dysesthesia in the bilateral lower extremities), 2) decreased or absent bilateral Achilles tendon reflexes, and 3) diminished bilateral vibratory sensation in the malleolus medialis (<10 s using a tuning fork at 128 Hz) [17]. The coefficient of variation of the R-R intervals (CV-RR) was calculated automatically using a computed analyzer that collected 100 R-R intervals and divided the standard deviation by the mean value. A CV-RR of <3% was considered indicative of diabetic cardiac autonomic neuropathy [18]. The mean corrected QT (QTc) interval was calculated using Bazett’s formula, and a QTc interval of >440 ms was considered prolonged [19]. Data on HbA1c level, glycated hemoglobin (GA) level, liver enzyme (aspartate aminotransferase, alanine transaminase, and gamma-glutamyl transferase) levels, and lipid profiles were collected from the patients’ medical records. Furthermore, the GA/HbA1c ratio, which reflects glucose variability, was calculated by dividing the GA level by the HbA1c level [20].

RSH, IAH, and hypoglycemic symptoms

SH was defined as an event requiring assistance from another individual to actively administer carbohydrates or glucagon or to take corrective action [21]. RSH was defined as two or more episodes of SH in 1 year [22]. The IAH was determined using the gold standard method [23]. The Gold’s questionnaire constitutes a single question (“Do you know when your hypoglycemia is commencing?”), and the patients respond using a 7-point Likert scale, with scores ranging from 1 (“always aware”) to 7 (“never aware”). In the gold standard method, a score of 4 or higher implied the presence of IAH. Hypoglycemic symptoms were evaluated using the Edinburgh Hypoglycemia Scale [24,25]. This questionnaire comprises 11 key symptoms (sweating, palpitations, shaking, hunger, confusion, drowsiness, odd behavior, speech difficulty, incoordination, nausea, and headache), which are evaluated using a 7-point Likert scale, with scores ranging from 1 (“not at all”) to 7 (“very severe”), and divided into three domains (neuroglycopenic, autonomic, and general malaise). The self-reported number of SH episodes in the preceding year, defined as “hypoglycemia that the patient was unable to treat on his or her own,” was also assessed.

Diabetes-related distress and hypoglycemia problem-solving abilities

Diabetes-related distress was assessed using the Problem Areas in Diabetes (PAID) questionnaire. Each item on the PAID questionnaire was scored from 0 (“no problem”) to 4 (“serious problem”). All 20 scores were summed and multiplied by 1.25, with a total score of 0–100 points. Higher scores indicate greater diabetes-related distress; a cut-off score of ≥40 indicates high level of distress [26,27]. Fear of hypoglycemia was assessed using the Hypoglycemia Fear Survey (HFS), adapted for use in Japan [28,29]. The HFS has two subscales: the HFS-B (behavior subscale) and HFS-W (worry subscale). The items are rated on a 5-point Likert scale, with scores ranging from 0 (never) to 4 (always). Higher scores indicated a greater fear of hypoglycemia. Health-related quality of life was assessed, and the utility index was calculated using the European Quality of Life-5-Dimension (EQ-5D) questionnaire [30,31]. This questionnaire has five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. The EQ-5D-3 level, which assesses each dimension based on three levels of severity (e.g., “no problem,” “some problems,” or “unable”). Hypoglycemia problem-solving abilities were assessed using the Hypoglycemia Problem-Solving Scale (HPSS) [12]. The HPSS has 24 items and seven subscales: problem-solving perception, detection control, identifying problem attributes, setting problem-solving goals, seeking preventive strategies, evaluating strategies, and immediate management.

Lifestyle factors

Self-administered questionnaire data regarding lifestyle behaviors (current smoking, regular exercise, dietary habits, drinking habits, and sleeping habits) were collected using a standardized questionnaire from the Specific Health Check and Guidance System [32]. Three items were related to exercise habits: 1) regular exercise (≥2 times/week of exercise ≥4 METs/h), 2) active physical activity (≥23 METs × h/week), and 3) walking pace (rapid or not rapid), which is an indicator of physical fitness. Excessive drinking was defined based on the answers to questions on drinking habits: “occasionally or every day” and “≥180 mL of sake (equivalent to ≥20 g of alcohol).” Sleep debt was defined as the difference between the self-reported total weekday and weekend sleep hours of at least two hours [33]. Healthy lifestyle behaviors included consumption of fruit, fish, and milk; level of exercise; avoidance of smoking; moderate alcohol intake; and moderate sleep duration [34].

