Decoding success: A five-year retrospective study of dental Implant survival

Abstract

Background

Dental implants are the preferred option for replacing missing teeth, offering aesthetic and functional benefits. However, factors such as systemic health, smoking, and prosthetic design can influence implant survival. This study aimed to evaluate the impact of clinical, systemic, and prosthetic factors on the survival of dental implants over five years.

Materials and methods

This retrospective cohort study included 143 patients who received 161 dental implants between 2016 and 2018, each followed for a minimum of five years. Clinical parameters, systemic conditions and prosthetic factors were evaluated. Radiographic analysis was performed to measure crestal bone loss. Statistical analysis, including multiple regression, was conducted to assess the factors influencing implant survival.

Results

The overall implant survival rate was 92.5 %. Factors significantly associated with implant survival included gender (female patients had a higher survival rate, p = 0.01), smoking status (non-smokers had a higher survival rate, p = 0.04), and the absence of parafunctional habits (p = 0.02). Systemic conditions such as diabetes and vitamin D deficiency were also associated with less implant survival rate (p < 0.05). Implant-related parameters, including less crestal bone loss and implant placement protocol type IV (delayed placement) demonstrated statistically significant association with high implant survival. Multiple regression analysis confirmed that females and patients without systemic conditions were significantly more likely to experience implant success.

Conclusion

Age, systemic health conditions, smoking status, and prosthetic design significantly influence implant survival. A comprehensive evaluation of these factors is crucial for improving clinical outcomes and optimizing implant success rates.

1. Introduction

Dental implants have revolutionized modern dentistry, offering a durable and effective solution for replacing missing teeth. According to the World Health Organization Global Oral Health Status Report (2022), the global average prevalence of complete tooth loss among adults aged 20 years and older is over 7 %. A considerably higher global prevalence of 23 % has been noted in individuals aged 60 years and older.¹

The success rate of dental implants as a therapy option for the restoration of missing teeth has increased over time. Nevertheless, early implant failure still occurs, and it usually happens when the implant fails to osseointegrate during the initial healing phase following implantation.² Conversely, peri-implant diseases, improper prosthetic designs, and unfavorable loading or occlusion are linked to late implant failure. In the realm of dental implantology, the survival and success of implants are influenced by a complex interplay of clinical, systemic, and prosthetic factors.³

Additionally, the surgical technique employed, including flap design, drilling protocol, and aseptic measures, significantly impacts osseointegration, the process where the implant integrates with the bone.⁴

Besides this, systemic factors also encompass the patient's overall health status. Chronic diseases such as diabetes, osteoporosis, and cardiovascular conditions can compromise the body's healing capabilities and bone metabolism, thereby affecting the osseointegration process.⁵ Moreover, lifestyle factors like smoking, alcohol consumption, and poor nutritional status further exacerbate the risk of implant complications. Therefore, a comprehensive evaluation of the patient's medical history is crucial before proceeding with implant placement.⁶

Prosthetic factors pertain to the design and material of the prosthesis, as well as its functional alignment. The type of abutment used, the choice of material (e.g., titanium or zirconia), and the design of the crown or fixed dental prosthesis all contribute to the mechanical stability of the implant. Proper occlusal alignment is critical; excessive or uneven occlusal forces can lead to micromovements of the implant, resulting in bone loss or implant fracture. Moreover, the prosthetic design should also facilitate easy cleaning and maintenance to reduce the risk of peri-implant diseases.⁷

Understanding the factors affecting implant survival is key for optimizing long-term success. While dental implants typically have a high success rate, complications and failures remain challenges. Identifying and addressing risk factors early can enhance clinical decision-making and improve implant survival rates.

Numerous research has reported on the criteria used to assess the success and survival of dental implants.^3,8 Albrektsson et al. defined a successful implant as one with no mobility, no peri-implant radiolucency, bone loss of less than 0.2 mm per year after the first year of loading, and no persistent pain, discomfort, or infection.⁸ According to a systematic review and meta-analysis by Morachini et al. the mean survival rate was 94.6 % with a 13.4-year mean follow-up period.³ Currently, there is still a dearth of efficient therapeutic strategies for addressing biological complications like peri-implantitis, despite the fact that the majority of mechanical and prosthetic difficulties can be reversed by replacing restorative counterparts.

