Abstract
Background
Loop electrosurgical excision is a procedure utilised in the treatment of high‐grade squamous intraepithelial lesion (HSIL) of the cervix. Post‐operatively women may experience immediate and/or delayed per vaginal bleeding.
Aims
The objective of this prospective pilot study was to assess the feasibility of identifying and quantifying patients' subjective experiences of post‐operative bleeding following a loop electrosurgical excision procedure (LEEP) for HSIL. In addition, an analysis of demographical, lifestyle and surgical factors was undertaken to assess for any statistically significant correlation with post‐operative bleeding.
Materials and Methods
This study included 110 patients who underwent a LEEP for biopsy‐proven or suspected HSIL between 2017 and 2020. Subjective data were collected from weekly post‐operative surveys and correlated with procedural data. Primary outcome assessed was the subjective rate of bleeding experienced. Baseline demographics were age, body mass index (BMI), specimen size, human papilloma virus variant and histopathology. Other variables of interest collected were exercise intensity, and alcohol intake.
Results
No association of statistical significance was discovered between age, BMI, or day of menstrual cycle. There was a statistically significant association between exercise intensity or specimen size (greater than the median) and increased bleeding, primarily in the first 2 weeks.
Conclusions
Women who undergo intense or prolonged exercise in the post‐operative period may experience heavier bleeding particularly in the first 2 weeks post‐LEEP. Heavy bleeding was also associated with a larger specimen size. There was no correlation between BMI, age or any other demographical factor.
Keywords: LEEP, CIN, HSIL, cervix, bleeding, cervical dysplasia, LLETZ
INTRODUCTION
Cervical dysplasia (squamous intraepithelial lesion/SIL), is a condition characterised by abnormal epithelial cell growth and division of the squamous cells in the endocervical canal and on the surface of the cervix itself. 1 This abnormal growth can be caused by several factors and is strongly association with human papilloma virus (HPV) infection, of which there are over 200 different strains/variants. 2 Certain strains of HPV increase the likelihood that abnormal dysplasia of cervical cells will progress to a high‐grade squamous intraepithelial lesion (HSIL), as well as decrease the time taken for dysplastic change to progress. 3 , 4 , 5 In chronic HPV infections, smoking has also been strongly associated with progression to HSIL. 6 Other associated risk factors include early initiation of sexual activity, multiple sexual partners, immunosuppression, and infection with human immunodeficiency virus. 2 , 5
Loop electrosurgical excision procedure (LEEP) is a procedure utilised to treat HSIL by removing the section of the cervix which contains dysplastic cells with a small wire loop heated with electrical current. 2 Current literature suggest that a varied number of patients experience heavy per vaginal bleeding in the post‐operative period which can significantly impact their recovery and in certain cases require readmission to hospital and further treatment. 7 , 8 In Australia LEEP is generally performed where either HSIL has been proven on biopsy or there is discordance between a Pap smear cytology and biopsy, raising a strong suspicion of HSIL. In some instances where the LEEP has been performed for a high‐grade lesion, the final pathology shows a low‐grade lesion or no residual dysplasia.
The literature on the incidence of post‐operative bleeding is limited, as most studies currently published have looked at the incidence of recurrence of HSIL as the most important post‐operative complication. Of the remaining papers, there is a wide range of post‐operative bleeding reported in the literature, varying between 2% to 78%. 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 Of note in the studies found was a meta‐review of n = 857, conducted in Thailand, which found a reported post‐operative bleeding rate of 5.5%. 7
The largest single study found involved n = 929 in 2009 which looked at the after‐effects of both colposcopy and LEEP over post‐operative six weeks. 8 This study found reported rates for post‐operative bleeding of 87%, but did not differentiate between light or heavy bleeding. 8 A study by Paraskevaidis et al. 14 focused on post‐operative bleeding and correlation with menstrual cycle and found that women who underwent LEEP during the luteal phase of their menstrual cycle experienced more post‐operative bleeding than women treated during the follicular phase. No other studies appear to focus on any potential lifestyle or demographic cause for this post‐operative bleeding. 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 The most recent of the studies identified was a quality improvement study in Perth, Australia (n = 75) which reported 36% of women experienced post‐operative bleeding in the first week, which then decreased to 10.7% by post‐operative four weeks. 20
It is therefore clear that there is limited research which focuses solely on post‐operative bleeding in this area of gynaecological surgery, with rates varying widely in their findings (5.4% to 87% respectively). In addition, there is a paucity of Australian research into this area. 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18
MATERIALS AND METHODS
This prospective pilot study was registered and approved by Royal Prince Alfred (RPA) Human Research Ethics Committee (HREC) (X17‐0172 & HREC/17/RPAH).
