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Abstract

Objective

Subsequent limb amputation (SLA) may be necessary due to disease progression, infection, or to aid prosthesis fit. SLA in Saskatchewan has increased 3.2% from 2006 to 2019 with minor SLA increasing 9.6% during that period. Diabetes affects a large proportion of patients who require SLA; however, the impact of additional comorbidities is not clear.

Methods

First-episode subsequent lower extremity limb amputation (SLEA) cases with the presence/absence of diabetes, other comorbidities, and demographic characteristics from 2006–2019 were retrieved from Saskatchewan's Discharge Abstract Database. Logistic regression was performed to examine the magnitude of the odds of SLEA.

Results

Among the 956 first-episode SLEA patients investigated, 78.8% were diagnosed with diabetes. Of these, 76.1% were male and 83.0% were aged 50 + years. Three comorbidities: renal failure (AOR = 1.9, 95% Cl 1.1 − 3.0), hypertension (AOR = 3.0, 95% Cl 2.0 − 4.5), and congestive heart failure (AOR = 2.0, 95% CI 1.2 − 3.2), conferred the highest odds of SLEA. The odds of SLEA is greatest for those aged 50–69 years, males, Registered Indians, and associated with a prolonged hospital stay.

Discussion

These data are important as they may help medical providers identify patients at the highest risk of SLEA and target interventions to optimize outcomes.

Keywords

subsequent amputation lower extremity epidemiology diabetes comorbidity

Introduction

The overall rate of limb amputation has remained stable over two decades in Saskatchewan despite increasing community efforts to educate and manage people with diabetes, the leading cause of lower extremity amputation.¹ Subsequent limb amputation (SLA), defined as ipsilateral revision amputation or contralateral index (single) amputation, may be performed to mitigate disease progression, reduce pain and enhance prosthesis fit.^2–4 A recent meta-analysis by Liu et al. (2021) found SLA rates of 19% at 1 year and 37.1% at 5 years in people with diabetes.⁵ This frequently performed procedure may be devastating,² along with a high rate of hospital readmission, extended post-operative hospital stay, and an increased risk of mortality when compared to index amputation.^3,6–8

People with diabetes have a high prevalence of multimorbidity including, but not limited to, hypertension (HTN), heart disease, chronic kidney disease, ischemic heart disease, peripheral arterial disease (PAD), and stroke.^3,9,10 These comorbidities may differentially impact SLA however, conflicting reports exist in the literature.^3,11 Fard et al. found no risk factors associated with 1-year re-amputation among patients in Northern Netherlands,¹¹ while Norvell and Czerriecki found several risk factors, including chronic obstructive pulmonary disease, kidney failure, and diabetes among patients with limb amputation in the United States.³ Further, Littman et al. found substantial geographical and ethnoracial variation contributing to SLA rates after minor (below the level of the ankle) amputation with greater risk among African American patients than white patients and those living in the southeast region of the United States compared to other regions.¹²

In Saskatchewan, the rate of SLA (10.6 per 100,000 population) is steadily rising with a 3.2% average annual percent change from 2006−2019 ¹³; this, in combination with a 45% provincial increase in overall diabetes prevalence over the last decade,¹⁴ leads to the question of how epidemiologic correlates impact the rate of SLA in the province.

Addressing this gap may provide useful information to avoid the devastating impact of SLA, preserve limb length after index LA and enhance ambulatory function.¹⁵ Additionally, identifying the demographic characteristics and most prevalent comorbidities may allow for targeted interventions to alter the rate of subsequent lower extremity amputation (SLEA). Therefore, the purpose of this study is to explore potential risk factors including comorbidities and demographic characteristics of SLEA among patients in Saskatchewan.

Methods

A cohort of patients with first-episode SLEA was identified and retrieved from Saskatchewan's Discharge Abstract Database (SK-DAD). The SK-DAD is part of Canada's nationally collated hospital abstract databases¹⁶ that compiles health information from all hospital discharges in the province under the provincially managed Canadian universal single-payer healthcare system. Health information captured in the SK-DAD includes demographic and clinical data for discharges of inpatient acute care, chronic illnesses, rehabilitation, and surgical procedures.¹⁶ The SK-DAD accommodates up to 25 diagnoses defined by the Canadian adaptation of the International Classification of Diseases codes (ICD-10-CA) and 20 interventions defined by the Canadian Classification of Health Intervention codes (CCI) per hospitalization.¹