Although previous studies have addressed the impact of various risk factors on the survival rate of the implant, this study uniquely examines their combined impact on both clinical and prosthetic outcomes in a retrospective cohort, providing data on long-term survival rates.⁹

The purpose of this five-year retrospective study was to evaluate the clinical and radiological outcomes, along with systemic and prosthesis-related factors influencing the survival rate of dental implants. The study analyzed implant cases placed between 2016 and 2018, each followed for a minimum of five years, with follow-up data collected through 2021 to 2023.

2. Materials and methods

This retrospective cohort study was conducted through a review of patient medical records and radiographs. The study was carried out following STROBE cohort reporting guidelines.¹⁰ The study protocol was approved from institutional ethical committee MADC/IEC/III/79/2023.

INCLUSION & EXCLUSION CRITERIA: Patients aged between 18 and 62 years, who have undergone implant surgery using A,B,C,D,E and F implant system and followed up for at least 5 years. Patients with complete clinical and radiographic records at each follow-up visit were included. Patients with incomplete clinical and radiographic records exceeding 50 % of required follow-up data and suffering from any other diseases such as HIV, AIDS, Hepatitis B or Tuberculosis were excluded from the study.

The initial selection of implant cases were pooled from the medical records room of the Dental College between 2013 and 2018 to get maximum number of participants. However, the patients enrolled between 2013 and 2015 could not be taken in the study as they failed to meet the eligibility criteria. Hence the final selection of the participants was 165 with 197 implants from the period of 2016–2018 who were eligible for the study. From the selected participants, telephonic conversation was made to determine their willingness in participation of the study. Twenty two patients who did not answer calls on five distinct occasions were deemed unreachable and were excluded from the study. Finally, the study population comprised 143 patients of both genders who received 161 dental implants. Follow-up was performed in 2021 for implants placed in 2016, in 2022 for those placed in 2017, and in 2023 for those placed in 2018, ensuring a five-year follow-up for all included implants. Informed written consent was obtained from all participants before their inclusion in the study. (Fig. 1).

Fig. 1.

Study design.

Three qualified dentists (P.G, U.S, J.M) conducted the clinical examination. The first fifteen subjects were examined jointly by all three examiners to assess inter-examiner variability. Intra-examiner standardization for periodontal probing was performed before the study began. An experienced clinician (J.M) also conducted a training session on data collection, including a practice exercise using a predetermined collection form from an actual patient file. To ensure stable and consistent results, intra-examiner reliability tests were conducted by selecting five files from a pool of retrieved patient files. Data were collected by the investigator (P.G.) three weeks apart and cross-checked by an experienced clinician (U.S).

The selected patients' age, gender, and history of smoking habit were gathered from medical records. (Those who had smoked 100 or more cigarettes in their lifetime and currently smoked were categorized as smokers, while those who had smoked fewer than 100 cigarettes in their lifetime and did not currently smoke were categorized as non-smokers according to CDC classification)¹¹ and parafunctional habits were self-reported which included bruxism and clenching documented in patient history records were collected. Past dental and medical history of the patient was retrieved from previous patients’ records. Patients with Type-II diabetes, hypertension and self-reported Vitamin D deficiency from the past medical records were included in the study. Apart from this any history of periodontitis from previous records was taken into consideration according to 2017 World Workshop on the Classification of Periodontal and Peri-implant Diseases.¹²The current periodontal status was assessed through clinical examination. Full-mouth bleeding on probing scores and periodontal pocket depth were recorded.¹³ Implants were assessed for stability, discomfort during function, and the presence of exudate or suppuration. Data pertaining to implant including number, location, type of restoration placed, implant system, implant dimensions (diameter/length), implant stability using Resonance Frequency Analysis (RFA), implant placement protocol were recorded.

Prostheses were carefully assessed for technical issues, such as crown debonding, retention loss, screw loosening, abutment failure, implant or screw fractures, and restoration loss. Additionally, details regarding occlusal and proximal contacts, opposing dentition, and crown design were meticulously documented.