Data was collected by recruiting patients who presented to the Chris O'Brien Lifehouse Colposcopy Clinic for treatment of HSIL. Inclusion criteria included women aged 18–80, with a biopsy‐proven or suspected (from high‐grade cytology) diagnosis of HSIL requiring LEEP and with a willingness to give online consent and participate in a series of short surveys. Exclusion criteria include women lactating, pregnant or of childbearing potential who were not willing to avoid becoming pregnant during the study. Unfortunately, women who were unable to access email communication, or communicate and understand the English language were also excluded from this study as we did not have the funding and ability to offer alternative options.
The weekly emailed surveys began at post‐operative 7 days. The surveys were identical except for the first one which included questions of height, weight, and menstrual period cycles. All four surveys collect data on bleeding rates, days of bleeding experienced, contraceptive use, and lifestyle factors including smoking, exercise and alcohol intake. Data were also collected from the electronic medical record, including pathology specimen dimensions, HPV status, histopathology results and the age of the participant as these were not captured in the survey.
As this was a novel study, for which similar data are limited in the literature, a formal power calculation was not feasible. It was estimated that to detect a 30% reduction in the proportion of patients exhibiting a lifestyle factor such as exercise or drinking alcohol (eg from 60% to 30%), a total sample size of 120 would be required assuming a 1:4 ratio of excessive bleeding. Thus, it was anticipated that a sample size of 100–120 patients would be appropriate.
Participants were defined as having heavy bleeding if they had both moderate or heavy bleeding (plus or minus clots) with >3 days bleeding per week†. The option chosen by participants was subjective; however, examples were given, eg, changing a pad every 2 hours, or passing clots would be considered heavy. To investigate the association of characteristics with heavy bleeding, generalised estimating equations (GEE) were used. Specimen size was calculated by individually reviewing histopathology, and using the measurements obtained to determine the size of the specimen (or specimens with multiple fragments) of the cumulative amount of cervix taken. The median tissue size based on these results was determined to be 689.19 mm3. The baseline demographics of interest were age, body mass index (BMI) and LEEP size.
RESULTS
In total 215 participants were invited with 110 full responses being recorded, 74 of these completed the full 4 weeks of the survey (see Table 1). There was a wide range of age features in these responses, with the youngest participant being 23 and the oldest 77. Mean age was 33. Participants underwent LEEP for HSIL (high‐grade squamous intraepithelial lesion) as described earlier; however, around 10% of the final pathology specimens yielded only LSIL which is consistent with published standards 21 (see Tables 1 and 2).