Data analyses

Qualitative variables were compared using the Fisher’s exact test . As the analyzed quantitative variables were not normally distributed, comparisons were conducted using the Mann–Whitney U test for two groups and the Kruskal–Wallis test for three or more groups. The normality of the variable distribution was verified using the Shapiro–Wilk test. Logistic regression was used to estimate the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). Patients with RSH were divided into three groups: non-SH, solitary SH, and RSH. Multiple comparisons were performed using one-way analysis of variance followed by Tukey’s post-hoc test. Trends were assessed using the Jonckheere–Terpstra test. A P value of <0.05 was considered significant. Cronbach’s alpha coefficient and mean interitem correlations were used to measure the internal consistency of the questionnaires. Patients with missing data were excluded from the analysis. The analysis was conducted using R version 4.1.2. We acknowledged and cited our previous article on description method [35].

Participants and SH incidence

The study included a total of 287 adults with T1D and IAH (mean age: 50.3 ± 14.5 years; proportion of men: 36.2%; diabetes duration: 17.6 ± 11.2 years; mean HbA1c level: 7.7 ± 0.9%), who were divided into non-SH (n = 262, 91.3%), solitary SH (n = 17, 5.9%), and RSH (n = 8, 2.8%) groups (Table 1). The overall SH rate was 16.7/100 person-years. IAH was associated with an increased risk of RSH (OR: 4.82 [95% CI: 1.09–21.23], Table 2).

Table 1

Clinical characteristics of the study participants according to the SH category
Variables	SH categories			P for trend
Variables	Non-SH (n=262)	Solitary SH (n=17)	RSH (n=8)	P for trend
Age, years Male sex, % Diabetes duration, years BMI, kg/m²	50.2 (14.4) 36.3 17.2 (11.1) 23.3 (3.5)	52.6 (16.6) 35.3 18.7 (11.9) 24.4 (6.0)	49.6 (15.2) 37.5 25.7 (11.1) 23.7 (3.2)	0.677 0.990 0.110 0.575
Diabetic complication Retinopathy, % NDR/SDR vs. PPDR/PDR Photocoagulation Nephropathy, % 1^st/2^nd/3^rd/4^th/5^th 1^st vs. 2^nd/3^rd/4^th/5^th Peripheral neuropathy, % Coronary artery disease Cerebrovascular disease Peripheral arterial disease Atrial fibrillation Femoral neck fractures IAH, %	8.4 9.5 82.4/13.0/3.1/0.4/1.1 17.6 11.9 5.3 3.8 3.4 0.8 0.4 11.1	14.3 23.5 75.0/18.8/0/0/6.2 25.0 50.0 0 0 0 0 0 23.5	12.5 25.0 87.5/12.5/0/0/0 12.5 42.9 0 0 0 0 0 37.5	0.465 0.034 ^* 0.770 0.915 <0.001^* 0.266 0.351 0.377 0.681 0.722 0.009 ^*
ECG QTc (Bazett’s formula), ms Abnormal, >440 ms CV-RR, % <3%	416.7 (27.2) 14.5 3.5 (1.6) 45.5	412.9 (29.2) 18.2 2.8 (1.3) 66.7	403.6 (12.1) 0 2.2 (1.0) 100.0	0.388 0.591 0.064 0.017 ^*
^*P < 0.05.
RSH, recurrent severe hypoglycemia; NDR, no diabetic retinopathy; SDR, simple retinopathy; PPDR, pre-proliferative retinopathy; PDR, proliferative retinopathy; IAH, impaired awareness of hypoglycemia; ECG, electrocardiogram; QTc, QT corrected; CV-RR, coefficient of variation of R-R interval.