Peri-implant bone levels were assessed using radiographs with the paralleling technique and appropriate aiming devices (XCP®, Rinn Corporation, Elgin, IL, USA). In most cases, vertical bitewing radiographs were utilized for posterior implants, while periapical radiographs were preferred for anterior implants. The radiographic analysis was performed using Adobe™ Photoshop 2014.2.2. Images were adjusted using the arbitrary rotation tool to align the implant's long axis vertically, ensuring accurate measurements with the millimeter ruler scale on the x- and y-axes (precision up to 0.1 mm). A magnification factor of 97 was determined using the known implant diameter as a reference point for calibration in Adobe Photoshop. The known implant diameter was used to determine the radiographic magnification, which was then factored into the measured bone loss to calculate the actual bone loss in millimeters.¹⁴

Implants were classified as surviving if they were still in-situ at the time of examination and supporting a functional prosthesis during the entire observation time, while failures were those that had been removed or required removal at the time of examination. Peri-implant mucositis was defined as an osseointegrated functional implant that demonstrated bleeding and/or suppuration on probing, absence of increasing probing depths, and bone loss beyond initial remodeling of crestal bone levels.¹⁵ Peri-implantitis was defined as an osseointegrated functional implant that demonstrated bleeding and/or suppuration on probing, increased probing depths and bone loss beyond initial remodeling of crestal bone levels or > 2 mm in the absence of baseline clinical parameters (2017 World Workshop on the Classification of Periodontal and Peri-implant Diseases).¹²

All data were entered into Microsoft Excel and analyzed using Statistical Package for Social Sciences (version 26, IBM, Chicago, USA). Continuous variables were expressed as mean ± standard deviation (SD). Categorical variables were expressed as n and %. The normal distribution of the data was checked using Shapiro Wilk test. As data followed normal distribution, parametric test of significance was used. The level of significance was set at 5 %. Chi-square test was used to assess the association of all categorical variables with survival of implants. Independent sample t-test was used to compare the continuous variables between participants with implant survival and without implant survival.

3. Results

Among the initial 165 subjects, a total of 197 implants were placed. After excluding 22 patients who were unreachable, the final sample comprised 143 patients with 161 implants, resulting in a five-year survival rate of 92.5 %. (Table 1).

Table 1.

No. of implants survived and failed.

	n (%)
Total	161 (100)
Implants survived	149 (92.54)
Failed implants	12 (7.45)

The implant survival rate was higher in the 30–45 age group compared to those aged 18–30 and over 45, though differences were not statistically significant (p = 0.89). Females had a significantly higher survival rate than males (p = 0.01). Non-smokers had a 98.6 % survival rate, with a significantly higher survival rate than smokers (p = 0.04). Patients without parafunctional habits also showed a higher survival rate compared to those with such habits, with statistically significant results (p = 0.02) (Table 2).

Table 2.

Association of survival of implants with socio-demographic details, systemic factors and previous history of periodontitis of study population.

		Survival of implants		Total	p-value
		Yes n (%)	No n (%)
Sociodemographic details
Age (years)	18–30 years	39 (26.17)	4 (33.3)	43 (26.7)	0.89
	30–45 years	75 (50.3)	5 (41.6)	80 (49.6)
	45–62 years	35 (23.4)	3 (25)	38 (23.6)
Gender (M/F)	Female	72 (98.6)	1 (1.4)	73 (45.3)	0.01∗
	Male	77 (87.5)	11 (12.5)	88 (54.7)
Smoking	Absent	147 (98.6)	12 (100)	159 (98.7)	0.04∗
	Present	2 (1.4)	0 (0)	2 (1.3)
Parafunctional habits	Absent	152 (94.4)	1 (0.6)	153 (95)	0.02∗
	Present	8 (5)	0 (0)	8 (5)
Systemic factors
Diabetes	Absent	145 (97.3)	12 (100)	157 (97.5)	0.03∗
	Present	4 (2.7)	0 (0)	4 (2.5)
Hypertension	Absent	144 (96.6)	12 (100)	156 (96.9)	0.02∗
	Present	5 (3.4)	0 (0)	5 (3.1)
Vitamin D Deficiency levels	Absent	140 (93.9)	11 (91.6)	151 (97.3)	570.57
	Present	9 (6.1)	1 (8.4)	10 (6.3)
Previous history of Periodontitis	Absent	124 (96.6)	12 (100)	126 (96.9)	0.04
	Present	25 (3.4)	0 (0)	25 (3.1)

-Chi square test ∗p-value<0.05 – statistically significant.