Table 1.
Demographics
| All study participants | |||||
|---|---|---|---|---|---|
| Parameter | Summary | Week 1 | Week 2 | Week 3 | Week 4 |
| n = 110 | n = 97 | n = 83 | n = 74 | ||
| Age, years | Age < 40 | 86 (78.1%) | 76 (78.3%) | 65 (78.3%) | 58 (78.3%) |
| Age > 40 | 26 (23.6%) | 21 (21.6%) | 18 (21.6%) | 16 (21.6%) | |
| Mean age | 35 | 34 | 35 | 34 | |
| Median age | 33 | 33 | 33 | 33 | |
| Range | 23–75 | 23–66 | 23–66 | 23–66 | |
| Body mass index (BMI) | BMI < 20 | 20 (18.3%) | 17 (17.5%) | 14 (16.8%) | 13 (6.7%) |
| BMI 20–25 | 63 (57.9%) | 55 (56.8%) | 47 (56.7%) | 41 (66.3%) | |
| BMI > 25 | 26 (23.8%) | 25 (25.7%) | 22 (26.5%) | 20 (27%) | |
| Median BMI | 22.05 | 22.31 | 21.92 | 21.69 | |
| Mean BMI | 23.3 | 23.59 | 23.82 | 23.6 | |
| Unquantified | 1 | 0 | 0 | 0 | |
| Excessive bleeding, >3 days + heavy | Excessive bleeding | 34 (30.9%) | 31 (31.9%) | 14 (16.8%) | 5 (6.7%) |
| Specimen size | Median LEEP, mm3 constant | 689.19 | 689.19 | 689.19 | 689.19 |
| LEEP size_ < median | 54 (49%) | 48 (49.4%) | 40 (48.2%) | 36 (48.6%) | |
| LEEP size_ > median | 56 (51%) | 49 (50.6%) | 43 (51.8%) | 38 (51.4%) | |
| Mean LEEP size, mm3 | 858.73 | 815.08 | 828.07 | 823.97 | |
| Lifestyle – smoking status | Current smokers | 16 (14.5%) | 13 (13.4%) | 11 (13.2%) | 10 (13.5%) |
| Non‐smoking | 94 (85.5%) | 84 (86.6%) | 72 (86.8%) | 64 (86.5%) | |
| Lifestyle – alcohol consumption | No alcohol | 46 (41.8%) | 36 (37.1%) | 31 (37.4%) | 25 (33.8%) |
| Consumed alcohol < 5 std drinks | 42 (38.2%) | 37 (38.1%) | 31 (37.4%) | 34 (46%) | |
| Consumed alcohol > 5 std drinks | 22 (20%) | 24 (24.7%) | 21 (25.3%) | 15 (20.2%) | |
| Total % consuming alcohol | 58.10% | 62.80% | 62.60% | 66.20% | |
| Lifestyle – exercise activity | No/light exercise | 102 (92.8%) | 87 (89.7%) | 66 (79.6%) | 53 (73%) |
| Heavy exercise | 8 (7.2%) | 10 (10.3%) | 17 (20.4%) | 21 (27%) | |
| Lifestyle – intercourse | None | 107 (97.3%) | 91 (94%) | 66 (79.5%) | 39 (52.7%) |
| Once | 3 (2.7%) | 3 (3%) | 8 (9.7%) | 18 (24.3%) | |
| More than once | 0 (0%) | 3 (3%) | 9 (10.8%) | 17 (23%) | |
| HPV status | HPV 16/18 | 27 (24.5%) | 20 (20.5%) | 17 (20.5%) | 15 (20.3%) |
| HPV other | 63 (57.3%) | 60 (62%) | 51 (61.4%) | 46 (62.2%) | |
| Both | 11 (10%) | 10 (10.3%) | 8 (9.6%) | 7 (9.5%) | |
| HPV negative | 9 (8.2%) | 7 (7.2%) | 7 (8.5%) | 6 (8%) | |
| Grade | CIN 2/3 (HSIL) | 97 (88.2%) | 85 (87.6%) | 73 (87.9%) | 66 (89.2%) |
| LSIL | 11 (10%) | 10 (10.3%) | 9 (10.8%) | 8 (10.8%) | |
| Both | 2 (1.8%) | 2 (2.1%) | 1 (1.3%) | 0 (0%) | |
| Margins | Positive | 26 (23.6%) | 21 (21.6%) | 19 (22.9%) | 59 (79.7%) |
| Clear | 84 (76.4%) | 76 (78.4%) | 64 (77.1%) | 15 (20.3%) | |
| Total | Total participants | 110 | 97 | 83 | 74 |
| Lost to follow‐up | 0 | 13 (11.8%) | 27 (24.5%) | 36 (32.7%) | |
CIN, cervical intraepithelial neoplasia; HPV, human papilloma virus; HSIL, high‐grade squamous intraepithelial lesion; LEEP, loop electrosurgical excision procedure; LSIL, low‐grade squamous intraepithelial lesion.
Table 2.
