| Literature DB >> 28322094 |
Xi-Yang Yao1, Cai-Qi Jiang2, Gen-Lai Jia3, Gang Chen1.
Abstract
Objective This systematic review aimed to define the relationship between diabetes mellitus (DM) and the risk of aneurysmal subarachnoid haemorrhage (aSAH). Methods Studies associated with DM and aSAH published until March 2016 were retrieved from Pubmed, Embase, Web of Science, and Cochrane Library databases. A random-effects model was used to calculate the relative risks (RRs) with 95% confidence intervals (CIs). Results Eighteen observational studies were retrieved. The overall RRs for DM and aSAH were RRs = 0.59 (0.44, 0.79), with moderate heterogeneity ( I2 = 55.7%, Pheterogeneity = 0.000). Subgroup analysis by study quality revealed a reduced association between DM and aSAH risk in high quality studies only (RRs = 0.40, 95% CI: 0.29, 0.56; I2 = 0.0%, Pheterogeneity = 0.549), therefore study quality may be a source of heterogeneity. Conclusion A potential decreased risk of aSAH in DM patients was found in high quality studies. Further studies are required to confirm this causal relationship and to investigate the biological mechanisms.Entities:
Keywords: Diabetes; intracranial aneurysm; meta-analysis; subarachnoid hemorrhage; systematic review
Mesh:
Year: 2016 PMID: 28322094 PMCID: PMC5536738 DOI: 10.1177/0300060516666426
Source DB: PubMed Journal: J Int Med Res ISSN: 0300-0605 Impact factor: 1.671
Figure 1.Flow chart of the search procedure.
Main characteristics of the included studies.
| Author, year | Study period/ years of follow-up | Country | Study design | Sex | No. of cases/ No. of controls | RR and 95% CI (DM versus non-DM) | Adjustment |
|---|---|---|---|---|---|---|---|
| Knekt 1991 | 1966–1972/22 | Finland | Cohort | M + F | 187/42862 | M: 0.7 (0.1, 4.7) F: 0 (0, 2.9) | Age |
| Canhao 1994 | 1985–1990 | Portugal | Case-control | M + F | 134/134 | 2.7 (0.9, 8.3) | None |
| Kunze 2000 | 1997–1998 | Germany | Case-control | M + F | 44/44 | 0.06 (0, 1.02) | None |
| Kubota 2001 | NS | Japan | Case-control | M + F | 127/127 | 0.49 (0.09, 2.74) | None |
| Qureshi 2001 | 1990–1997 | United States | Case-control | M + F | 323/969 | 0.7 (0.4, 1.2) | Age, sex, race |
| Mhurchu 2001 | 1995–1998 | Australia/ New Zealand | Case-control | F | 268/286 | 0.47(0.22,1.00) | Age, sex, city of residence |
| Kissela 2002 | 1997–2000 | United States | Case-control | M + F | 107/197 | 0.6 (0.2, 1.6) | Age, sex, race |
| Ohkuma 2003 | 1989–1998 and 2000–2001 | Japan | Case-control | M + F | 390/390 | 0.73 (0.42,1.27) | Age, sex |
| Broderick 2003 | 1994–1999 | United States | Case-control | M + F | 312/618 | 0.75 (0.41,1.38) | Age, sex, race |
| Inagawa 2005 | 1980–1998 | Japan | Case-control | M + F | 247/247 | 0.33 (0.13, 0.84) | Age, sex, hypertension, smoking, drinking, total cholesterol level, heart disease, liver disease |
| Okamoto 2005 | 1992–1997 | Japan | Case-control | M + F | 201/402 | 2.6 (1.2, 6.7) | Age, sex, family history, smoking |
| Sandoval 2009 | 2002–2004 | Mexico | Case-control | M + F | 231/231 | 0.34 (0.17, 0.68) | Age, sex, hypertension, smoking, drinking |
| Koshy 2010 | 2003–2008 | India | Case-control | M + F | 163/150 | 0.34 (0.15, 0.76) | None |
| Inagawa 2010 | 1981–2005 | Japan | Case-control | M + F | 798/798 | 0.41 (0.26, 0.64) | Age, sex, hypertension, smoking, drinking, hypercholesterolemia, heart disease |
| Cui 2011 | NS/median 12.0 | Japan | Cohort | M + F | 122/35657 | M: 0.15 (0.01, 2.47) F: 0.97 (0.3, 3.15) | Age, systolic blood pressure, smoking, drinking, BMI, HDL cholesterol, total cholesterol, triglycerides, antihypertensive medication, fasting status, residential areas. |
| Shiue 2012 | 1995–1998 | Australia/ New Zealand | Case-control | M + F | 432/473 | 0.61 (0.35, 1.06) | None |
| Vlak 2013 | 2006–2009 | Netherlands | Case-control | M + F | 250/574 | 0.5 (0.2, 1.2) | Age, sex |
| Shah 2015 | 1998–2010/NS | England | Cohort | M + F | 11/1921260 | 0.48 (0.26, 0.89) | Age, sex, systolic blood pressure, smoking, BMI, HDL cholesterol, total cholesterol, deprivation, statin and antihypertensive drugs |
Abbreviations: NS, not stated; RR, risk ratio; CI, confidence interval; F, female; BMI, body mass index; HDL, high-density lipoprotein.