Table 2

Odds ratio of interest variables for solitary and recurrence SH
Variables	SH categories
Variables	Non-SH	Solitary SH	RSH
IAH DPN CGM usage CSII treatment HPSS 1. Problem-solving perception 2. Detection control 3. Identifying problem attributes 4. Setting problem- solving goals 5. Seeking preventive strategies 6. Evaluating strategies 7. Immediate management	1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00	2.47 (0.76–8.09) 7.38 (2.41–22.55) ^* 0.65 (0.24–1.75) 0.70 (0.24–2.04) 0.52 (0.29–0.92) 1.15 (0.75–1.75) 1.20 (0.77–1.87) 1.23 (0.78–1.97) 1.12 (0.67–1.87) 0.89 (0.53–1.49) 1.60 (0.88–2.88)	4.82 (1.09–21.23) ^* 5.53 (1.18–25.98) ^* 0.25 (0.05–1.24) 0.56 (0.11–2.82) 0.35 (0.18–0.69) ^* 1.23 (0.67–2.24) 1.20 (0.65–2.23) 1.21 (0.64–2.28) 0.91 (0.44–1.91) 0.72 (0.35–1.45) 1.07 (0.53–2.17)
^*P < 0.05.
RSH, recurrent severe hypoglycemia; IAH, impaired awareness of hypoglycemia; DPN, diabetic peripheral neuropathy; CGM, continuous glucose monitoring; CSII, continuous subcutaneous insulin infusion; HPSS; hypoglycemia problem-solving scale.

Diabetic complications, treatment, driving safety, lifestyle factors, and laboratory data

DPN increased in the SH group (P for trend < 0.001, Table 1). Moreover, the prescription rate of mecobalamin increased based on the SH category (P for trend = 0.034, Table 3). No differences were observed in the HbA1c levels or incidence of other complications among the SH categories, except for DPN. The prevalence of IAH increased as the SH category increased (P for trend = 0.009, Table 1). The incidence of a CV-RR of < 3% increased as the SH category increased, but no difference was observed in the rate of abnormal QTc interval (Bazett’s formula) among the groups. Although no difference was found in the rate of treatment and isCGM use among the groups, the rate of rtCGM use decreased as the SH category increased (P for trend = 0.048, Table 3).

Table 3

Diabetes and other treatment of the study participants according to the SH category
Variables	SH categories			P for trend
Variables	Non-SH	Solitary SH	RSH	P for trend
Diabetes treatment CSII SAP CGM usage isCGM rtCGM TDD/BW Basal, % Neuropathy-related medicine, % Mecobalamin Epalrestat Pregabalin and duloxetine	37.4 22.9 57.6 33.2 24.4 0.6 (0.2) 32.7 (14.1) 3.1 0.4 0.4	29.4 11.8 47.1 35.3 11.8 0.7 (0.2) 33.2 (14.5) 11.8 0 5.9	25.0 0.0 25.0 25.0 0 0.6 (0.1) 33.6 (11.2) 12.5 0 0	0.343 0.064 0.051 0.770 0.048 ^* 0.238 0.496 0.034 ^* 0.772 0.169
Anti-hypertensive medicine, % Calcium-channel blockers Angiotensin-converting enzyme inhibitor Angiotensin II receptor blockers Thiazide diuretics Other Cholesterol-lowering medicine, % Statin Ezetimibe Other	23.3 14.1 6.5 11.8 2.3 1.5 25.2 23.3 1.1 2.3	11.8 5.9 5.9 0 0 0 35.3 29.4 5.9 5.9	12.5 12.5 0 0 0 0 50.0 50.0 0 0	0.230 0.519 0.512 0.088 0.473 0.559 0.076 0.086 0.493 0.851
^*P < 0.05.
RSH, recurrent severe hypoglycemia, CSII, continuous subcutaneous insulin infusion; SAP, sensor augmented pump; isCGM, intermittently scanned CGM
rtCGM, real time CGM; TDD; total daily dose; BW, body weight.

The prevalence rate of IAH increased as the SH category increased (P for trend = 0.009). The average Gold’s score of the non-SH, solitary SH, and RSH groups was 2.0 ± 1.3, 2.8 ± 2.0, and 3.5 ± 1.7, respectively (P for trend = 0.009). DPN was associated with an increased risk of solitary and RSH (OR: 7.38 [95% CI: 2.41–22.55] and OR: 5.53 [95% CI: 1.18–25.98], respectively), whereas treatment with CSII and CGM did not. The proportion of late-night dinner increased in the SH categories (P for trend = 0.037, Table 4). No differences were found in smoking, excessive drinking, sleep debt, and non-restorative sleep among the three groups (Table 4). No difference was also found in the laboratory data, including HbA1c level and GA/HbA1c ratio (Table 5).