The SK-DAD is similar to the national discharge data collated by the Diagnosis-Related Group Statistics (DRG-Statistics) in Germany,¹⁷ which captures Germany's all acute care hospital inpatient cases, diagnoses defined by the German adaptation of the International Classification of Diseases (ICD-10-GM), German intervention procedure codes (OPS), demographic information and discharge status.¹⁷ Furthermore, the SK-DAD is also comparable to the Swedish National Inpatient Register (INP) comprises the Hospital Discharge Register^18,19 and links several national Swedish registers via a unique Swedish personal identifier number.^18,19 In the Swedish INP, limb amputation cases are defined by the Nordic Classification of Surgical Procedure (NCSP), and diagnosis is defined by the International Classification of Diseases (ICD-10).¹⁸ Sweden, like Germany and Canada, has a universal health care system, with coverage provided to all inhabitants irrespective of their income level,²⁰ making limb amputation data more comparable in these countries. For example, NCSP codes (NFQ09, NFQ19, NGQ09, NEQ19, NGQ 19, NHQ09, and NHQ11) are for major lower limb above-knee amputation (LL-AKA) and lower limb below-knee amputation (LL-BKA) in Sweden.¹⁸ And this is equivalent to the Canadian CCI code (1VC 93, 1VQ93, 1VA93, 1SQ93, 1WA93, and 1VG93) for major LL- AKA and LL-BKA¹ and German OPS code (5-864).^17,21 Also, the lower limb minor amputation (LLA) OPS codes 5-865 in Germany^17,21 are equivalent to CCI codes (1WE93, 1WI93, 1WJ93, 1WK93, 1WL93, 1WM93, 1WN93) for minor LLA in Canada¹ and NCSP codes NHQ12, NHQ13 and NHQ14 in Sweden.¹⁸ Likewise, the diagnosis code (ICD-10-CA) for diabetes E10-E14 in Canada is the same as the diabetes diagnosis code E10-E14 in German (ICD-10-GM)^17,21 and ICD-10 codes in Sweden.¹⁸

The present study data included all patient cases from January 1, 2006, to December 31, 2019, which were identified in the SK-DAD using the Canadian Classification of Health Interventions procedure codes that describe the various levels and specific anatomical sites of amputation (CCI: 1SQ93, 1VA93, 1VC93, 1VG93, 1VQ93, 1WA93, 1WE93, 1WI93, 1WJ93, 1WK93, 1WL93, 1WM93, 1WN93) (see Appendix 1 for the description of each code).²² The primary outcome variable of interest was SLEA in patients diagnosed with diabetes. The diabetes diagnosis history of each patient was accessed five years prior to the index LEA intervention date using the International Classification of Disease (ICD-10-CA) codes for diabetes E10-E14 (E10.2-E10.8, E11.2-E11.8, E12.2-E12.8, E13.2-E13.8, E14.2-E14.8) ²³ (see Appendix 1 for the description of each code)²⁴ and index into a binary indicator (‘Yes’ representing the presence of diabetes and ‘No’, absence of diabetes) via the Elixhauser comorbidity index.²⁵

In a similar manner, other comorbidities, including peripheral vascular disease (PVD), renal failure, HTN, arrhythmia, congestive heart failure (CHF), and cardiovascular disease (CVD) status was accessed. The present study accounted for these comorbidities due to their demonstrated direct or indirect influence on diabetes-related limb amputation research.^26–28

The demographic characteristics of patients, including age (0–49 years, 50–59 years, 60–69 years, and 70 + years), sex (female/male), and location of residence, determined by postal code population (rural < 1000 and urban ≥1000)^29,30 were retrieved from the Person Health Registration System (PHRS). Due to the unavailability of data on the location of residence in the years 2018−2019, the 2017 location of residence was used as a surrogate for those years. The patient's post-operative acute care length of stay (POALOS) after the SLEA procedure was also included in the present study as an explanatory variable. POALOS was calculated as patients’ discharge date minus intervention date, recorded in days, and grouped into short (≤ 7 days) and prolonged (> 7 days).^31,32 The Saskatchewan administrative data repository does not capture a person's ethnicity, but the data repository can identify self-declared First Nations (FN) persons registered under the Indian Act of Canada,³³ further referred to as Registered Indians (RI), and other Saskatchewan residents (including whites, immigrants, Indigenous peoples with registered Indian status who have not self-identified in the PHRS, non-registered Indian status, Metis and Inuit peoples). For clarity, this study would refer to the other Saskatchewan residents as the General Population (GP) cohort. The 2016 Canadian census reported 106,440 people with RI status representing 60.8% of the 175,015 Indigenous people living in Saskatchewan.³⁴

Statistical analysis

Descriptive analyses specifically, frequencies and proportions were used to describe the study population demographic characteristics and the presence of comorbidities. A multiple logistic regression (MLR) analysis^35,36 was also applied to assess potential comorbidities and other risk factors associated with SLEA in the presence of diabetes. The MLR process began by first fitting an unadjusted model between the outcome of interest and each comorbidity and demographic factor. All comorbidities and factors with p-values <0.25³⁵ in the unadjusted model were considered candidates for the adjusted model. The final adjusted model was arrived at by implementing the manual backward elimination method to eliminate all factors with p-values that exceed the set significant level of 0.05.³⁵

Change in estimate method was used to assess potential confounding factors³⁷ and interactions evaluated by Hosmer et al.'s model-building approach.³⁵ Finally, the odds ratio (OR) and its companion 95% confidence interval were reported from the study models.