Heavy bleeding subset demographics
| Parameter | Summary | Week 1 | Week 2 | Week 3 | Week 4 |
|---|---|---|---|---|---|
| n = 34† | n = 31† | n = 14† | n = 3† | ||
| Age, years | Age < 40 | 25 (73.5%) | 26 (83.9%) | 11 (78.6%) | Unable to analyse |
| Age > 40 | 9 (26.5%) | 5 (16.1%) | 3 (21.4%) | ||
| Mean age | 36 | 34 | 37 | ||
| Median age | 34 | 33 | 35 | ||
| Range | 23–66 | 23–66 | 27–66 | ||
| Body mass index (BMI) | BMI < 20 | 3 (8.8%) | 6 (19.3%) | 3 (21.4%) | |
| BMI 20–25 | 21 (61.8%) | 20 (64.5%) | 8 (57.1%) | ||
| BMI > 25 | 10 (29.4%) | 5 (16.1%) | 3 (21.4%) | ||
| Median BMI | 22.37 | 21.7 | 21.8 | ||
| Mean BMI | 23.7 | 22.6 | 23.5 | ||
| Specimen size | Median LEEP, mm3 constant | 689.19 | 689.19 | 689.19 | 689.19 |
| LEEP size_ < median | 11 (32.3%) | 12 (38.7%) | 3 (21.4%) | ||
| LEEP size_ > median | 23 (67.7%) | 19 (61.3%) | 11 (78.6%) | ||
| Mean LEEP size, mm3 | 1036.12 | 933.8 | 997.3 | ||
| HPV status | HPV 16/18 | 8 (23.5%) | 4 (12.9%) | 3 (21.4%) | |
| HPV other | 16 (47.1%) | 22 (71%) | 8 (57.1%) | ||
| Both | 8 (23.5%) | 4 (12.9%) | 3 (21.4%) | ||
| HPV negative | 2 (5.9%) | 1 (3.2%) | 0 (0%) | ||
| Grade | CIN 2/3, HSIL | 29 (85.3%) | 27 (87.1%) | 12 (85.7%) | |
| LSIL | 5 (14.7%) | 4 (12.9%) | 2 (14.3%) | ||
| Margins | Positive | 9 (26.5%) | 6 (19.4%) | 4 (28.6%) | |
| Clear | 25 (73.5%) | 25 (80.6%) | 10 (71.4%) | ||
| Lifestyle – smoking status | Current smokers | 4 (11.8%) | 2 (6.5%) | 0 (0%) | |
| Non‐smoking | 30 (88.2%) | 29 (93.5%) | 14 (100%) | ||
| Lifestyle – alcohol consumption | No alcohol | 20 (58.8%) | 13 (41.9%) | 8 (57.1%) | |
| Consumed alcohol < 5 std drinks | 12 (35.3%) | 15 (48.4%) | 2 (14.3%) | ||
| Consumed alcohol > 5 std drinks | 2 (5.8%) | 3 (9.6%) | 4 (28.5%) | ||
| Total % consuming alcohol | 41.10% | 58% | 42.80% | ||
| Lifestyle – exercise activity | No/light exercise | 30 (88.2%) | 24 (77.4%) | 10 (71.4%) | |
| Heavy exercise | 4 (11.8%) | 7 (22.6%) | 4 (28.6%) | ||
| Lifestyle – Intercourse | None | 34 (100%) | 30 (96.8%) | 11 (78.6%) | |
| Once | 0 (0%) | 1 (3.2%) | 1 (7.1%) | ||
| More than once | 0 (0%) | 0 (0%) | 2 (14.3%) |
CIN, cervical intraepithelial neoplasia; HPV, human papilloma virus; HSIL, high‐grade squamous intraepithelial lesion; LEEP, loop electrosurgical excision procedure; LSIL, low‐grade squamous intraepithelial lesion.
†Heavy bleeding refers to participants who bled for >3 days with blood ± clots.
A majority (67%) of participants were treated for dysplasia secondary to ‘HPV Other’ (indicating a HPV strain that is not 16/18). There were 69% of women who reported some form of bleeding in their first post‐operative week, which increased to 75.2% in the second week. Of these women 30.9% and 31.9% categorised their bleeding as severe in the first and second weeks respectively. In addition, over 50% of participants reported some form of vaginal bleeding up to and including the fourth post‐operative week.
Results were analysed using cross tabulation and GEE looking at reported bleeding rates and also within a defined group of responses categorised as heavy bleeding (as previously categorised). The results are detailed in Tables 3 and 4.
Table 3.
Statistical analysis
| Univariate model | P‐value | ||
|---|---|---|---|
| Week 1 | Week 2 | Week 3 | |
| BMI | 0.618 | 0.172 | 0.799 |
| Age | 0.545 | 0.704 | 0.308 |
| LEEP size | 0.100 | 0.18 | 0.277 |
| LEEP size binary | 0.013 | 0.144 | 0.024 |
| Smoking | 0.939 | 0.476 | 0.191 |
| Alcohol | 0.021 | 0.073 | 0.191 |
| Exercise days | 0.295 | 0.989 | 0.072 |
| Exercise intensity | 0.243 | 0.018 | 0.172 |
| Sexual activity | 0.133 | 0.221 | 0.912 |
| LMP | 0.253 | 0.024 | 0.825 |
| HPV 16/18 | 0.068 | 0.45 | 0.266 |
| HPV other | 0.716 | 0.069 | 0.488 |
| Margins | 0.642 | 0.705 | 0.587 |
| HSIL | 0.285 | 0.571 | 0.66 |
| LSIL | 0.537 | 0.913 | 0.782 |
| Characteristic | OR | 95% CI | P‐value |
|---|---|---|---|
| Multivariate model week 1 | |||
| LEEP size binary | 2.84 | 1.15, 7.40 | 0.023 |
| Alcohol | 0.036 | ||
| 1 | — | — | |
| 2 | 0.44 | 0.17, 1.11 | |
| 3 | 0.1 | 0.01, 0.62 | |
| 4 | 0.21 | 0.01, 1.55 | |
| HPV 16/18 | 2.91 | 1.16, 7.65 | 0.023 |
| Multivariate model week 2 | |||
| Exercise intensity | 0.013 | ||
| 1 | — | — | |
| 2 | 0.38 | 0.08, 1.39 | |
| 3 | 2.8 | 0.99, 8.26 | |
| Multivariate model week 3 | |||
| LEEP size binary | 8.16 | 1.74, 60.7 | 0.006 |
| Exercise intensity | 0.039 | ||
| 1 | — | — | |
| 2 | 4.48 | 0.44, 48.4 | |
| 3 | 7.55 | 1.55, 57.0 | |
BMI, body mass index; CI, confidence interval; HSIL, high‐grade squamous intraepithelial lesion; LEEP, loop electrosurgical excision procedure; LMP, last menstrual period; LSIL, low‐grade squamous intraepithelial lesion; OR, odds ratio.