Table 4

Lifestyle factors of the study participants according to the SH category
Variables	SH categories			P for trend
Variables	Non-SH	Solitary SH	RSH	P for trend
Eating habits Skipping breakfast Fast eating Late-night dinner eating Snack and sweetened beverage Exercise habit Exercise Physical activity Fast walking Overwork Current smoking Alcohol drinking habits Drinking everyday Excessive drinking Healthy lifestyle score Sleep habits average sleep time, min Sleep time in weekday, min Sleep time in weekend, min Sleep debt, % Non-restorative sleep, %	8.8 35.4 25.0 72.8 31.2 53.8 46.9 21.2 17.7 15.8 8.8 4.30 (1.41) 394 (66) 378 (69) 433 (85) 29.1 60.8	25.0 35.3 41.2 94.1 35.3 62.5 35.3 5.9 29.4 29.4 11.8 4.25 (1.18) 393 (47) 379 (50) 425 (69) 35.3 64.7	12.5 12.5 50.0 50.0 37.5 62.5 50.0 25.0 12.5 25.0 25.0 4.38 (1.51) 385 (44) 371 (39) 420 (72) 25.0 50.0	0.152 0.279 0.037 ^* 0.940 0.613 0.445 0.702 0.453 0.706 0.171 0.144 0.948 0.876 0.864 0.899 0.916 0.753
^*P < 0.05.
RSH, recurrent severe hypoglycemia.

Table 5

Laboratory data of the study participants according to the SH category
Variables	SH categories			P for trend
Variables	Non-SH	Solitary SH	RSH	P for trend
TP, g/dl AST, U/L ALT, U/L GGT, IU/L BUN, mg/dL Creatinine, mg/dL eGFR HbA1c, % GA, % GA/HbA1c ratio TC, mg/dL HDL-C, mg/dL	6.9 (0.4) 20.2 (7.3) 17.3 (10.9) 21.3 (18.5) 15.1 (5.2) 0.8 (0.9) 78.0 (20.9) 7.7 (0.9) 21.9 (3.6) 2.9 (0.3) 205.2 (32.6) 78.8 (20.1)	6.8 (0.4) 22.7 (8.8) 19.3 (8.8) 25.8 (28.3) 18.2 (9.5) 1.1 (1.5) 74.8 (25.0) 7.9 (1.1) 23.0 (4.8) 2.9 (0.4) 210.4 (31.8) 85.7 (24.0)	6.8 (0.3) 20.0 (7.6) 17.3 (7.8) 19.0 (12.1) 13.1 (2.9) 1.1 (1.3) 85.2 (11.5) 7.5 (0.6) 22.3 (2.7) 3.0 (0.3) 182.5 (41.3) 70.4 (21.3)	0.114 0.324 0.162 0.785 0.704 0.784 0.488 0.669 0.313 0.507 0.660 0.850
RSH, recurrent severe hypoglycemia; TP, total protein; AST, aspartate transaminase; ALT, alanine transaminase; GGT, gamma-glutamyl transferase;
BUN, blood urea nitrogen; eGFR, estimated glomerular filtration rate; TC, total cholesterol; HDL-C, high-density lipoprotein

Hypoglycemic symptoms, diabetes-related distress, and hypoglycemia problem-solving abilities

Drowsiness, odd behavior, and speech difficulty scores increased in the SH categories. No difference was observed in the autonomic and general malaise scores between the three study groups (Table 6). The average HFS-W score increased as the SH category increased. The average PAID score and the proportion of patients who scored ≥ 40 points increased, but not significantly, as the SH category increased. No differences were found in the PHQ-9, HFS-B, and EQ-5D utility indices among the groups. The average HPSS hypoglycemic problem-solving perception score was significantly lower in the IAH group than in the control group. The average hypoglycemic problem-solving perception score was associated with a decreased risk of solitary and RSH (OR: 0.52 [95% CI: 0.29–0.92] and 0.35 [95% CI: 0.18–0.69], respectively), whereas the scores on other subscales did not.