Systemic conditions like diabetes, hypertension, and a previous history of periodontitis were significantly associated with implant survival, with patients without these conditions showing higher survival rates. However, Vitamin D deficiency did not show a significant association with implant survival (Table 2).

The mean and standard deviation of bleeding on probing and periodontal probing depth (mm) for implant survival were statistically significant (p < 0.05). The mean bleeding on probing was 56.62 ± 27, which was lower in implants that survived compared to those that did not. Similarly, the periodontal probing depth was less in survived implants, with a mean of 1.49 ± 0.98 mm (Table 3).

Table 3.

Association of clinical parameters with survival of implants.

Clinical parameters		Survival of implants		p-value
		Yes (Mean ± S.D) or n (%)	No (Mean ± S.D) or n (%)
Bleeding on probing (Percentage)		56.62 ± 27	69.83 ± 22.02	0.01∗
PPD (mm)		1.49 ± 0.98	2.40 ± 0.96	0.01∗
Crestal bone loss	Absence	121 (81.2)	11 (91.7)	0.69
	Presence	28 (18.8)	1 (8.3)

Independent sample t-test; ∗p-value< 0.05 – statistically significant.

The current study found that 5 % of crestal bone loss was less than 1 mm, 20 % ranged from 1 to 2 mm, 6.6 % fell between 2 and 3 mm, and 7.5 % exceeded 2.5 mm (Fig. S1). The mean ridge width (6.08 ± 0.62), ridge length (14.11 ± 1.23), and ridge height (13.69 ± 2.23) had a significant impact on implant survival, with statistically significant findings (p < 0.05). Surviving implants had a mean diameter of 4.02 ± 0.53 %, length of 10.68 ± 2.19 %, and stability of 1.12 ± 0.58 %. Type IV implants showed a better survival rate compared to other types, and these differences were statistically significant (p < 0.05) (Table 4).

Table 4.

Association of radiological and implant related parameters with survival of implants.

Radiological and implant related parameters		Survival of implants		p-value
		Yes (Mean ± S.D) or n (%)	No (Mean ± S.D) or n (%)
Ridge width (mm)		6.08 ± 0.62	3.10 ± 0.41	0.01∗
Ridge length (mm)		14.11 ± 1.23	9.25 ± 0.72	0.05
Ridge height (mm)		13.69 ± 2.23	16.34 ± 1.76	0.01∗
Implant diameter		4.02 ± 0.53	4.21 ± 0.48	0.26
Implant length		10.68 ± 2.19	13.32 ± 1.33	0.02∗
Implant stability		1.12 ± 0.58	3.12 ± 0.16	0.01∗
Implant placement protocol	Type 1	25 (15.5)	4 (2.5)	0.05
	Type 2	0 (0)	0 (0)
	Type 3	5 (3.1)	3 (1.9)
	Type 4	119 (73.9)	5 (3.1)

- Independent sample t-test and chi-square test ∗p-value<0.05 – statistically significant.

Patients with single implant placements had a higher survival rate compared to those with two or three implants. Implants placed in posterior regions showed a higher survival rate than those in anterior regions. Cement-retained implants had the highest survival rate compared to screw-retained implants, though this difference was not statistically significant (p = 0.03). Among implant brands, D implants had the highest survival rate, followed by A,F,B,E and C but these differences were not statistically significant (p < 0.05) (Table 5).

Table 5.

Association of number of implants, location of implant and implant system with survival of implants.