Summary of critical appraisal of case-control studies.
| Criteria | Canhao 1994 | Kunze 2000 | Kubota 2001 | Qureshi 2001 | Mhurchu 2001 | Kissela 2002 | Ohkuma 2003 | Broderick 2003 |
|---|---|---|---|---|---|---|---|---|
| Clearly focused issue? | Y | Y | Y | Y | Y | Y | Y | Y |
| Appropriate method? | Y | Y | Y | Y | Y | Y | Y | Y |
| Acceptable case recruitment? | Y | Y | Y | Y | Y | Y | Y | Y |
| Acceptable control recruitment? | Y | C/T | C/T | Y | Y | Y | C/T | C/T |
| Exposure accurately measured? | Y | Y | Y | Y | Y | Y | Y | Y |
| Confounders accounted for? | Y | Y | Y | Y | Y | Y | Y | Y |
| Confounding factors in the design and/or analysis taken account of? | N | N | N | N | N | N | N | N |
| What are the results? | C/T | C/T | C/T | C/T | C/T | C/T | C/T | C/T |
| How precise are the results? | C/T | C/T | C/T | C/T | C/T | C/T | C/T | C/T |
| Do you believe the results? | Y | Y | Y | Y | Y | Y | Y | Y |
| Applicable to the local population? | Y | Y | Y | Y | Y | Y | Y | Y |
| Fits with other available evidence? | N | Y | Y | Y | Y | Y | Y | Y |
| Do you believe the results? | Y | Y | Y | Y | Y | Y | Y | Y |
| Total methodological quality | L | M | M | M | M | M | M | M |
Y-Yes; N-No; H-High; L-Low; M-Moderate; C/T-Cannot tell.
Summary of critical appraisal of cohort studies.
| Criteria | Knekt 1991 | Cui 2011 | Shah 2015 |
|---|---|---|---|
| Clearly focused issue? | Y | Y | Y |
| Acceptable cohort recruitment? | Y | Y | Y |
| Exposure accurately measured? | Y | Y | Y |
| Outcome accurately measured? | Y | Y | Y |
| Important confounding factors identified? | Y | Y | Y |
| Confounding factors in the design and/or analysis taken into account? | N | Y | Y |
| Was the follow-up complete? | Y | Y | Y |
| Was the follow-up long enough? | Y | Y | Y |
| What are the results of the study? | C/T | Y | Y |
| How precise are the results? | C/T | C/T | Y |
| Do you believe the results? | Y | Y | Y |
| Applicable to the local population? | Y | Y | Y |
| Agrees with other evidence? | C/T | Y | Y |
| Total methodological quality | M | H | H |
Y-Yes; N-No; H-High; L-Low; M-Moderate; C/T-Cannot tell.
Figure 2.Forest plots for the risk of diabetes mellitus and aneurysmal subarachnoid hemorrhage.
Synthetic RRs for diabetes mellitus and aneurysmal subarachnoid hemorrhage.
| Synthetic estimation | Heterogeneity | ||||
|---|---|---|---|---|---|
| Subgroup | No. of studies | RR (95% CI) | I2 (%) | ||
| Total studies | 18 | 0.59 (0.44, 0.79) | 0 | 55.7 | 0.001 |
| Study design | |||||
| Cohort | 3 | 0.34 (0.09, 2.14) | 0.103 | 68.4 | 0.013 |
| Case-control | 15 | 0.61 (0.46, 0.82) | 0.001 | 53.1 | 0.008 |
| Study quality | |||||
| High | 5 | 0.38 (0.27,0.54) | 0 | 0 | 0.655 |
| Moderate and Low | 13 | 0.69 (0.47,1.01) | 0.056 | 59.8 | 0.002 |
Abbreviations: RR, relative risk; CI, confidence interval; BMI, body mass index.
Figure 3.Sensitivity analyses for the risk of diabetes mellitus and aneurysmal subarachnoid hemorrhage.
Figure 4.Begg funnel plot for the risk of diabetes mellitus and aneurysmal subarachnoid hemorrhage.