Table 6

Hypoglycemic symptoms of the study participants according to the SH category
Variables	SH categories			P for trend
Variables	Non-SH	Solitary SH	RSH	P for trend
Autonomic Sweating Palpitations Shaking Hunger Neuroglycopenic Confusion Drowsiness Odd behavior Speech difficulty Incoordination General malaise Headache Nausea Total score	3.5 (1.9) 3.4 (1.8) 3.7 (1.8) 3.6 (1.9) 1.9 (1.5) 2.1 (1.5) 1.6 (1.2) 1.8 (1.4) 2.6 (1.7) 1.8 (1.4) 1.6 (1.2) 26.9 (10.5)	3.6 (2.1) 3.9 (2.0) 3.5 (1.8) 3.5 (1.9) 3.0 (2.3) 2.9 (1.5) 2.3 (1.8) 2.9 (1.9) 3.5 (1.6) 1.8 (1.4) 1.6 (0.9) 32.4 (10.6)	2.8 (2.0) 1.8 (1.2) 2.3 (1.2) 2.6 (2.0) 2.1 (1.6) 4.0 (1.9) 2.5 (1.5) 2.4 (1.6) 2.3 (1.2) 1.4 (0.7) 1.6 (0.7) 25.6 (8.4)	0.614 0.430 0.110 0.365 0.105 < 0.001^* 0.004 ^* 0.014 ^* 0.111 0.820 0.383 0.060
Psychological, points PAID ≥40 PHQ-9 HFS-B HFS-W EQ-5D utility index	30.0 (19.2) 32.2 4.0 (4.1) 17.9 (6.4) 10.3 (9.0) 0.90 (0.14)	33.8 (21.0) 47.1 5.4 (5.2) 18.9 (6.2) 13.5 (10.3) 0.89 (0.17)	37.3 (21.3) 50.0 5.5 (4.4) 20.5 (4.4) 19.5 (13.3) 0.87 (0.16)	0.268 0.121 0.146 0.255 0.014 ^* 0.741
^*P < 0.05.
RSH, recurrent severe hypoglycemia; PAID, problem areas in diabetes; PHQ-9, Patient Health Questionnaire-9;
HFS-B, hypoglycemia fear survey- behavior; HFS-W, hypoglycemia fear survey- worry; EQ-5D, euroqol five dimensions.

This study was the first to identify the protective factors such as hypoglycemia problem-solving perception and the risk factors such as DPN and IAH for RSH in Japanese adults with T1D.

DPN and RSH

Cross-sectional and observational studies have indicated that DPN and cardiac autonomic neuropathy are associated with SH [36,37]. On the contrary, Olsen et al. reported that IAH was not associated with autonomic dysfunction or DPN in adults with T1D [37]. In this study, DPN and abnormal CV-RR were associated with increased risk of RSH. Abnormal CV-RR is a good indicator of autonomic and peripheral neuropathy [39].

In addition, repeated hypoglycemia can cause DPN as reported in animal experiments [40,41]. Therefore, careful attention should be paid to monitoring RSH in adults with T1D and abnormal CV-RR. Further large-scale and long-standing examinations are required to confirm these issues in the future.

Diabetes-related technologies and RSH

In this study, rtCGM usage was associated with a decreased risk of RSH, whereas isCGM usage was not. Moreover, CSII treatment was not associated with a decreased risk of RSH. A previous study by Wohland et al. showed that treatment with CSII reduces the risk of SH [43]. Sensor-augmented insulin pump therapy with predictive low-glucose suspension may be effective in reducing the risk of RSH. Davis et al. reported that isCGM usage did not prevent RSH [43]. Switching from isCGM to rtCGM reduces the risk of SH [44]. Hásková et al. reported that rtCGM was superior to isCGM in reducing the risk of hypoglycemia and improving the T1D duration and normal hypoglycemia awareness [45]. Use of rtCGM reduced the number of hypoglycemic events in individuals with T1D treated with MDI and with IAH or SH [46]. Further examinations, including hypoglycemic alerts and approaches using trend arrows [47], are required to confirm these issues.