		Survival of implants		Total	p-value
		Yes n (%)	No n (%)
Number of implants	1	135 (90.6)	11 (91.6)	146 (90.6)	0.05(NS)
	2	1 (0.6)	1 (8.4)	2 (1.2)
	3	13 (8.7)	0 (0)	13 (8.2)
Location of implant	Anterior	25 (16.7)	2 (16.7)	27 (19.1)	0.03∗
	Posterior	124 (83.3)	10 (83.3)	134 (80.9)
Retention	Screw retained	52 (32.3)	3 (1.8)	55 (34.1)	0.03∗
	Cement retained	102 (63.4)	4 (2.5)	106 (65.9)
Implant system	A	38 (23.6)	9 (5.6)	47 (29.2)	0.04∗
	B	6 (3.7)	0 (0)	6 (3.7)
	C	1 (0.6)	0 (0)	1 (0.6)
	D	91 (56.5)	3 (1.9)	94 (58.4)
	E	2 (1.3)	0 (0)	2 (1.3)
	F	11 (6.8)	0 (0)	11 (6.8)

Chi square test ∗p-value<0.05 – statistically significant.

Dental implant systems used in this study include: A- Adin Dental Implant Systems Ltd., Afula, Israel, B-Dentin Implants Technologies Ltd., Israel, C-Osstem Implant Co., Ltd., Seoul, South Korea, D-Neodent (Straumann Group), Curitiba, Brazil E-Bioline Dental Implants, Germany, F-DIO Implant Co., Ltd., Busan, South Korea.

Contributing factors to implant failure included: 5 % of implant failure due to loss of retention, crown debonding and peri-implantitis; 4.3 %implants failed due to screw fracture and peri-implant mucositis; 3.7 % implant loss was due to loss of restoration, abutment failure, and screw loosening; and 3.1 % due to implant fracture (Fig. S2).

Multiple regression analysis was performed to assess risk factors associated with implant failures. It was found that the odds of implant success in females were significantly higher, with an odds ratio of 11.27 (95 % CI: 1.39–91.17), suggesting that females are over 11 times more likely to experience implant success compared to males, and the association was statistically significant (p = 0.02). The odds ratio for smokers was 1.67 (95 % CI: 1.67–1.68), indicating smokers were approximately 67 % more likely to experience implant failure compared to non-smokers (OR = 1.0), but this was not statistically significant. The odds ratio for implants placed in the posterior region was 1.08 (95 % CI: 0.75–3.19), suggesting a better survival rate, though not statistically significant compared to the anterior region. The odds of implant failure in patients with systemic risks like diabetes and hypertension were 1.47 (95 % CI: 1.18–1.45), indicating a higher risk of implant failure, and this association was statistically significant. (Table 6).

Table 6.

Multiple Logistic regression analysis for risk factors associated with implant survival.

		Odds ratio	95 % Confidence Interval	p-value
Gender	Male (Reference)	1.0		0.02∗
	Female	11.27	1.39–91.17
Smoking	Yes (Reference)	1.0		1.0
	No	1.67	1.67–1.68
Location	Anterior (Reference)	1.0		0.77
	Posterior	1.08	0.75–3.19
Systemic risk such as diabetes and hypertension	Absence (Reference)	1.0		0.01∗
	Presence	1.47	1.18–1.45
Previous history of periodontitis	Absence (Reference)	1.0		0.77
	Presence	1.51	0.18–12.14

∗p-value<0.05-statistically significant.

4. Discussion

The present study aimed to evaluate the clinical, systemic, radiological, and prosthesis-related factors influencing implant survival over five years. The results revealed that out of 161 implants placed, 149 survived (92.54 %) during the follow-up period, while 12 implants (7.45 %) failed (Table 1).

The study demonstrated a higher implant survival rate in middle-aged individuals compared to the elderly. Female patients had an odds ratio (OR) of 11.27 (95 % CI: 1.39–91.17, p = 0.02), suggesting that gender and age-related factors, healing responses, and oral hygiene practices, may have influenced implant success (Table 2). These findings align with a retrospective analysis of 5200 patients by Raiker et al., which showed higher implant failure rates in individuals over 60 years of age (55 failures out of 1250 implants) compared to middle-aged patients (20 failures out of 1300 implants) and also found that implant failures were more prevalent among males.¹⁶

Similarly, Chatzopoulos GS et al., identified a significantly higher likelihood of implant failure in males, consistent with the present study.¹⁷ Olmeda Gaya MV also found a 1.255-fold increase in failure rates among males.¹⁸ However, studies by Bornstein et al., Alsaadi et al., and Van Steenberghe et al., did not report significant gender differences in implant survival rates.19, 20, 21 The reasons for these discrepancies are multifactorial, and the findings regarding gender differences in implant survival remain inconclusive.