Results

The demographics and comorbidities of patients are presented in Table 1. Of the 956 patients with first-episode SLEA investigated, 78.8% (753) were diagnosed with diabetes, and 21.2% (203) had no diagnosis of diabetes. Among the SLEA patients with diabetes, the majority, 59.1% (445) were 60 + years of age, whereas in the cohort without diabetes, those aged 70 + years reported the highest proportion, 41.3% (84), followed by patients aged 0–49 years, 28.1% (57). Males dominated both study groups, with 76.1% (573) of SLEA among diabetes patients reported in males and 64.0% (130) of SLEA without diabetes being males. SLEA was more common in urban dwellers with 57.7% (435) and without 62.1% (126) diabetes than their counterparts residing in the rural areas. Individuals with diabetes reported a higher proportion, 48.7% (367), of prolonged hospital stay after SLEA than the proportion of extended hospitalization witnessed in those without diabetes 36.9% (75), with median days of stay being 7 days vs. 5 days respectively. SLEA proportion reported in the general population (GP) with and without diabetes was 65.7% vs. 90.2% compared to 34.3% vs. 9.8% in Registered Indians (RI).

Table 1.

Demographic characteristics and comorbidities in subsequent lower extremity amputation patients with and without diabetes.

Variables	SLEA with diabetes N = 753, 78.8%	SLEA without diabetes N = 203, 21.2%
Age/years
0 − 49	128 (17.0%)	57 (28.1%)
50 − 59	180 (23.9%)	31 (15.3%)
60 − 69	233 (30.9%)	31 (15.3%)
70 +	212 (28.2%)	84 (41.3%)
Sex
Female	180 (23.9%)	73 (36.0%)
Male	573 (76.1%)	130 (64.0%)
Location of Residence
Rural	318 (42.3%)	77 (37.9%)
Urban	435 (57.7%)	126 (62.1%)
Post-Operative Acute Care Length of Stay (POALOS)/days
≤ 7	386 (51.3%)	128 (63.1%)
> 7	367 (48.7%)	75 (36.9%)
Population Groups
General Population (GP)	495 (65.7%)	183 (90.2%)
Registered Indian (RI)	258 (34.3%)	20 (9.8%)
Peripheral Vascular Disease (PVD)
No	277 (36.8%)	98 (48.3%)
Yes	476 (63.2%)	105 (51.7%)
Renal Failure
No	491 (65.2%)	175 (86.2%)
Yes	262 (34.8%)	28 (13.8%)
Hypertension (HTN)
No	165 (21.9%)	93 (45.8%)
Yes	588 (78.1%)	110 (54.2%)
Arrhythmia
No	547 (72.6%)	152 (74.9%)
Yes	206 (27.4%)	51 (25.1%)
Cardiovascular Disease (CVD)
No	185 (24.6%)	72 (35.5%)
Yes	568 (75.4%)	131 (64.5%)
Congestive Heart Failure (CHF)
No	511 (67.9%)	171 (84.2%)
Yes	242 (32.1%)	32 (15.8%)

Three comorbidities for SLEA dominated in both individuals with and without diabetes. These were peripheral vascular disease (diabetes 63.2% vs. non-diabetes 51.7%), HTN (diabetes 78.1% vs. non-diabetes 54.2%) and CVD (diabetes 75.4% vs. non-diabetes 64.5%).

Table 2 summarizes the unadjusted and adjusted model results of demographic characteristics and comorbidities associated with subsequent LEA among individuals with diabetes. The unadjusted results showed significant differences in age, sex, population subgroups, renal failure, HTN, CHF (p < 0.001), POALOS, cardiovascular disease (p < 0.002), and peripheral vascular disease (p < 0.003) associated with SLEA in patients with diabetes. In contrast, location of residence (p = 0.270) and arrhythmia (p = 0.524) were not significantly associated with SLEA in patients with diabetes.

Table 2.

Demographic characteristics and comorbidities associated with diabetic subsequent lower extremity amputation.