Table 4.
Generalised estimating equations model
| Characteristic | OR | 95% CI | P‐value |
|---|---|---|---|
| LEEP size binary | 2.60 | 1.27, 5.32 | 0.009 |
| Week | |||
| 1 | — | — | |
| 2 | 0.70 | 0.36, 1.35 | 0.3 |
| 3 | 0.13 | 0.03, 0.53 | 0.005 |
| Exercise intensity | |||
| 1 | — | — | |
| 2 | 0.55 | 0.21, 1.39 | 0.2 |
| 3 | 0.28 | 0.06, 1.29 | 0.10 |
| Week * Exercise intensity | |||
| 2 * 2 | 0.79 | 0.16, 3.95 | 0.8 |
| 3 * 2 | 5.52 | 0.64, 47.4 | 0.12 |
| 2 * 3 | 8.88 | 1.60, 49.1 | 0.012 |
| 3 * 3 | 16.1 | 2.08, 125 | 0.008 |
CI, confidence interval; OR, odds ratio.
While no correlation was discovered between age, BMI, or day of menstrual cycle, there was a statistically significant correlation between exercise intensity (as defined by >3 days per week and medium to high‐intensity sessions) and increased bleeding (95% CI) (See Table 3). A significant association was seen between LEEP size as expressed as a dichotomous variable (greater than median size) and the risk of reported heavy bleeding. There was also a correlation between decreased alcohol consumption and increased bleeding; however, this was not evident after the first week. A further association was also seen between HPV 16/18 strains and increased bleeding in the first week; however, this was not evident in the following weeks.
DISCUSSION
This study was limited by its small sample size; however, this was an intense survey with a significant time and commitment from the participants over 4 weeks. This is reflected in the number invited n = 215 and the number that successfully completed at least one of the surveys (n = 110). In addition, the self‐reporting nature of recall of bleeding rates is subjective.
While subjective reporting of bleeding loss does positively correlate with blood loss objectively measured, its positive predictive value is low. 22 , 23 There are many factors that influence this, including number of days bleeding, positive or negative experiences associated with this blood loss, number of sanitary products utilised and pain experienced. 22 , 23 Women with a high health literacy, who have experienced menorrhagia, or given birth vaginally may be subjectively unconcerned about using a high number of sanitary products in a eight‐hour window. 22 This same consumption of sanitary products could be distressing to women who previously have experienced only light menstrual bleeding. 22
These concerns and deficits in subjective data could have been augmented by the collection of qualitative data about perceived blood loss which may have assisted distinguishing why participants who reported high blood loss did so. 24 Factors including first language spoken, health literacy, and individual experiences of the blood loss would have allowed for understanding and to an extent, more accurately quantifying how heavy bleeding was. 24 Socioeconomic concerns remain a confounding factor as those with more time and availability are more likely to participate than those who are financially or time poor. A useful addition would have been the parity of the participant, due to both the changes that occur in the cervix, especially in multiparous women. As previously mentioned, women who did not have access to email communication, or were unable to communicate in the English language were also excluded. We acknowledge that this has the potential to effect the quality of the data received and reflect a predominantly Western society. Qualitative data also acknowledges that this bleeding experience is retrospectively reported, and can thus augment the quantitative data reported. 24
Recall bias is of a moderate concern in our study as participants who have moderate to severe bleeding could potentially be more likely to participate in the survey process due to their symptoms. This reflects the retrospective nature of the data collection although the survey was sent out within a narrow time window from the procedure. Participants without significant bleeding could be lost to follow‐up if they do not finish the surveys due to their lack of symptoms, thus leading to an over‐representation of moderate to severe bleeding in the data. Due to the time‐critical nature of the survey it was not appropriate to send repeat invitations out and therefore the low response rate was an accepted consequence. Response bias is also important in this cohort study as those who volunteer to enrol in this study may represent a population of people who are more aware and involved in their medical health, as evidenced by their willingness to be involved in medical research. 25 These patients could potentially be more likely to over‐report their bleeding symptoms and create a picture of increased episodes of bleeding which may not reflect the actual population. 25 By utilising contemporaneous survey design in which we split the data collection into four separate surveys weekly, we have attempted to limit the effect of recall bias and potentially attempt to collect subjective data that reflect more closely the lived experience of the patient.