The present study also revealed a significant association between smoking and implant survival, with an odds ratio of 1.67 (95 % CI: 1.67–1.68) (Table 2). This finding aligns with a study by Cavalcanti R et al., which showed higher failure rates in smokers (5.5 %) compared to non-smokers (2.9 %), with an odds ratio (OR) of 1.72.²² Similarly, recent systematic review by Mustapha AD et al., found higher implant survival in non-smokers (140 %) compared to smokers.²³ However, given that only two subjects in this study were smokers, statistical conclusions regarding smoking's effect on implant survival should be interpreted with caution.

Smoking increases pro-inflammatory cytokine expression, leading to enhanced tissue damage and alveolar bone resorption. Nicotine further disrupts cellular protein synthesis and impairs gingival fibroblast adhesion, compromising wound healing and worsening periodontal disease. To improve implant survival in smokers, several protocols are recommended. Bain et al., suggested that patients should stop smoking at least one week before surgery to reverse the increased platelet adhesion and blood viscosity levels caused by nicotine. Additionally, refraining from smoking during the early osseointegration phase enhances bone healing.²⁴ Similarly, Lambert et al., noted that implant survival rates were higher in non-smokers and recommended smoking cessation, pre-operative antibiotics, and hydroxyapatite-coated implants to reduce the detrimental effects of smoking on implant success.²⁵

In this study, of the 161 dental implants reviewed, a higher survival rate of 95 % was observed in both patients with and without parafunctional habits, suggesting that parafunctional habits may not significantly affect implant survival. This aligns with findings from Herzberg et al., who studied implant marginal bone loss in maxillary sinus graft cases involving 70 patients and 212 implants. They reported a negative link between bruxism and implant failure in only 15 individuals with bruxism.²⁶ Similarly, Nedir et al., examined 236 individuals with 528 implants and found only two failures (13.6 %) in patients with bruxism.²⁷

Although parafunctional habits like bruxism are typically thought to affect implant survival, our study found no failures among patients exhibiting these habits. This may indicate that, with proper case selection, implant placement techniques, and post-operative care, the negative impact of parafunctional habits on implant survival can be minimized. Additionally, factors like the type of occlusal forces, load distribution, and bone integration quality may contribute to maintaining implant stability even in the presence of bruxism. Hence, while parafunctional habits are considered risk factors, their effect on implant survival may be less significant when these factors are carefully managed.

The present study found that systemic conditions such as diabetes and hypertension significantly impacted implant survival, with an odds ratio of 1.47 (95 % CI: 1.18–1.45) (Table 2). A systematic review by Sbricoli L et al., and Jiang X et al., observed mixed results with some studies showing no link between these conditions and implant failure, while others reported a 33 % increase in failure risk for diabetes and a 14 % increase for hypertension.^28,29 These findings emphasize how systemic health can affect implant stability by impairing healing and bone metabolism.

Contrary to expectations, the study did not find a significant difference in implant survival between patients with or without Vitamin D deficiency (Table 2). While vitamin D's role in bone healing and implant success is widely discussed, our findings suggest that it may not be a primary determinant. Fretwurst et al., reported successful osseointegration even in patients with prior implant failures due to vitamin D deficiency, highlighting the importance of considering multiple factors in implant outcomes.³⁰ Though various studies underscore the role of vitamin D in calcium homeostasis and bone formation, which are critical for implant osseointegration, Mangano F et al., found mixed results regarding the direct impact of vitamin D deficiency on implant failure.³¹ These insights underscore the complexity of factors influencing implant osseointegration, indicating that while vitamin D may contribute to the process, it should be considered alongside other critical determinants. Furthermore, maintaining adequate vitamin D levels could still serve as a beneficial preventive measure, particularly for individuals with compromised bone metabolism.