	Unadjusted Model			Adjusted Model
Variables	UOR	95% Cl	P-value	AOR	95% Cl
Age/years
0 − 49	1.0			1.0
50 − 59	2.6	(1.6 − 4.2)	<0.001	2.5	(1.4 − 4.5)
60 − 69	3.4	(2.1 − 5.5)		2.9	(1.7 − 5.2)
70 +	1.1	(0.8 − 1.7)		0.9	(0.5 − 1.5)
Sex
Female	1.0			1.0
Male	1.8	(1.3 − 2.5)	<0.001	2.2	(1.5-3.3)
Location of Residence
Rural	1.0
Urban	0.8	(0.6 − 1.2)	0.270
POALOS
Short (≤ 7 days)	1.0			1.0
Prolonged (> 7 days)	1.6	(1.1 − 2.2)	0.002	1.5	(1.1 − 2.2)
Population Groups
General Population (GP)	1.0			1.0
Registered Indian (RI)	4.8	(2.9 − 7.8)	<0.001	5.9	(3.4 − 10.2)
Peripheral Vascular Disease (PVD)
No	1.0
Yes	1.6	(1.2 − 2.2)	0.003
Renal Failure
No	1.0			1.0
Yes	3.3	(2.2 − 5.1)	<0.001	1.9	(1.1-3.0)
Hypertension (HTN)
No	1.0			1.0
Yes	3.0	(2.2 − 4.2)	<0.001	3.0	(2.0 − 4.5)
Arrhythmia
No	1.0
Yes	1.1	(0.8-1.6)	0.524
Cardiovascular Disease (CVD)
No	1.0
Yes	1.7	(1.2 − 2.4)	0.002
Congestive Heart Failure (CHF)
No	1.0			1.0
Yes	2.5	(1.7 − 3.8)	<0.001	2.0	(1.2 − 3.2)

When other person-level factors and comorbidities were adjusted for, four demographic characteristics (age, sex, length of hospital stay, population subgroups) and three comorbidities (HTN, renal failure, CHF) were found to be associated with SLEA in patients with diabetes. Age 50–69 years increased the odds of SLEA in patients with diabetes by 2.5−2.9-fold (50−59 years: AOR = 2.5, 95% Cl 1.4−4.5; 60–69 years: AOR = 2.9, 95% Cl 1.7−5.2) than age 0–49 years. However, the odds of SLEA in patients with diabetes attenuated at age 70 + years (AOR = 1.1, 95% CI 0.8 −1.7). The sex of the study population also contributed significantly to SLEA in patients with diabetes, with 2.2 times higher odds of SLEA in males (AOR = 2.2, 95% Cl 1.5−3.3) than females. In addition, the odds of having pronged POALOS after SLEA with diabetes increased by 1.5-fold (AOR = 1.5, 95% Cl 1.1−2.2). Further, in the presence of diabetes, Registered Indians (RI) were 5.9 times more likely to have SLEA than the general population (AOR = 5.9. 95% Cl 3.4−10.2).

Three comorbidities conferred the strongest odds of SLEA in individuals with diabetes, with renal failure, increasing the odds by 1.9-fold (AOR = 1.9, 95% Cl 1.1−3.0), HTN by 3.0-fold (AOR = 3.0, 95% Cl 2.0−4.5), and CHF by 2.0-fold (AOR = 2.0, 95% Cl 1.2−3.2).

Discussion

The need for SLEA among patients is confounded by other comorbidities. We found that over a 14-year-study period, approximately 79% of people who had first-episode SLEA in Saskatchewan also had a history of diabetes. Further, a diagnosis of HTN increased the odds of SLEA by 3.0-fold, renal failure by 1.9-fold, and CHF by 2.0-fold in people with diabetes. People with diabetes aged 50–69 years had a 2.5–2.9-fold increased odds of SLEA than those aged 0–49 years, with lower odds observed in those aged 70 + years. Males with diabetes were 2.2 times more likely than females to have SLEA, and Registered Indians (RI) were 5.9 times more likely to have SLEA than the general population (GP). In addition, people with diabetes were 1.5 times more likely to have prolonged POALOS after SLEA compared to people without diabetes. When other person-level factors and comorbidities were adjusted for, location of residence, peripheral vascular disease (PVD), arrhythmia, and cardiovascular disease (CVD) were not significantly associated with SLEA in individuals with diabetes.

Our finding that HTN increased the odds of SLEA by 3.0-fold in people with diabetes is supported by the literature.^27,38–40 Alshallwi (2019) found that HTN increased the odds of SLEA by 3.7-fold in patients with diabetes.³⁸ A similar trend was observed in Seçkin et al.'s study where HTN increased the odds of subsequent amputation in patients with diabetes by 2.2-fold. Our findings that CHF increases the odds of SLEA by 2.0-fold in patients with diabetes are consistent with the findings of Zhang et al., who identified a 1.5-fold odds of 1-year re-amputation in patients with CHF and diabetes.⁴¹

Although the association between renal failure and LEA among diabetes patients has been broadly studied,^42,43 few studies have attempted to specifically examine the association of SLEA^6,39,44,45 in patients also diagnosed with diabetes.^3,46 These studies, similar to ours, suggest that having renal failure in addition to diabetes increases the risk of SLEA.^3,46 Acar and Kacira (2017) found that patients with diabetic nephropathy had 2.8 times higher odds of re-amputation,⁴⁶ but Seçkin et al. found chronic renal failure was not a risk factor for re-amputation among patients with diabetes.⁴⁰

Our finding in the unadjusted model that PVD and CVD were associated with SLEA in individuals with diabetes did not persist in the adjusted model. These latter findings are in line with those of Seçkin et al., in which peripheral arterial disease (PAD) did not significantly increase the risk of re-amputation in patients with diabetes.⁴⁰ However, other studies found a significant association between SLEA and PVD/PAD.^27,38,41 The inconsistencies in the association between SLEA and PVD/PAD and renal failure warrant further studies explicitly focusing on these factors.