Limitation of the study

The strength of the study is that it included a validated self-administered questionnaire. However, our study has some limitations; it only included a small sample of patients with RSH. This study employed a cross-sectional design to make causal inferences. DPN status was estimated as the presence or absence of this condition; therefore, the severity of DPN was not evaluated. DCAN is an under-diagnosed cardiovascular complication in individuals with diabetes. In an animal model, DCAN was evaluated using histological patterns and cardiac nerve density. QTc interval is affected by other factors, such as obesity, arteriosclerotic macroangiopathy, and autonomic nerve function. Nerve conduction studies and sympathetic skin responses are reliable methods for detecting DCAN. Further examinations, including the definite DCAN method, are required to compare the DCAN and IAH status.

Implication for practice

IAH is prevalent among adults with T1D. IAH can be easily identified using validated questionnaire-based methods, such as Gold’s method. The protective factors for IAH, such as rtCGM　use and problem-solving perception, were also identified using the HPSS. A sensor-augmented pump with predictive low-glucose suspend or a hybrid-closed loop system, rtCGM, or structured education should be considered in adults with T1D and IAH. Problem solving, defined as a self-directed cognitive-behavioral process by which individuals attempt to cope with a difficult situation, is a behavioral strategy used in diabetes management. It refers to a mental process that involves discovering, analyzing, and solving problems. Problem-solving perceptions explained most of the variance in the seven factors. This subscale consists of four reverse items: discouraged from failing to prevent hypoglycemia, feeling depressed or angry due to the difficulties in preventing hypoglycemia, worrying about how to prevent hypoglycemia but not taking any action, and reduced self-esteem. DPN is associated with cognitive impairment in adults with T1D. Cognitive impairment may also affect the perception of hypoglycemia. Acceptance and commitment therapy-based interventions for diabetes-related distress [48] may help improve the problem-solving perception of patients. Interventions based on the HPSS effectively improved the HbA1c levels and hypoglycemic problem-solving abilities in individuals with hypoglycemia [49]. In this study, late-night dinner eating, indicating unhealthy eating and disrupted circadian rhythms, was associated with an increased risk of RSH. An educational program promoting an increased problem-solving ability and healthy lifestyle based on the recommendations [50] for adults with T1D and RSH should be considered.

In conclusion, we identified the protective and risk factors for RSH in Japanese adults with T1D. This information may help manage problematic hypoglycemia. RSH has a complex pathophysiology that may lead to serious and potentially lethal consequences in patients with T1D. In clinical practice, physicians should be proactive in asking people with T1D whether, and at which glucose level, they feel hypoglycemic in order to assess for IAH and adjust the individual’s glucose targets to prevent severe hypoglycemia.

CGM: continuous glucose monitoring

CI: confidence interval

CSII: continuous subcutaneous insulin infusion

DCAN: diabetic cardiac autonomic neuropahty

DPN: diabetic peripheral neuropathy

GA: glycated albumin

HbA1c: hemoglobin A1c

HFS: hypoglycemia fear survey

IAH: impaired awareness of hypoglycemia

isCGM: intermittently scanned continuous glucose monitoring

MDI: multiple daily insulin injection

NHO: National Hospital Organization

rtCGM: real-time continuous glucose monitoring

OR: odds ratio

PAID: problem areas in diabetes

SH: severe hypoglycemia

T1D: type 1 diabetes

Ethics approval and consent to participate

Approval of the research protocol: This study was approved by t the National Hospital Organization Central Review Board (NHOCRB/ R2-0117002、R3-0614027)

The written informed consent was obtained from each patient before any trial-related activities were undertaken.

Animal Studies: N/A

Conflict of interest disclosures

None to be declared

Funding

The PR-IAH study with funding from the National Hospital Organization Clinical research (NHO) (Grant number: H31-NHO (Endocrinology and Nephrology)-01).

Authors' contributions

Authors’ contributions statement: NS conceived the ideas. MD analyzed the data. NS acquired the funding. SH, EN, RA, KK, MH, YM, YM, and KK collected the data. NS and AS written the original draft. TM, SS, and FW reviewed and written the article.

Acknowledgments

The authors are grateful to the NHO Diabetology group.

Data availability statement

The datasets generated and/or analysed during the current study are not publicly available due [restrictions e.g. their containing information that could compromise the privacy of research participants] but are available from the corresponding author on reasonable request.

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No competing interests reported.

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Protective and risk factors of recurrent severe hypoglycemia in adults with type 1 diabetes: A cross-sectional analysis of baseline data from the PR-IAH study

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