Additionally, the study showed a 96.9 % implant survival rate in patients without a history of periodontitis, consistent with Bornstein MM et al., findings.¹⁹ They attributed implant failures to factors like smoking and bone quality rather than periodontal history. Interestingly, 3.4 % implant survival was observed in patients with a history of periodontitis, with no implant failures. This is aligned with the conclusion by Renvert S et al., that implant survival rates in periodontitis patients are similar to non-periodontitis patients, provided they maintain regular follow-up care.³²

These findings underline the importance of ongoing periodontal care and patient compliance in preventing implant failure. For patients with periodontitis, combining professional therapy and diligent oral hygiene is essential to maintaining implant health and minimizing complications.

In this study, clinical parameters such as less bleeding on probing (BOP) and reduced probing pocket depth (PPD) were significantly associated with higher implant survival rates (Table 3). These findings are consistent with a systematic review by Hashim et al., which found a 24 % peri-implantitis rate in cases with BOP.³³ Similarly, Winitsky et al., reported that implants with BOP remained stable for 14 to 20 years, aligning with the current study's results.³⁴ The strong association between reduced BOP and PPD emphasizes the importance of early intervention in maintaining mucosal health to improve implant longevity and success.

Additionally, the study revealed that larger implant diameters, lengths, greater implant stability, and favorable ridge dimensions were linked to higher survival rates (Table 4). This supports the findings of Goiato MC et al., who showed that implants with narrower diameters (3.25 mm) are more prone to mechanical failure due to compromised fatigue.³⁵ Winkler et al., also found that longer implants (16 mm) had a higher survival rate compared to shorter ones (7 mm), which aligns with the study's observations.³⁶ However, Esposito et al., noted that failures were more common in implants between 10 mm and 11.5 mm in length.³⁷ Borie et al., highlighted that the length, diameter, and connection of implants influence bone biomechanics. However, they emphasized that peri-implant bone stress and strain must remain within physiological limits to prevent pathological overload, bone resorption, and potential risks to long-term implant success.³⁸ Similarly, Misch in his study found that implants shorter than 10 mm had lower success rates (7 %–25 %) compared to those longer than 10 mm.³⁹ The study's results also highlighted that patient with successful implants had a mean ridge width of 6.08 ± 0.62 mm and a mean ridge length of 14.11 ± 1.23 mm (Table 4). This is the first study to correlate ridge width and length with implant survival. Wider bone dimensions seem to enhance implant stability, providing better support for osseointegration and primary stability, which are crucial for long-term success. Similarly, longer ridge lengths allow for optimal implant placement, increasing surface area for osseointegration. These findings emphasize the significance of adequate bone dimensions and the clinician's expertise in ensuring the success of dental implants.

The present study revealed a higher survival rate for implants placed under the Type IV protocol (delayed placement) compared to the Type I protocol (immediate placement) (Table 4). This aligns with the systematic review by Esposito et al., which showed that delayed implant placement significantly reduces the risk of peri-implantitis and implant failure, with survival rates ranging from 95 % to 97 %.⁴⁰ Although Type I implants had slightly lower survival rates, as reported by Lang et al., (93 % for immediate vs. 97.5 % for delayed), they still demonstrated reliable outcomes when placed appropriately.⁴¹ Studies by Aiquel LL et al., and Patel R et al., found no significant difference in survival rates between immediate and delayed placements, highlighting that with proper case selection, both protocols can achieve predictable outcomes.^42,43

The highest survival rate in this study was observed in single implant placements (Table 5), which was consistent with studies by Soegiantho P et al., and Zembic A et al., who found a higher success rate in single implants compared to multiple implants.^44,45 The reduced stress, better load distribution, and less trauma to the surgical site are factors contributing to the success of single implants. The study also noted a survival rate of 83.3 % for implants placed in the posterior region, with a slightly higher survival rate compared to implants placed in the anterior region (16.7 %). This is likely due to superior bone quality in the posterior region, as corroborated by studies by Yang Y et al., and de Araújo Nobre M et al.,^46,47

Additionally, the study showed that cement-retained implants had a higher survival rate (63.4 %) compared to screw-retained implants (Table 5), which is consistent with findings from Lemos CA et al., and Hamed et al., who found cement-retained implants to exhibit fewer complications such as screw loosening and better stress distribution.^48,49 The absence of visible screws also enhances aesthetics and helps prevent biological issues like peri-implantitis. The study further indicated that D implant system had the highest survival rates compared to other implant systems, possibly due to their Morse taper connections, which improve mechanical strength, reduce bone remodeling, and promote favorable peri-implant bone maintenance.