We found that ethnicity, specifically First Nations Saskatchewanians registered under the Indian Act of Canada, with diabetes were 5.9 times more likely to undergo SLEA than people in the general population with diabetes. This finding was the most divergent of all variables studied and questions why such a large disparity exists. Although disparities in LEA rates have been recently identified in the literature, including our previously reported findings that the overall rate of limb amputation for RI was 1.7 to 4.2 times higher than that of GP, we did not anticipate an even greater disparity in SLEA rates.^12,47,48 Littman et al. found higher SLEA rates in African Americans than whites in the 90 days after initial toe amputation (202 versus 149 per 1000 patients, respectively) in military veterans with diabetes.¹² Gandjian et al. found higher rates of overall (1.16) and primary (1.34) major amputation in nonwhites than whites living in California after diagnosis of acute limb ischemia,⁴⁷ and Tan reported African Americans were at a 1.9% greater risk and Native Americans were at a 1.8% greater risk of major amputation when compared with whites after diagnosis of diabetic foot ulceration or infection.⁴⁸ The root of these disparities is multifactorial, with sociodemographic factors (economic, racism, health care accessibility, health behaviours, and stresses associated with systemic racism) and biologic factors, including diabetic phenotypes and risks of diabetic complications that may differ among ethnic groups and contribute to the imbalance in SLEA, and LEA, identified between First Nations and non-First Nations Saskatchewanians.^49–51 This highlights the need to explore diabetes phenotypes among ethnic groups to tailor treatment needs.

Our findings also identified that advancing age, specifically age 50−69 years increased the risk of SLEA in patients with diabetes. Interestingly, the risk attenuated with age 70 + years. These findings are partly supported by Zambetti et al. and Erşen et al., who reported an association of ages 68.8 ± 10.8 years and 60.8 ± 17.1 years, respectively, were associated with re-amputation.^6,52

The differential impact of sex on SLEA among patients with diabetes in the present study is reflective of the differences in the prevalence of males diagnosed with diabetes (76.1%) compared to 23.9% of females. We identified that males diagnosed with diabetes were 2.2 times more likely than females to undergo SLEA. These findings are supported by Johannesson et al. who found a higher incidence rate of re-amputation in men with diabetes than in females (21 per 100 amputee-years vs. 16 per 100 amputee-years).⁵³ And further re-echoed by Acar and Kacira (2017), who found adult males with diabetes had 4.1 times increased odds of re-amputation.⁴⁶

In the present study, patients with diabetes had a 1.5-fold higher risk of prolonged POALOS after SLEA (7 days vs. 5 days) when compared to patients without diabetes. Although Zambetti et al. did not limit their study to diabetes patients, their findings were similar to increased length of hospital stay found when re-amputation occurred within 30 days of index amputation (12.9 days vs. 7.3 days).⁶ Likewise, Yaghi et al.'s who broadly explored the length of stay among diabetes and non-diabetic patients with limb amputation but not limited to re-amputation cohorts found the risk of prolonged stay of LA in diabetes patients was 4.6 times higher than in non-diabetic patients.⁵⁴ As an explanation, Ceyhan et al. observed that re-amputated patients do experience prolonged lengths of hospital stay because they are prone to more postoperative complications than their counterparts.⁵⁵ These postoperative complications include renal disease, a history of sepsis, and contaminated/infected wounds, especially in diabetes patients.^56,57

Strengths and limitations

Subsequent LEA is an area that has not been well explored in literature as in the case of index amputation, hence it was a strength of this study to explicitly focus on this neglected area of research. Also, since the incidence of SLEA could be impacted by many personal-level factors and comorbidities, it was a strength that the present study accounted for several of these factors. Due to limited samples, we could not stratify the data for subsequent levels of amputation (minor/major) and explore potential risk factors by these levels. This is because further stratification by amputation level would cause the study to lack statistical power. The limitation on using the 2017 location of residence as a proxy for the years 2018 and 2019 and its possible impact on the study variable is reported elsewhere.⁵⁸

Conclusion

Among this first-episode SLEA cohort diagnosed with diabetes, three comorbidities, renal failure, CHF, and HTN conferred the highest odds of SLEA. Also, the risk of SLEA is greatest for those aged 50–69 years, males, Registered Indians (RI), and is associated with prolonged POALOS. Although not all SLEA is avoidable, risk factors associated with diabetes may be independently treated thus may mitigate the need for SLEA. Our most dispirit finding, that First Nations Saskatchewanians registered under the Indian Act of Canada with diabetes were 5.9 times more likely to undergo SLEA than the general population, is among the areas in need of further in-depth study to target the root causes of the disparity.

Footnotes

Disclaimer

This study is based in part on de-identified data provided by the Saskatchewan Ministry of Health and eHealth Saskatchewan. The interpretation and conclusions contained herein do not necessarily represent those of the Government of Saskatchewan, the Saskatchewan Ministry of Health, or eHealth Saskatchewan.

Acknowledgements

We thank the Saskatchewan Amputee Patient-Oriented Research Team (PORT) and the Saskatchewan Centre for Patient-Oriented Research for their support throughout this study.

Contributorship

SKE and AZL conducted the literature reviews. SKE and AZL conceptualized and designed the study. SKE and AZL secured the study data, performed the analyses, interpreted the results, and drafted the manuscript. All authors have read and approved the final submitted copy.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical approval

This study received ethical approval from the Biomedical Ethics Board (Approval number # Bio 1590).

Informed Consent

Informed consent was waived by the Biomedical Ethics committee, as the study presents no risk of harm to the study subjects.

Guarantor

* SKE

ORCID iD

Samuel Kwaku Essien

Appendix 1

CCI CODES

Lower extremity amputations

Major

1SQ93 = Amputation at pelvis

1VA93 = Amputation at hip joint

1VC93 = Amputation at femur

1VG93 = Amputation at knee joint

1VQ93 = Amputation at tibia and fibula

1WA93 = Amputation at ankle joint

Minor

1WE93 = Amputation at tarsal bones and intertarsal joints (hindfoot, midfoot)

IWI93 = Amputation at first metatarsal bone and first metatarsophalangeal joint

1WJ93 = Amputation at tarsometatarsal joints, other metatarsal bones and other metatarsophalangeal joints (i.e., forefoot)

1WK93 = Amputation at first phalanx of foot

1WL93 = Amputation at phalanx of other foot

1WM93 = Amputation at other interphalangeal joints of toe

1WN93 = Amputation at first interphalangeal joint of toe

International Classification of Diseases ICD-10-CA, 10^th Revision, Canada

References

Essien

Kopriva

Linassi

, et al. Trends of limb amputation considering type, level, sex and age in Saskatchewan, Canada 2006–2019: an in-depth assessment. Arch Public Health 2022; 80: 1–19.

Condie

Ambler

. Re-amputation: time for Major revision of current practice? Eur J Vasc Endovasc Surg 2020; 60: 622.

Norvell

Czerniecki

. Risks and risk factors for ipsilateral Re-amputation in the first year following first Major unilateral dysvascular amputation. Eur J Vasc Endovasc Surg 2020; 60: 614–621.

Pascale

Potter

. Residual limb complications and management strategies. Curr Phys Med Rehabil Rep 2014; 2: 241–249.

Liu

Petersen

Rothenberg

, et al. Lower extremity reamputation in people with diabetes: a systematic review and meta-analysis. BMJ Open Diabetes Res Care 2021; 9: e002325.

Zambetti

Stiles

Gupta

, et al. Analysis of early lower extremity Re-amputation. Ann Vasc Surg 2022; 81: 351–357.

Dillingham

Pezzin

Shore

. Reamputation, mortality, and health care costs among persons with dysvascular lower-limb amputations. Arch Phys Med Rehabil 2005; 86: 480–486.

Ebskov

Josephsen

. Incidence of reamputation and death after gangrene of the lower extremity. Prosthet Orthot Int 1980; 4: 77–80.

Lin

Jeon

Romano

, et al. Rates and timing of subsequent amputation after initial minor amputation. J Vasc Surg. 2020; 72: 268–275.

, et al. Risk factors for ipsilateral reamputation in patients with diabetic foot lesions. Int J Low Extrem Wounds 2009; 8: 69–74.

, et al. Mortality, reamputation, and preoperative comorbidities in patients undergoing dysvascular lower limb amputation. Ann Vasc Surg 2020; 64: 228–238.

, et al. Risk of ipsilateral reamputation following an incident toe amputation among US military veterans with diabetes, 2005–2016. Diabetes Care 2020; 43: 1033–10340.

, et al. The influence of primary and subsequent limb amputation on the overall rate of limb amputation in Saskatchewan, Canada, 2006–2019: a population-based study. BMC Surg 2021; 21(1): 1–19.

14.

Diabetes in Canada. Diabetes in Saskatchewan [Internet]. Diabetes Canada; 2018 . Available from: https://www.diabetes.ca/DiabetesCanadaWebsite/media/About-Diabetes/Diabetes%20Charter/2018-Backgrounder-Saskatchewan_JK_AB-edited-13-March-2018.pdf (2018, accessed 13 November 2018).

15.

Fleming

O’Daniel

Bharmal

, et al. Application of the orthoplastic reconstructive ladder to preserve lower extremity amputation length. Ann Plastic Surg 2014; 73: 183–189.

16.

Canadian Institute for Health Information [Internet]. Data quality documentation, Discharge Abstract Database—Multiyear information. Ottawa (ON): CIHI Canada; 2012. Available from: https://www.cihi.ca/sites/default/files/dad_multi-year_en_0.pdf (2012, accessed 1 July 2022).

17.

Spoden

Nimptsch

Mansky

. Amputation rates of the lower limb by amputation level–observational study using German national hospital discharge data from 2005 to 2015. BMC Health Serv Res 2019; 19: 1–9.

18.

Jarl

Johannesson

Carlberg

, et al. Incidence of lower-limb amputations in Sweden from 2008–2017. Eur J Vasc Endovasc Surg. 2022.

19.

Ludvigsson

Andersson

Ekbom

, et al. External review and validation of the Swedish national inpatient register. BMC Public Health 2011; 11: 1–6.

20.

New York State Government [Internet]. Foreign Countries with Universal Health Care. Department of Health New York State; 2022 . Available from: https://www.health.ny.gov/regulations/hcra/univ_hlth_care.htm (2022, accessed 1 July 2022).

21.

Kröger

Berg

Santosa

, et al. Lower limb amputation in Germany: an analysis of data from the German federal statistical office between 2005 and 2014. Dtsch Arztebl Int 2017; 114: 130.

22.

Canadian Institute for Health Information. Canadian Classification of Health Interventions [Internet]. CIHI Canada; 2015 . Available from: https://www.cihi.ca/sites/default/files/cci_volume_four_2015_en_0.pdf (2015, accessed 24 October 2020).

23.

Canadian Institute for Health Information. International Statistical Classification of Diseases and Related Health Problems [Internet]. CIHI Canada; 2015. Available from: http://assets.ibc.ca/Documents/Auto%20Insurance/ICD-10-CA%202015.pdf.(2015, accessed 1 July 2022).

24.

Manitoba Centre for Health Policy. Concept: Elixhauser Comorbidity Index [Internet]. University of Manitoba; 2020. Available from: http://mchp-appserv.cpe.umanitoba.ca/viewConcept.php?printer=Y&conceptID=1436 (2020, accessed 11 September 2022).

25.

Elixhauser

Steiner

Harris

, et al. Comorbidity measures for use with administrative data. Med Care 1998; 36: 8–27.

26.

Wong

Stern

Rick

, et al., The risk of subsequent amputation following an initial lower extremity amputation: a systematic review. Int J Diabetol Vasc Dis Res 2016; 4: 171–177.

27.

Pemayun

Naibaho

Novitasari

, et al. Risk factors for lower extremity amputation in patients with diabetic foot ulcers: a hospital-based case-control study. Diabet Foot Ankle 2015; 6: 29629.

28.

Heart Research Institute. Help prevent limb amputation [Internet]. New South Wales: HRI; 2019 . Available from https://www.hri.org.au/news/help-prevent-limb-amputation (accessed 4 December 2021).

29.

Statistics Canada. Data and definition [Internet]. Ottawa: Statistics Canada; 2008 [cited 2021 April 14]. Available from: https://www150.statcan.gc.ca/n1/pub/21-006-x/2008008/section/s2-eng.htm (accessed 14 April 2021).

30.

Manitoba Centre for Health Policy (MCHP). 1991&1996 Census Definitions: Urban Area [Internet]. University of Manitoba; 2002 [cited 2022 April 14]. Available from: http://mchp-appserv.cpe.umanitoba.ca/concept/urban_91_96.html#:∼:text=6041 URBAN AREA (UA)&text=Statistics Canada defines an urban,urban areas is considered rural (2002, accessed 14 April 2022).

31.

Kayssi

de Mestral

Forbes

, et al. A Canadian population-based description of the indications for lower-extremity amputations and outcomes. Can J Surg 2016; 59: 99.

32.

Batten

Kuys

McPhail

, et al. Demographics and discharge outcomes of dysvascular and non-vascular lower limb amputees at a subacute rehabilitation unit: a 7-year series. Aust Health Rev 2015; 39: 76–84.

33.

Statistics Canada. Registered or Treaty Indian status of person [Internet]. Ottawa: Statistics Canada; 2019 [Cited 2020 Dec 14]. Available from: https://www23.statcan.gc.ca/imdb/p3Var.pl?Function=DEC&Id=42932 (2019, accessed 14 December 2020).

34.

Statistics Canada. Focus on Geography Series, 2016 Census [Internet]. Ottawa: Statistics Canada; 2016 [Cited 2020 Nov 18, 2020]. Available from: https://www12.statcan.gc.ca/census-recensement/2016/as-sa/fogs-spg/Facts-PR-Eng.cfm?TOPIC=9&LANG=Eng&GK=PR&GC=47 (2016, accessed 18 November 2020).

35.

Hosmer

Jr Lemeshow

Sturdivant

. Applied logistic regression. 3rd ed. Hoboken (NJ): John Wiley & Sons; 2013.

36.

Menard

. Logistic regression: From introductory to advanced concepts and applications. Thousand Oaks (CA): Sage Publications, Inc.; 2010.

37.

Mickey

Greenland

. The impact of confounder selection criteria on effect estimation. Am J Epidemiol 1989; 129: 125–137.

38.

Alshallwi

. Evaluation of risk factors in diabetic foot ulcers patient as predictors of lower extremity amputation: a hospital-based case-control study. J Med Sci and Clin Res 2019; 7: 134–140.

39.

Baril

Gooney

Robinson

, et al. Prior contralateral amputation predicts worse outcomes for lower extremity bypasses performed in the intact limb. J Vasc Surg 2012; 56: 353–360.

40.

Seçkin

Özcan

Çamur

, et al. Predictive factors and amputation level for reamputation in patients with diabetic foot: a retrospective case-control study. J Foot Ankle Surg 2022; 61: 43–47.

41.

Zhang

Canner

Kayssi

, et al. Geographical socioeconomic disadvantage is associated with adverse outcomes following major amputation in diabetic patients. J Vasc Surg 2021; 74: 1317–1326.

42.

Margolis

Hofstad

Feldman

. Association between renal failure and foot ulcer or lower-extremity amputation in patients with diabetes. Diabetes Care 2008; 31: 1331–1336.

43.

Shatnawi

Al-Zoubi

Hawamdeh

, et al. Predictors of major lower limb amputation in type 2 diabetic patients referred for hospital care with diabetic foot syndrome. Diabetes Metab Syndr Obes: Targets and Ther 2018; 11:313.

44.

Glaser

Bensley

Hurks

, et al. Fate of the contralateral limb after lower extremity amputation. J Vasc Surg 2013; 58: 1571–1577.

45.

Stuart

Kimmel

Jolly

. Incidence of lower limb amputation in central Australia. Aust Health Rev 2021; 45: 361–367.

46.

Acar

Kacıra

. Predictors of lower extremity amputation and reamputation associated with the diabetic foot. J Foot Ankle Surg 2017; 56: 1218–1222.

47.

Gandjian

Sareh

Premji

, et al. Racial disparities in surgical management and outcomes of acute limb ischemia in the United States. Surg Open Sci 2021; 6: 45–50.

48.

Tan

Armstrong

Concha-Moore

, et al. Association between race/ethnicity and the risk of amputation of lower extremities among medicare beneficiaries with diabetic foot ulcers and diabetic foot infections. BMJ Open Diabetes Res Care 2020; 8: e001328.

49.

Ahlqvist

Storm

Käräjämäki

, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. The Lancet Diabetes & Endocrinology 2018; 6: 361–369.

50.

Liu

Dou

Zheng

, et al. Association between abnormal glycemic phenotypes and microvascular complications of type 2 diabetes Mellitus outpatients in China. Diabetes, Metab Syndr Obes: Targets Ther 2020;13:4651.

51.

Byrne

Nkongolo

. Genetic susceptibility for type 2 diabetes mellitus among north American aboriginals. International Journal of Medicine and Medical Sciences 2012; 4: 220–231.

52.

Erşen

Kilinç

Bilekli

, et al. Indications, complications, and revisions of amputations in Turkey. Ege Tıp Dergisi 2020; 59: 251–257.

53.

Johannesson

Larsson

Ramstrand

, et al. Incidence of lower-limb amputation in the diabetic and nondiabetic general population: a 10-year population-based cohort study of initial unilateral and contralateral amputations and reamputations. Diabetes Care 2009; 32: 275–280.

54.

Yaghi

McDonald

, et al. Diabetes or war? Incidence of and indications for limb amputation in Lebanon, 2007. East Mediterr Health J 2012; 18: 1178–11186.

55.

Ceyhan

Erkılıç

Demirtola

, et al. Preoperative risk factors for improved outcome in major limb amputations: in the perspective of anesthesiologists. Global J Anesthesiol 2020; 7: 001–0014.

56.

Belmont

Jr Davey

Orr

, et al. Risk factors for 30-day postoperative complications and mortality after below-knee amputation: a study of 2,911 patients from the national surgical quality improvement program. J Am Coll Surg 2011; 213: 370–378.

57.

Zhu

Goh

Chew

, et al. Struggling for normality: experiences of patients with diabetic lower extremity amputations and post-amputation wounds in primary care. Prim Health Care Res Dev 2020; 21: 1–10.

58.

Essien

Zucker-Levin

. Factors associated with prolonged post-operative acute care length of stay in limb amputation patients in Saskatchewan, Canada. BMC Health Serv Res 2021; 21: 1–9.

Comorbidity and risk factors of subsequent lower extremity amputation in patients diagnosed with diabetes in Saskatchewan,Canada

Abstract

Objective

Methods

Results

Discussion

Keywords

Introduction

Methods

Statistical analysis

Results

Discussion

Strengths and limitations

Conclusion

Footnotes

Disclaimer

Acknowledgements

Contributorship

Declaration of conflicting interests

Funding

Ethical approval

Informed Consent

Guarantor

ORCID iD

Appendix 1

References