The process of studying and following up patients itself influences the outcome and is of potential concern. In this observational bias, participants potentially could over‐report their bleeding as they are more aware of it due to the study highlighting it as a post‐operative experience. Unfortunately, it is impossible for this bias to be completely removed as we were unable to blind the participants to the intent of the study.
Specimen size, was defined by calculating the relative volume of a specimen based on histopathology measurements which was necessary due to the retrospective nature of collection of this data. In many of our participants, more than one pass with the electrosurgical loop was required, which would have complicated any data regarding size of loop utilised. This data point does not include the type of transformation zone or accurate measurement of removed tissue volume relative to the existing cervical volume but was considered the most suitable measure given the number of patients. In weeks one, two and three the rates of heavy bleeding reported were significantly higher in those who had a LEEP size greater than the median (42% vs 20%, 39% vs 26% and 25% vs 8% for each week respectively). This might therefore be a consideration when advising patients on care following LEEP, particularly where other identified risk factors for bleeding are present.
Women who had increased exercise intensity (as defined by >3 days per week and medium to high‐intensity sessions) reported significantly increased bleeding (P = 0.013, Table 3). Exercises which put strain in the pelvis, such as a bicycle seat, leg squats and lunges, intense sprinting/running, and high‐intensity interval workouts, could also be a contributing factor due to the increased possibility of cervical clot disruption and interruption of healing of the tissue of the cervix. The strenuous nature of different exercises may also be a factor. The increased heart rate, cardiac output and dilation of blood vessels generated by intense exercise could contribute to an increase in ongoing bleeding once clot disruption has occurred.
Of concomitant interest in this cohort, a majority (67%) of participants were treated for dysplasia secondary to ‘HPV Other’ (indicating a HPV strain that is not 16/18). This most likely reflects a relative rise in HSIL from non‐16/18 strain HPV due to the widespread vaccination program in Australia against HPV 16/18. This vaccination program began over ten years ago and targeted high school‐aged teenagers in a mass vaccination. Other countries have also adopted this vaccination scheme. A cross‐sectional study 26 displayed a declining trend in HPV 16/18 diagnoses and found that women born after 1994 (who therefore underwent mass vaccination at or before the age of 13), had a near 90% risk reduction of HPV 16/18. However, the same study has shown no risk reduction currently, of developing ‘HPV Other’ (non‐vaccinated genotypes). This reflects an area of interest which could benefit from future research into identifying ongoing rise in cervical neoplasia arising from non‐16/18 type HPV in the era of vaccine suppression of 16/18 type HPV.
Based on the interesting findings of this pilot study we have identified two areas for potential future research. These include a definitive study into the correlation between bleeding pattern and LEEP volume as well as the correlation between patterns of exercise and post‐LEEP bleeding.
In conclusion, post‐operative bleeding risk factors in women undergoing LEEP remain elusive in the literature. Women who undergo intense or prolonged exercise in the post‐operative period may experience heavier bleeding, particularly in the first two weeks post‐LEEP. The size of the specimen removed is also likely to be a significant factor in post‐LEEP bleeding risk. We found no correlation between age, BMI or any other demographical factor and heavy bleeding in our analysis.
FUNDING
Financial contributions.
ACKNOWLEDGEMENTS
Gillian Heller (statistical analyst, Sydney Local Health District, NSW Health). Open access publishing facilitated by The University of Sydney, as part of the Wiley ‐ The University of Sydney agreement via the Council of Australian University Librarians.
Conflict of Interest: The authors report no conflicts of interest.
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