The present study found that 65 % of crestal bone loss was below 1 mm (Fig. S2), aligning with Tey VH et al.'s study, which reported 52 % of bone loss under 1 mm.⁵⁰ This minimal bone loss is clinically significant, as a loss of less than 1 mm is generally considered acceptable and does not significantly impact implant longevity. Proper initial implant stability and bone quality can mitigate minor bone loss, allowing continued osseointegration. However, close monitoring is necessary to prevent complications such as peri-implantitis, which could lead to more severe bone loss over time. This aligned with Lu B et al., findings which emphasized the importance of peri-implantitis prevention in implant success.⁵¹

This study provides valuable insights into the factors influencing dental implant survival. By identifying key associations with demographic, systemic, and clinical parameters, such as gender, smoking, and systemic health, the findings contribute to a deeper understanding of implant outcomes. Furthermore, the study highlights the importance of prosthetic factors like retention type and material selection, underlining the need for tailored prosthetic design. Overall, these findings stress the significance of individualized patient management and pave the way for future research aimed at improving implant success rates.

The study also has several limitations that warrant acknowledgment. Firstly, its retrospective design limits the ability to establish causality. The 15.5 % refusal rate for participation raises the possibility of selection bias. As a single-institution study, the influence of operator bias cannot be excluded, as treatment planning and surgical technique may have varied between clinicians despite standard protocols. While early implant failures are well-documented, the detection of late failures and long-term complications requires extended follow-up beyond the current study period. Additionally, habits such as bruxism and clenching were self-reported and thus prone to recall bias; future studies should utilize objective diagnostic tools for greater accuracy. Other relevant factors that were not assessed in this study include bone quality or density at the implant site, glycemic control in diabetic patients, medication history and peri-implant soft tissue characteristics such as the width of keratinized mucosa. These unaddressed variables may also influence implant survival and should be considered in future prospective studies to enhance clinical predictability and generalizability.

5. Conclusion

This study highlights that while various factors influence the success of dental implants, a high survival rate was achieved across the observed cases. Nonetheless, the presence of both technical and biological complications underscores the need for ongoing vigilance in implant management. Future research on dental implant survival should emphasize prospective study designs to establish clearer causal relationships in a larger population with more diverse samples for enhancing the generalizability of findings.

Authors' contributions

Conceptualization: [Dr. Jaideep Mahendra].

Methodology: [Dr. Jaideep Mahendra (lead) and Dr. Sathish Rajendran (supporting)]

Investigation: [Dr. Uma Subbiah, Dr. Pavithra GopalaKrishnan, Dr. Saranya Mohan].

Data Curation: [Dr. Karunanidhi K (lead),Dr. Saranya Mohan. (supporting)]

Writing – Original Draft Preparation: [Dr. Uma Subbiah, Dr. Pavithra GopalaKrishnan].

Writing – Review & Editing: [Dr. Jaideep Mahendra].

Supervision: [Dr. Jaideep Mahendra (lead) and Dr. Sathish Rajendran (supporting)]

Project Administration: [Dr. Jaideep Mahendra].

Consent

PATIENT’S/GUARDIAN CONSENT FORM: The study protocol was approved from institutional ethical committee MADC/IEC/III/79/2023. Informed consent was obtained from all subjects involved in the study.

Funding statement

Source(s) of financial support: This research received no external funding.

Declaration of competing interest

The authors declare no conflicts of interest related to this study. All materials and equipment used in this research were procured independently, and no financial support or sponsorship was received from any organization or entity that could influence the outcome of the research. The study was conducted solely for academic and scientific purposes, aiming to contribute to precision in implant therapy.

Appendix A. Supplementary data

The following is the Supplementary data to this article: