Refractive errors are the most common cause of visual impairment worldwide. Its proportion varied among societies and is considered as a public health challenge. Symptoms and signs associated with refractive errors are the most worrisome and common presentations in the general practice in eye clinics. Methodology. A cross-sectional study including 1,500 out-patients aged from 0 to 30 years attending the ophthalmology clinic in Sanaa, Yemen (between 2012 and 2015). All patients underwent visual acuity examination, autorefractometer, and anterior and posterior segment examination and were grouped according to type, that is, myopia, hyperopia, and astigmatism.  The goal of this study was to determine the types and presentations of refractive error among the 0–30-year-old Yemeni population to aid early identification, diagnosis, referral, and treatment.  Hyperopia was the most common single diagnosis (53.3%) followed by myopia (33.3%). Astigmatism was uncommon as a single diagnosis (13.4%) but commonly associated with hyperopia or myopia. Myopia was more common in males (42.9%) than in females (25%). Hyperopia was more in females (62.5%) than in males (42.9%). Age groups most affected by refractive errors were 13–18 years (27.7%), 19–24 years (24.8%), and 25–30 years (24.6%), respectively. Decreased vision (53%) was a common presentation in myopia and astigmatism (41.5%) and less in hyperopia (39.6%). Headache was common in astigmatism (56%), hyperopia (28.8%), and myopia (17.8%). Muscle imbalance, namely, exotropia (27.2%), is mainly found in myopia and esotropia (24.3%) in hyperopia.  In addition to decreased vision, our patients with refractive errors mostly complain of headaches with clear variations with age and type of refractive error. Early identification and proper categorization of refractive errors by age, gender, and other demographics by general physicians in primary care can better deduce and make useful referrals to eye specialists. Refractive error is a problem with focusing light accurately on the retina due to the shape of the eye. The most common types of refractive error are near-sightedness (myopia), far-sightedness (hyperopia), astigmatism, and presbyopia. Near-sightedness results in faraway objects being blurry, far-sightedness, presbyopia results in close objects being blurry, and astigmatism causes objects to appear stretched out or blurry. Other symptoms may include double vision, headaches, and eye strain. Refractive errors are corrected with eyeglasses, contact lenses, or surgery . The numDecreased vision and headache are common presentations associated with visual disability and refractive errors seen in general practice and at specialist eye clinics –11. Myope5.2) in children. The lowest and highest EPP was seen in South-East Asia  and the Americas , respectively. The EPP of hyperopia was 30.6% (95% CI: 26.1e35.2) in adults. Based on the results of the meta-analysis, Africa had the highest EPP of hyperopia  followed by the Americas  while Europe had the lowest EPP  [According to the WHO regions, the estimated pool prevalence (EPP) of hyperopia was 4.6% (95% CI: 3.9.1e40.2) .e17.1). According to WHO regions, the lowest estimated pool prevalence (EPP) was seen in South-East Asia (9.8%) while the highest EPP was seen in the Americas (27.2%) followed by the Eastern Mediterranean region (20.4%). For adults, studies showed that 40.4% (95% CI: 34.3e46.6) of adults had astigmatism. However, astigmatism showed a lot of variation in different WHO regions; the highest EPP astigmatism was seen in the Americas, and the lowest EPP was seen in Africa (11.4% vs. 45.6%). However, it should be noted that only one study was conducted in the Americas. After the Americas, South-East Asia had the highest EPP of astigmatism  [The definition of astigmatism in epidemiologic studies has less variation. Considering the changes of astigmatism with age, in children above 1 year old, astigmatism was 14.9% (95% CI: 12.7.6e53.1) .Given how common these eye defects are in clinical practice, research that helps to understand their natural history and especially local risk factors will be helpful for early diagnosis and properly targeted treatments in primary care practice. Therefore, the focus of this study was to determine the types and presentations of refractive errors among the 0–30-year-old Yemeni population a basis for developing preventive interventions.This was a cross-sectional clinical epidemiological study involving a convenient purposive sample of patients referred from across the country for ophthalmic consultation at the department of ophthalmology, Saudi–German Hospital, a major referral center for eye problems in Sanaa, Yemen. During the study period, all patients with eye problems are referred to the Saudi–German Hospital due to the limited facilities across the health centers in Yemen.This was a purposive sample whose selection was based on their willingness to participate in the study once they met the inclusion criteria. Given that our primary goal was to determine the types and presentation of refractive errors in our practice population, no specific sample size was calculated. No other similar studies were reported from the area on this topic.A total of 1500 patients between ages 0 and 30 years were included in this study following informed consent. Subjects were divided into the following age groups 0–6, 7–12, 13–18, 19–25, and 26–30 in order to include the maximum patients who agreed to participate in the study. We identified the patients who can benefit from vision rehabilitation. Then, we accurately measure visual acuity and provide appropriate vision rehabilitation services. Eligibility included referral for ophthalmic consultation by other clinicians for symptoms including decreased vision, headaches, esotropia, and exotropia. Patients, with a history of eye injury, aphakia retinoblastoma, and systemic or congenital disease were excluded from the study.Procedures: demographic data were obtained from patients' records and/or referral notes. All patients underwent visual acuity assessment and refraction measurement by cycloplegic autorefraction and subjective refraction.E, at a distance of 6 m. The right eye was tested first and then the left, each time with occlusion of the fellow eye. Ocular Examinations were done by a trained team consisting of an ophthalmologist. After assessment of visual acuity as above, axial length was measured by an IOL Master , and a slit lamp  examination and direct ophthalmoscopy were performed by an ophthalmologist. Intraocular pressure was measured by an optometrist using noncontact tonometry , and participants having a peripheral anterior chamber depth of >1/2 the thickness of cornea, IOP 25 mm Hg, given cycloplegia of one drop of 0.5% proparacaine hydrochloride in each eye followed by two drops of cyclopentolate 1.0%  5 minutes apart. If the pupil size was ‡6 mm and the light reflex was absent after 30 minutes, cycloplegia was deemed adequate. Subsequently, autorefraction  and subjective refraction were performed by an experienced optometrist.Visual Acuity Testing was performed with tumbling A value of 6/6 or 20/20 is considered optimum, or perfect vision. Individuals who have 20/20 vision are able to read letters that are 3/8 of an inch tall from 20 feet away. Those who do not have 20/20 vision are considered as refractive error. People who require spherical equivalent (SE) ≤ −0.50 Diopters of optical correction are considered as having myopia, SE ≥ +2.0. Diopters are considered having hyperopia and SE of −2.00 + 3.50 × 095. Diopters are considered having astigmatism. Once examined, patients were grouped into the following five categories: myopia only, hyperopia only, astigmatism only, myopia with astigmatism, and hyperopia with astigmatism.Data was collated and analysed in an Excel database. Subjects were grouped according to age, gender, presenting symptoms, and diagnosis based on the five categories identified. Descriptive statistics for categorical data included frequencies (percentages). Inferential statistics were used to make comparisons between error type, frequency of occurrence, and gender difference.The primary goal of these analyses was to determine the types and presentation of refractive errors and their possible association with gender and age as a basis for future predictions in Yemeni children and young adults especially in general practice in primary care. All analyses were performed in Microsoft Excel and an alpha level of 0.05 was considered statistically significant. Descriptive statistics of quantitative data are presented as proportions (percentages). Categorical data, for example, age group, gender, and presenting symptoms are also presented as proportions (percentages).Out of 1500 patients, 700 were males (46.7%) and 800 females (53.3%). Hyperopia was the most common single diagnosis (53.3%) followed by myopia (33.3%). Astigmatism was uncommon as a single diagnosis (13.4%) but commonly associated with hyperopia or myopia. Myopia was more common in males 42.9%) than females (25%). Hyperopia was more in females (62.5%) than males (42.9%) . Age gro.9% than Myopia was diagnosed in 500 patients and occurred in all age groups from 0 to 30 years but was more common in males (42.9%), compared to females (25%). There was also a progressive increase in the frequency of myopia with age from 0–6 years (28%) to 25–30 years (47.3%) .M = 42.9%; F = 62.5%). In terms of age distribution, all age groups 0–30 years were affected but highest in the 13–18-year-old group (67.8%) followed by the 19–24-year-old group (45.7%)  .Astigmatism was diagnosed in 200 patients with increased distribution in males (14.3%) and females (12.5%). No cases of astigmatism were found in the 0–6-year-old group. It was much higher in the 19–24-year-old group (18%) compared to the other groups .In terms of presentation, decreased vision (53%) was a major complaint in patients with myopia with a progressive increase in frequency from age 0–6 years from 48.6% to 57.2% in the 25–30-year group. A similar trend was found in hyperopia but starting from a higher frequency of 33.3% in 0–6 years with a plateau of around (47.9%) in the age group of 25–30 years. In astigmatism, decreased vision was not found in the 0–6-year group and was less common before the age of 13 years but was a major complaint in the 25–30-year group (45.5%) and followed by 19–24-year groups (44.8%) .Headache was reported less in the 7–12-year-old group (9.2%) with myopia, increasing in the 25–30-year-old group (23.4% highest). In hyperopia, headache was most reported in patients between 13 and 30 years amongst whom the 19–24-year group (44.1%) complained the most followed by the 25–30-year group (40.7%) and 13–18-year-old group (34%). In astigmatism, there was a progressive decrease and increase in headache from 7 to 30 years old: 7–12 (57.1%), 13–18 (58.1%), 19–24 (55.2%), and 25–30 (54.5%), respectively .In our population, muscle imbalance, namely, exotropia, a form of strabismus where the eyes are deviated outward was found in 27.2% of myopia patients, and esotropia, a form of strabismus in which one or both eyes turn inward, was found in 2% of myopia patients. In myopia patients, exotropia found in all age groups 0–6 (34.3%) and 7–12 (46.1%) and 13–18 (38.9%), 19–24 (18.5%) and 25–30 (19.4%) respectively. A similar trend but much lesser frequency of exotropia was found in patients with hyperopia with the highest frequency (9.3%) in the 25–30-year group. Exotropia was not a feature of astigmatism, except in a very small percentage of the 7–12-year-old group (14.3%) .Similarly, esotropia was not found in astigmatism and only found in a small proportion of patients with myopia (2%). None of those aged between 13 and 30 years with myopia presented with esotropia. However, esotropia was a common feature in hyperopia, most common in the much earlier age groups 0–6 (61.1%) and 7–12-year-old group (51.7%). It was also found in the 13–18-year-old (21.4%) and 19–24-year-old group (8.8%) but very uncommon in the 25–30-year-old group (2.1%) . PresbyoRefractive errors are the most common ocular problem affecting all age groups and considered as a public health challenge. Recent studies and WHO reports indicate that refractive errors are the first cause of visual impairment and the second cause of visual loss worldwide as 43% of visual impairments are attributed to refractive errors . A revieThere were not any previous publications regarding the types and presentations of refractive errors in Yemen and neighboring countries. Previous studies reported a decrease in myopia and an increase in hyperopia with increasing age , 23–26. According to a meta-analysis conducted in the Middle East region, the prevalence of astigmatism was 15%  in subjects less than or equal to 15 years and 24%  in those older than 15 years of age . The preA review study found a higher prevalence of hyperopia in Eastern Mediterranean children than in African, Southeast Asian, and Western Pacific children . A generThe association of gender with refractive errors has not been well established. Some studies have reported that the prevalence of myopia is higher in men than in women , 28–31. The limitations of the current study included that the selection of individuals was conducted using nonprobability sampling and did not also consider regional and occupational differences. For wider use and predictive generalization, a more randomized probability population sample may be necessary. Thus, despite possible limitations, a sample of patients who visited the ophthalmic clinic for any laboratory service or visual examination from different parts of the Yemen was used for the examination of refractive errors, which ensures some representation of the population. Furthermore, the types and presentations of refractive error in children and young adults have not been previously studied in Yemen. To our knowledge, this is the first report of refractive error in the Yemeni population.The information of this study can be used to characterize and potentially predict types of refractive error among Yemeni children and young adults. The findings may be found useful among primary care and general practitioners and eye specialists and could help in the development of simple diagnostic tools such as clinical algorithms to aid early diagnosis and management.


This study aimed to examine the risk factors for surgical site infection (SSI) and the association of that with recurrence in JCOG0212. The results for secondary endpoints showed that compared with the mesorectal excision (ME) alone group, ME with lateral lymph node dissection (LLND) group showed significantly longer operative time and significantly higher blood loss. These results suggested that LLND was a risk factor for SSI. All 701 patients registered in JCOG0212 were analyzed in this study. Wound infection was defined as incisional/deep SSI, and pelvic abscess and anastomotic leakage were defined as organ/space SSI. The risk factors for the incidence of SSI and the effect of SSI on relapse-free survival (RFS) were investigated. Multivariable odds ratio of Grade 2 or higher all SSI was 0.58 [95% Confidence interval: 0.36–0.93] for female  and that of Grade 2 or higher incisional/deep SSI was 2.24 [1.03–4.86] for blood infusion. For RFS, patients with Grade 3 or higher all SSI showed poor prognosis (multivariable hazard ratio: 1.66 [1.03–2.68]). LLND is not significant factor for the incidence of all SSI. Male sex might be a risk factor of Grade 2 or higher SSI, and blood transfusion is a possible risk factor of Grade 2 or higher incisional/deep SSI. Grade 3 or higher all SSI might be a significant worse prognostic factor for lower rectal cancer. Surgical site infection (SSI), an infection associated with surgery, is a major complication. Generally, SSI is the second-most frequent occurring medical infection in developed countries . One of In surgery for the treatment of lower rectal cancer, mesorectal excision (ME) with lateral pelvic lymph node dissection (LLND) is the standard surgical procedure for patients with advanced lower rectal cancer in Japan . AutonomOn the other hand, ME with chemo-radiotherapy is the global standard treatment for rectal cancer. Therefore, we conducted a randomized controlled trial, JCOG0212, and concluded that the non-inferiority of ME alone could not be confirmed compared with ME with LLND .To the best of our knowledge, JCOG0212 may be the only clinical trial worldwide that has been performed on LLND. By performing LLND, recurrences in the pelvis were reduced from 12.6 to 7.4%; however, the duration of surgery increased by 106 min, the volume of blood loss increased by 239 mL, and Grade 3 or higher complications were reported in 22% versus 16% of patients . GeneralInclusion criteria of JCOG0212 have been reported previously. Eligibility criteria included histologically proven rectal cancer at clinical Stage II or III; , with the lower margin being below the peritoneal reflection; performance status of 0 or 1; and age 20–75 years. A total of 701 patients were randomized to the ME with LLND group (n = 351) or the ME alone group (n = 350).Wound infection was defined as incisional/deep SSI, and pelvic abscess and anastomotic leakage were defined as organ/space SSI according to NCI-CTC ver.2.0 in the present study . The defEach event numbers were small. Therefore risk factors for the incidence of Grade 2 or higher SSI were analyzed according to definitions of SSI . Odds ratio (OR) and its 95% confidence intervals (CI) for each factor were calculated by the multivariable logistic regression model in 691 patients without missing variables. The RFS and local RFS by definitions of SSI Grade were estimated according to the Kaplan–Meier method in all 701 patients. The effects of SSI on RFS and local RFS were evaluated by the multivariable Cox regression analysis in 693 patients without missing variables. The covariates were selected using a backward method with exclusion criteria of significance level of 0.20 under forcibly including the presence or absence of Grade 2 or higher and Grade 3 or higher SSI. Hazard ratio (HR) and its 95% CIs for each factor in the final model were described. A p-value of ≤ 0.05 was considered statistically significant. All statistical analyses were performed by SAS ver. 9.4.The grade 2 or higher all SSI was observed in 120 (17.1%) patients and all Grade 3 or higher in 48 (6.8%) patients . Presence of blood transfusions was a significant risk factor for the incidence of Grade 2 or higher incisional/deep SSI . No significant factors for the incidence of Grade 2 or higher organ/space SSI were noted.  and 72.5% (95% CI 63.5–79.6%), respectively . For incisional/deep SSI, the 5-year RFS for patients with Grade 1 or lower and Grade 2 or higher SSI were 73.4% (95% CI 69.8–76.7%) and 72.6% (95% CI 58.8–82.5%), respectively . For organ/space SSI, the 5-year RFS in patients with Grade 1 or lower and Grade 2 or higher SSI were 73.6% (95% CI 69.9–76.9%) and 71.6% (95% CI 60.4–80.1%), respectively .The 5-year RFS for patients with Grade 2 or lower and Grade 3 or higher all SSI were 74.3% (95% CI 70.8–77.5%) and 60.4% (95% CI 45.2–72.6%), respectively . For incisional/deep SSI, the 5-year RFS for patients with Grade 2 or lower and Grade 3 or higher SSI were 73.7% (95% CI 70.2–76.8%) and 61.1% (95% CI 35.3–79.2%), respectively . For organ/space SSI, the 5-year RFS in patients with Grade 2 or lower and Grade 3 or higher SSI were 74.2% (95% CI 70.7–77.3%) and 56.3% (95% CI 37.6–71.3%), respectively  . Incisional/deep Grade 3 or higher SSI was not a significant risk factor , whereas organ/space SSI was significantly associated with RFS .  for patients with Grade 2 or lower and Grade 3 or higher all SSI were 82.1% and 79.1%. For incisional/deep SSI, the 7-year OS for patients with Grade 2 or lower and Grade 3 or higher SSI were 82.4% and 77.8%. For organ/space SSI, the 7-year OS in patients with Grade 2 or lower and Grade 3 or higher SSI were 82.0% and 78.2%. Grade 3 or higher SSI did not affect the overall survival rate.But this study has some limitations. One is that there were few events of SSI. Another one is that the primary endpoint of this clinical trial was not the association of SSI. And therefore we might not take enough dates for analysis.In conclusion, the risk factors of the incidence of Grade 2 or higher all SSI was male sex and that of incisional/deep SSI was presence of blood transfusions. LLND was not associated with any SSI. The incidence of Grade 3 or higher all SSI and space/organ SSI was a significant prognostic factor in laparotomy for rectal cancer and requires preventive measures.


To analyze the prevalence & characteristics of sudden sensorineural hearing loss.st July 2019 to 31st October 2019. Study was conducted at Audiology section of ENT department, Lahore General Hospital, Pakistan. Sample included both genders, aged 17-70 years. Cases suffering from inflammatory or obstructive conditions of the external or middle ear and those who could not undergo pure tone audiometry were excluded from the study. Following consent for inclusion in study, data was collected using basic demographic and medical history sheet followed by Audiometric evaluation. Statistical Software for Social Sciences Version 20.0 was used for data analysis.This cross sectional study including n=377 cases of sensorineural hearing impairment, using non-probability convenience sampling, who fulfilled the selection criteria was conducted from 1The prevalence rate of sudden sensorineural hearing loss of 14(3.7%) being significantly more common in males 11(78%) than females 3(22%) (p=0.05) & age group 15-35 years (p=0.001). It is commonly of severe or profound degree with downward sloping audiogram (p<0.05), however it is not associated with vertigo (p=0.32), tinnitus (p=0.08) with no side predilection (p=0.27).We conclude that the prevalence of SSNHL is 3.7% being significantly more prevalent in males and those aged15-25 years. It is mostly characterized by severe to profound degree of hearing loss with downward sloping audiogram with no associated vertigo, tinnitus and side predilection. Sudden sensorineural hearing loss (SSNHL) is considered a medical emergency3The exact incidence of Sudden SNHL is not known. Estimate of incidence show a wide range of 11-77 per 100,000 people per year,7SSNHL is a subjective symptom perceived by the patient and hence to determine prevalence of hearing loss (HL), its type and threshold of hearing, a pure-tone audiogram is required.Acknowledging the available literature, the exact prevalence of SSNHL is not known with highly variable incidence reported in studies,th June, 2019 and informed consent of the sample. A basic demographic sheet, medical history sheet and PTA were used to collect data.This is a cross sectional study which recruited n= 377 patients with SNHL, who attended Audiology section of ENT Department of Lahore General Hospital, Pakistan using non probability convenience sampling technique over a period of four months extending from 1st July 2019 to 31st October 2019. Sample included both genders, aged 17-70 years. Cases with inflammatory and obstructive pathologies of external and middle ear, those who could not undergo audiological testing or were found to have conductive element were excluded. Study was conducted after obtaining approval of IRB of Isra Institute of Rehabilitation Sciences, Isra University vide Registration No 1609-M.Phil HS-007 dated 24History was noted in a confidential setting including duration of HL, associated complications like tinnitus, vertigo, exposure to ototoxic agents, occupational or leisure noise and treatment history. This was followed by physical examination including otoscopy to rule out any obstructive and inflammatory pathology and pure tone audiometry was done in cases suspected of having sensory neural hearing loss. Computer based Pure Tone Audiometer Labat, made in Italy was used and testing performed in sound proof room which met American National Standards Institute (ANSI) S 3.1-1991 standards. Both ears will be tested for air and bone conduction using the method of ascending pure tones at frequencies of 0.5, 1, 2, 4, 6 and 8 kHz before descending to 1 and 0.5 kHz. Bone conduction was checked at frequencies of 0.5 to 4 kHzData collected was analyzed using SPSS - Version 20.0. Descriptive statistics was used. Variables specially studied included degree and type of HL, ears affected, associated symptoms and age and gender. Pearson’s Chi-square test was used to determine association of type of HL with demographic and clinical variables. Independent sample t-test was used to see any significant difference in mean thresholds between the two ears. P-value of 0.05 was taken as significant.Sample of 377 cases, revealed 203 (53.8%) males and 174(46.2%) females with a ratio of 1.67:1 and mean age of 42.04±1.73 years . Of the Majority (n=12) cases of age group 15-35 years suffered SSNHL, while remaining (n=2) belonged to 36-55 years age group indicating significant (p=0.001) age association with SSNHL. Similarly gender association was noted (p=0.05) with 11 males and 3 females having SSNHL.No significant association (p=0.32) of vertigo was noted with no case of vertigo among cases of SSHL. Similarly no significant association (P=0.081) of tinnitus was noted with eight out of 14 cases of SSNHL having tinnitus and 125 out of 363 cases of chronic hearing loss with tinnitus.There was significant association (p=0.032) of severity of hearing loss in the right ear with maximum (n=8) cases having profound and n=4 having severe hearing loss among cases with SSNHL. On the other hand in the Left ear majority (n=6) had severe HL while n=5 had normal hearing in the group with SSNHL. While in the chronic HL cases majority (n=111) had profound HL. The difference was significant (p<0.001)No significant difference (p-0.27) was noted as regards side affected in SSNHL and chronic HL groups. As regards threshold of hearing in cases with SSNHL study revealed a continuous rise from a Mean threshold of 54.28±28.22 at 250 Hz to 72.89±31.04 at 8 KHz in the Right Ear and from 54.88±28.62 at 250 Hz to 75.46+30.78 at 8 KHz in the Left Ear. However, t-test statistics did not reveal any significant difference at all the frequencies form 250- to 8 kHz .Sudden sensorineural hearing loss, recovers spontaneously in majority, hence exact incidence is not known with a wide range of 11 to 77 per 100,000 people affected per year.9In the current study of the 89 cases with unilateral HL, 5 had SSNHL, while of the 288 cases with bilateral HL 9 had SSNHL, however the difference was not statistically significant (p-0.27). In contrast to our study in which majority had bilateral HL, in a study by Atay G et al. in 45.9% cases right ear was affected and in 54.1% left ear was affected.10Present research revealed that SSNHL is more prevalent in males as compared to females. With a total population of 203 (53.8%) males and 174(46.2%) females, 11 males and three females had SSNHL and difference was significant (p=0.05). Similarly, in study by Atay G et al. males were predominantly affected.In the present study, SSNHL was significantly (p=0.001) more common in age group 15-35 years with 12 cases, while remaining two cases belonged to 36-55 years age group. In contrast Alexander and Harris, reported a higher incidence of 77/ 100000 cases at age 65 and above compared to 11/100000 below 18 years of age.As regards etiology, different studies have reported widely varying prevalence of different etiological causes. According to Lloyd SKW et al. in 30% cases of SSNHL cause is identified including infection (44%), otologic disease (17%), neurologic and vascular 12%), malignancies (7%) and miscellaneous (4%), while the remaining 70% cases are idiopathic.%, malignIn the present study there was significant association (p=0.032) of severity of hearing loss with type of HL with majority (eight cases) having profound SSNHL followed by (4 cases) with severe SSNHL in the right ear. On the other hand in the Left ear majority (6 cases) had severe SSNHL while (five cases) had normal hearing in the group with SSNHL. In this study the mean threshold of hearing in cases with SSNHL showed a continuous rise (Downward sloping audiogram) from a Mean threshold of 54.28±28.22 at 250 Hz to 72.89±31.04 at 8 KHz in the Right Ear and from 54.88±28.62 at 250 Hz to 75.46±30.78 at 8 KHz in the Left Ear. However, t-test statistics did not reveal any significant difference at all frequencies form 250- to 8kHz. In contrast in a study by Atay G et al. reported that majority (29.8%) had flat audiogram configuration, followed by downward sloping audiogram in 26% and upward sloping audiogram configuration in 22.7%. However profound degree of HL was noted in 21.5% cases of SSNHL.10Common associated symptoms include aural fullness, vertigo and tinnitus.17According to Atay G et al. early initiation of treatment within five days (p<.05) and flat audiogram in mid frequencies (p<0.05) show better prognosis 20We conclude that the prevalence of SSNHL is 3.7% being significantly more prevalent in males and those aged 15-25 years. It is mostly characterized by severe to profound degree of hearing loss with downward sloping audiogram with no associated vertigo, tinnitus and side predilection.EN: Data Analysis & Interpretation, Literature Review & responsible for integrity of the researchGS: Conceptualization of work, designing of research & Manuscript Writing.NM: Critical revision of article.MNB: Literature search and Review.


Analysis was carried out in patients diagnosed with Clinically Isolated Syndrome (CIS), a precursor to MS, defined by a single episode of neurologic symptoms lasting at least 24 h. CIS is an indicator of future development of MS, as 60 % of the people diagnosed with CIS develop MS , using the the RepeatMasker program. Nomenclature used in Tables is indicated, the genomic location of each copy as well as alternative names used in the literature. Sequences corresponding to the coordinates listed were downloaded and compared to primer sequences using the “align” function in SerialCloner (version 2-6-1). Identity with primer sequence is indicated in black, mismatches in red.Additional file 3: Table S3. Number of reads mapping to the HERVW copies indicated in each of the five CIS or NDI (control) samples. The total number of reads per sample is indicated. The sum of reads in the CIS and NDI groups is indicated.Additional file 4: Table S4. Primers used.Additional file 5: Figure S1. Comparison of reference genes.Additional file 6: Figure S2. Comparison of HERVW elements.Additional file 7: Figure S3. qPCR primer efficiency standard curve analysis.Additional file 8: Supplementary Methods.Additional file 9. MIQE checklist.


BackgroundVaccination has provided a ray of hope in combating the coronavirus disease 2019 (COVID-19). Vaccines were rolled out as an emergency measure, with an expedited approval process. The available clinical trial data reveals the fact that vaccines mostly produce mild adverse events following immunization (AEFIs). Since the experiences are relatively new, it is important to monitor safety in a real-world setting. With this background, this survey was conducted.MethodsThis cross-sectional study was approved by the institutional ethics committee (IEC) of Vydehi Institute of Medical Sciences and Research Centre. This was conducted over a period of four months at select apartment complexes around Whitefield, Bangalore. The participants were invited to fill up data through online Google Forms . They were requested to provide demographic details, information related to vaccination, and AEFIs. Eligibility to participate included recipients of vaccines who received Emergency Use Authorization (EUA) in India. Data were analyzed using SPSS version 20.00 .ResultsTM  when compared with CovaxinTM  (P < 0.05). Of the participants, 5.9% (19) were diagnosed with COVID-19 post-vaccination. Among them, 15.8% (3) required hospitalization, with 10.5% (2) of them requiring an oxygen bed. It was observed that 76.5% (166) of the participants did not report their reactions to concerned authorities.The total number of participants in the study was 322. Out of this, 37.6% (121) were males and 62.4% (201) were females. The mean age of the participants was 34.9 ± 12.4 (mean ± standard deviation (SD) years. About 30% (96) of the study participants had comorbidities. Overall, 67.4% (217) of the participants suffered from AEFI. Of them, immediate reactions were reported by 18.3% (59) and 10.2% (32) of the participants after the first and second doses, respectively. A total of 0.9% (3) of the participants had immediate allergic reactions. The most common local and systemic AEFIs were pain at the injection site and extreme tiredness. AEFIs were found to be mild and with a probable association with vaccination as per the WHO scale. The number of females experiencing AEFIs was found to be higher when compared with males for both local and systemic reactions. There was a statistically significant increase in the number of individuals experiencing general adverse effects following the first dose of CovishieldConclusionBased on our sample, the study reflects that COVID-19 vaccination causes mild AEFI in most vaccine recipients. It also provides an insight that reporting of AEFI is very low. It is, therefore, important to take up more awareness campaigns about reporting of AEFIs through the COVID Vaccine Intelligence Network (CoWIN) portal. TM  and CovaxinTM . The vaccines were in phase III clinical trials [Adverse events following immunization (AEFIs) are defined as any untoward medical occurrence that follows immunization and that does not necessarily have a causal relationship with the usage of a vaccine. The adverse event may be any unfavorable or unintended sign, abnormal laboratory finding, symptom, or disease . In Indil trials ,3.TM, and then, CovaxinTM was made available. From March 2021, the second phase of vaccination was started. Vaccines were available first for people aged above 60 and above 45 with comorbidities. This was expanded on April 1, 2021, to cover everyone above 45 years. In the third phase, vaccines were made available for people above 18 years of age. The vaccination program started at the immunization clinics at hospitals, followed by vaccination drives hosted at outreach sites. The guideline document released by the Government of India mentioned management plans for AEFI and recording of the same through the COVID Vaccine Intelligence Network (CoWIN) software [Initially, in the first phase, the country vaccinated people at the highest risk of exposure, such as healthcare and frontline workers, on priority with CovishieldThere were circulars issued by the Pharmacovigilance Program of India (PvPI) to the adverse drug reaction monitoring centers (AMCs) to actively monitor and report coronavirus disease 2019 (COVID-19) vaccine-related AEFIs. The guideline suggested that the AEFIs need to be updated through VigiFlow®. For nonserious reactions, the same should be reported by filling up the suspected Adverse Drug Reaction (ADR) reporting form through VigiFlow®. Serious ones need to be updated through ADR forms to PvPI through VigiFlow®, as well as to the National Coordination Center (NCC)-PvPI by email after filling up the AEFI case notification form. AMCs were also directed to report the cases to the District Immunization Officer or State Expanded Program of Immunization Officer -7.The WHO COVID vaccine safety surveillance manual recommends active and various passive systems to monitor AEFIs. This is to ensure vaccine safety and generate data on the overall short-term and long-term effects . PreviouWith this background, this cross-sectional survey was taken up to assess the self-reported AEFIs of COVID-19 vaccines in select apartment complexes in and around Whitefield, Bangalore, India.It was a cross-sectional, questionnaire-based online survey. It was conducted over a period of four months between July 2021 and October 2021. It was approved by the institutional ethics committee of Vydehi Institute of Medical Sciences and Research Centre, with reference number VIEC/2021/APP/009. Confidentiality was ensured so that only authorized persons had access to the data. The study tool was a Google form questionnaire that was distributed to the residents via emails through the managing committees of the apartment complexes and personal messages through known contacts. The inclusion criteria were vaccinated residents of large apartment complexes who received at least one dose of vaccine that was approved by regulatory authorities in India. The Google form had an introductory section explaining the study and an option to indicate consent. The exclusion criteria included those who received vaccines not approved in India (nonresident Indians) and those who were unaware of the type of vaccine they received. The questionnaire was constructed based on a modified version of the screening questionnaire for adult immunization . The queA pilot survey with 20 participants was first conducted for the purpose of calculating the sample size. It was found that 70% (14) of the vaccinated individuals had AEFIs. Considering the confidence interval at 95%, precision at 5%, and prevalence at 70%, the minimum recommended sample size was derived at 320 (N = Z2pq/d2). It was decided to close the questionnaire link once the desired sample size was achieved.Baseline data were assessed using descriptive statistics. All quantitative variables are presented as means and standard deviations, and all qualitative variables are presented as frequencies and percentages. For the comparison of categorical variables, the chi-square test was used. Data were entered into Microsoft Excel  and analyzed using SPSS version 20.00 .Demographic characteristics2. Regarding professional status, 67.7% (218) were non-frontline workers and 32.3% (104) were frontline workers. Of the participants, 96.5% (311) completed both doses, and 3.5% (11) of them completed only one dose of vaccine. The results are presented in Table The total number of participants in the study was 322. Of the 322 participants, 37.6% 121) were males and 62.4% (201) were females. The mean age of the participants was 34.9 ± 12.4 (mean ± SD) years. Of the participants, 3.4% (11) were senior citizens (60 years or above) who participated in the study. Of the participants, 39.8% (128) were between 18 and 30 years, 28.6% (92) were between 31 and 40 years, 23.3% (75) were between 41 and 50 years, and 4.9% (16) were between 51 and 60 years. The mean BMI was 25.2 ± 4.4 (mean ± SD) kg/m21 were mComorbiditiesAbout 30% (96) of the study participants had comorbidities. Around 10% (25) of them were found to have diabetes, 11.2% (36) have hypertension, 3.1% (10) have a thyroid disorder, 0.9% (3) have respiratory disorders, and 0.3% (1) had hypersensitivity reactions to COVID-19 vaccination. The detailed list and frequency of the comorbidities are presented in Table Type of vaccineTM and 22.1% (71) received CovaxinTM. The details are shown in Table Of the participants, 77.9% 251) received Covishield receivedVaccination siteOf the participants, 65.2% (210) received the shot at hospitals, 14.3% (46) at their apartment complex vaccination drives, 13.6% (44) at drives coordinated at workplaces, 0.9% (3) at primary health centers (PHCs), 0.3% (1) at church complexes, and the remaining 5.5% (18) at other sites such as Bruhat Bengaluru Mahanagara Palike (BBMP) office and community halls of residential areas.Diagnosis of COVID-19 post-vaccinationDuring the study duration, 5.9% 19) of the participants were diagnosed with COVID-19 post-vaccination. Among them, 15.8% (3) required hospitalization, with 10.5% (2) of them requiring oxygen. The results are shown in Table 9 of the AEFIOverall, 67.4% (217) of the participants suffered from AEFI. Of them, immediate reactions within 30 minutes of the vaccine were reported by 18.3% (59) and 10.2% (32) of the participants after the first and second doses, respectively. The most common reactions were extreme tiredness, followed by pain at the injection site. A total of 0.9% (3) of the participants had immediate allergic reactions.Of the total participants, 63.6% 204) had local reactions following the first dose, and 46.3% (144) had local reactions following the second dose. The most common local reaction was pain, followed by swelling and weakness of the arm. Systemic reactions were reported by 71.4% (230) and 48.5% (151) of the participants, respectively, following the first and second doses. The most common systemic reaction was generalized weakness, followed by fever, headache, chills, dizziness, somnolence, and loss of appetite. The AEFIs included gastrointestinal disorders , nervous system disorders , skin and subcutaneous tissue disorders , musculoskeletal and connective tissue disorders (body pain and pain in extremity), and general and administration site disorders . The types of local and systemic reactions with prevalence following the first and second doses are presented in Table 04 had loAssociation of AEFI with gender, BMI, and types of vaccineTM when compared with CovaxinTM. There was a statistically significant increase in the number of individuals experiencing general adverse effects following the first dose of CovishieldTM when compared with CovaxinTM. There was no statistically significant difference in the number of participants experiencing local and systemic reactions following the second dose. The results are shown in Table The number of females experiencing AEFI was found to be higher when compared with males for both local and systemic reactions. The difference was, however, not statistically significant. There was no correlation between BMI and the total number of adverse events . The number of participants experiencing local and systemic reactions following the first dose was higher with CovishieldPharmacotherapy for AEFIOf the participants, 71% (154) who experienced AEFI used tablet paracetamol (500/650 mg), and 1.8% (4) used other medications including herbal products, ice packs, antibiotics for hard lump, and mometasone cream. The remaining 27.2% (59) did not require any medication.Reporting of AEFI and causality analysisOut of 67.4% (217) of participants who had AEFI, 19.8% (43) reported to the doctor, 3.7% (8) reported to PvPI, and 76.5% (166) mentioned that they did not report their reaction. All AEFIs were analyzed using the WHO-Uppsala Monitoring Centre (UMC) scale. They were found to have a probable association with vaccination. None were serious requiring hospitalization.In this survey, we aimed to analyze COVID-19 vaccination safety in a select population of Bangalore, India. The participants belonged to apartment complexes located within a 10 km radius of the institution. This was the criteria laid down by the ethics committee, with the idea of monitoring the population who might have received vaccination at the institution and around Whitefield area. This may be also because the adverse drug reaction monitoring center (AMC and PvPI) that functions from the institution supports the nearby peripheral hospitals toward routing their ADR/AEFI to PvPI. The population was targeted toward apartment complexes as request could be forwarded through the MCs, and data could be generated outside the functionality of the hospital. Also, previous studies were conducted mostly on healthcare workers and from AMCs in India ,10.TM or CovishieldTM. This ensured no incomplete responses. It also ensured that the study is conducted on COVID-19 vaccines that received EUA in India. The responses were disabled once the target sample size was reached.The survey was conducted through validated questionnaire uploaded at Google Forms. Participation was voluntary. All information was mandatory; only after responding to a question could the respondents move on to the next. The participants could respond to further questions only if they selected option for vaccine as Covaxin2. The majority of the participants were between 18 and 30 years. The results coincide with previous studies where majority participants were females (62.4% versus 37.6%), and females had more AEFI compared with males. Also, among the survey participants, the majority (39.8%) were 20-30 years old, and a smaller number (8.4%) were above 50 years [The COVID-19 vaccination drives in India were arranged at various sites. The participants of this study reside in apartment complexes. They received their vaccines at various sites, such as hospitals, apartment complexes, primary health centers, workplaces, community centers, and church complexes. Among the respondents, 37.6% 121) were males and 62.4% (201) were females. The mean age of the participants was 34.9 ± 12.4. The mean BMI was 25.2 ± 4.4 (mean ± SD) kg/m50 years ,11,18. A1 were maTM (77.9% versus 22.1%). Previous studies also had more participants who received CovishieldTM. This may be because of the fact that CovishieldTM was available at many centers in India compared with CovaxinTM [In this study, more participants received CovishieldTM .TM as compared with CovaxinTM. Till date, there are no comparative studies of AEFIs of these two vaccines. In this study, also, data is based on reporting by participants and in a specific population. Hence, generalized conclusions cannot be drawn. Also, any investigations into the role of active ingredients toward AEFIs are beyond the scope of this study.In this study, AEFIs were observed more following the first dose of both vaccines compared with the second dose. The results are similar to previous studies ,10. AlsoRegarding AEFIs, <1% of the participants (0.3%) reported immediate hypersensitivity reaction, and the common localized reactions were pain (59%) and swelling 12.4%). This is similar to previous studies. Also, pain at the site of injection was the most commonly reported adverse event in clinical trials .4%. This-20. The In the study, the majority of the participants (71%) with AEFIs resorted to tablet paracetamol (500/650 mg) for their symptoms. Out of 67.4% (217) participants who had AEFI, 19.8% (43) reported to the doctor, 3.7% (8) reported to PvPI, and 76.5% (166) mentioned that they did not report their reaction. It is worthwhile to note that none of them reported through CoWIN. Also, the majority of participants did not report their reaction. Our results coincide with a previous study that also detected low reporting and that 74.66% of the subjects were not aware of adverse event reporting . TherefoThis study was conducted in participants who received the questionnaire and volunteered to respond. Although it was conducted at the community level, we could have possibly skipped those hospitalized or experiencing serious AEFIs. Also, this was conducted on residents of housing complexes. The information that we acquired was based on subjective responses from the population rather than actual clinical assessment. The age range of the respondents was relatively wide, but it did not cover pediatric population as vaccination for COVID-19 was not available below 18 years. Very recently, the Government of India opened up vaccination of children above 15 years. Thus, a long-term study including pediatric population and various sociodemographic profiles of the community will draw more light on long-term AEFIs, if any, of COVID-19 vaccination.TM and CovaxinTM.Our study confirmed the facts available from clinical trial data that available COVID-19 vaccines under EUA are safe. AEFIs were more observed in females, and there were no significant differences in AEFIs between first and second doses and between Covishield


Rising availability of medical imaging exams in the emergency room potentially leads to an increase of ileitis findings by imaging in a context of gastrointestinal symptoms. However, it can be difficult to determine the clinical significance of this radiological finding in an acute consultation setting and to establish the relevant investigations.The aim of this study is to describe the current management and the long-term outcome of patients with diagnostic of acute ileitis on imaging during an emergency consultation in our center, Centre Hospitalier Universitaire de Sherbrooke(CHUS).We performed a retrospective study of all patients diagnosed with ileitis by abdominal ultrasound or computed tomography (CT scan) during a visit in our emergency department over the years 2010 and 2017. Patients with previous diagnosis of Crohn disease were excluded. Data collected were clinical, radiological and endoscopic at diagnostic and over at least 3 years following the initial visit.Yersinia enterocolitica and Campylobacter jejuni. 13% received a diagnostic of Crohn disease. 20% of ileitis remained undetermined. Among these, there was a case of Crohn’s disease which was eventually diagnosed 2 years later. The initial factors associated with a diagnosis of Crohn’s disease were family history of inflammatory bowel disease (OR 6.17 95% CI 1.67 to 22.781 p = 0.006), extra-digestive manifestations (OR 23.31 95% CI 2.255 to 240.92 p = 0.008), discontinuous impairment at initial imaging (OR 19.8 95% CI 4.284 to 91.52 p = 0.000), presence of stenosis at initial imaging (OR 14.429 95% CI 1.227 to 169.68 p = 0.034), the presence of abscess or collection on imaging (OR 11.54 95% CI 1.76 to 75.63 p = 0.011) and wall thickness in mm (1.22 95% CI 1.06 to 1.40 p = 0.005).A total of 118 files were reviewed. The initial imaging modality was 43% ultrasound and 57% CT scan. 36% of patients had an ileocolonoscopy within one month of the initial visit. Of these, 60% demonstrated macroscopic endoscopic abnormalities. 51% of patients had follow-up imaging within 3 months of the initial consultation. 64% of these images demonstrated persistence of pathological changes in the ileal region. Only 48% had a stool culture at diagnosis. 72% of patients met a gastroenterologist and 45% saw a general surgeon. The most common cause of ileitis was an infectious origin at 44% predominantly with Our study shows that the majority of acute ileitis found on imaging are of infectious origin. A portion of acute ileitis corresponded to the initial presentation of Crohn’s disease. Thus, we believe that it is preferable to offer at least clinical follow-up to patients with acute ileitis on imaging and to consider additional investigation by imaging and / or colonoscopy when symptoms persist and this particularly in presence of factors associated with Crohn’s disease.None


Escherichia coli (STEC) infection is controversial.The role of antibiotics in the treatment of Shiga toxin-producing To evaluate the association between treatment  for STEC infection and hemolytic uremic syndrome (HUS) development.We performed a population-based matched case-control study using the data from the National Epidemiological Surveillance of Infectious Diseases (NESID) between January 1, 2017 and December 31, 2018. We identified all patients with STEC infection and HUS as cases and matched patients with STEC infection without HUS as controls, with a case-control a ratio of 1:5. Further medical information was obtained by a standardized questionnaire. Multivariable conditional logistic regression model was used.7760 patients with STEC infection were registered in the NESID. 182 patients with HUS and 910 matched controls without HUS were selected. 90 patients with HUS (68 children and 22 adults) and 371 patients without HUS (266 children and 105 adults) were included in the main analysis. The matched ORs of any antibiotics and fosfomycin for HUS in children were 0.56 (95% CI 0.32–0.98), 0.58 (0.34–1.01). The matched ORs for HUS were 2.07 (1.07–4.03), 0.86 (0.46−1.61) in all ages treated with antidiarrheal agent and probiotics.Antibiotics, especially fosfomycin, may prevent the development of HUS in children, while use of antidiarrheal agents should be avoided. Escherichia coli (STEC) may cause hemorrhagic colitis and hemolytic uremic syndrome (HUS), which is characterized by microangiopathic hemolytic anemia, thrombocytopenia, and renal insufficiency ), physician’s refusal to cooperate (16 [8.8%]), failure to fulfil the precise diagnostic criteria (5 [2.7%]), and missed mandatory data (5 [2.7%]). A total of 539 controls fulfiling the following criteria were excluded from the study: no response (384 [42.2%]), physician’s refusal to cooperate (106 [11.6%]), diagnosis of HUS (12 [1.3%]), asymptomatic carrier (33 [3.6%]), and missed mandatory data (4 [0.4%]). Therefore, 90 (49%) cases and 371 (41%) controls were included in the final analyses .P < .001). Similarly, the frequency of Shiga toxin 1 detection was significantly lower in cases than in controls (P < .001). Serotype O157 was significantly more frequently detected in cases than in controls (P < .001), and no patient with serotype O26 developed HUS (P < .001). The rate of complications and death were significantly higher in cases than in controls  (ctively) . Among tctively) . In contadj 2.07 [1.07–4.03], 2.65 [1.21–5.82], respectively). The use of probiotics was not associated with risk of HUS in any age group.In separate analyses of all ages, and in children, there was significant association between serotype O157 and the development of HUS by univariable conditional logistic regression analyses Click here for additional data file.S1 Dataset(XLSX)Click here for additional data file. 3 Nov 2021PONE-D-21-32011Interventions for Shiga toxin-producing Escherichia coli gastroenteritis and risk of hemolytic uremic syndrome: a population-based matched case control studyPLOS ONEDear Dr. Miyairi,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.The manuscript focuses on a topic of potential interest. However, the manuscript has several shortcomings that preclude sound conclusions. To mention some of them, i) concern about the novelty of the study; ii) need to address in the discussion the nature of bactericidal versus bacteriostatic antibiotics; iii) need to provide in the tables the use of anti-diarrheal agents and antibiotics within distinct groups of patients; iv) unclear whether in cases treatments were counted only when they were administered before the development of HUS and whether this was comparable with the control group; v) need to elaborate on the time window of fosfomycin treatment  in children with STEC-HUS, and to clarify which  is the effect of fosfomycin at later time points of treatment; vi) unclear in figure 1 what is the reason for exclusion of 6668 not matched controls; vii) concern about the fact that in Table 2 cases and control cohorts are not always comparable; viii) unclear whether the observed associations are also present when comparing Stx2 infected cohorts or LPS O157 positive cohorts; ix) concern about the fact that authors’ data do not support the statement reported in lines 328-329; x) need to elaborate on the molecular mechanism of the beneficial effect of fosfomycin in STEC-HUS patients; xi) unclear whether there is any information available about the excluded patients to know if they are systematically different from those patients who were included in the analysis; xii) unclear whether the use of antibiotics look bad because they are given to sicker people, or they are bad even in equivalently sick people; xiii) need to clarify their interpretation of the difference between the unadjusted and adjusted ORs; xiv) concern about the fact that beta lactams are actually worse in adults.plosone@plos.org. 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Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.Reviewer #1: YesReviewer #2: YesReviewer #3: Yes2. Has the statistical analysis been performed appropriately and rigorously?Reviewer #1: YesReviewer #2: I Don't KnowReviewer #3: Yes3. Have the authors made all data underlying the findings in their manuscript fully available?The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). 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You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: PLOS One manuscript STEC-HUS and fosfomycin:The manuscript by Myojin et al. entitled “Intervention for Shiga toxin producing Escherichia coli gastroenteritis and risk of haemolytic uremic syndrome: a population-based matched case control study (reference PONE-D-21-32011)” reports on the role of antibiotics in the treatment of Shiga toxin-producing E. Coli (STEC) infections. Authors evaluate the association between treatment  for STEC infection and HUS development. A population based matched case-control study was performed with the data from NESID from 2017 and 2018. In this period 7760 patients with STEC infection were registered. The main analysis was executed with 90 patients with HUS and 371 patients without HUS. The patient cohort is impressive and the study has been performed adequately. Important information for the clinical care of STEC HUS patients is reported. Antibiotics  may prevent the development of HUS in children and the use of antidiarrheal agents should be avoided. Next issues need to be addressed:1.)Line 179: In cases treatments were counted only when they were administered before the development of HUS? Was this comparable with the control group? This may include bias in the data set?2.)Authors should elaborate on the time window of fosfomycin treatment in children with STEC-HUS? What is the effect of fosfomycin at later time points of treatment?3.)Figure 1: What is the reason for exclusion of “6668 not matched controls”. Please specify.4.)Table 1: You describe 182 HUS patients. In the age-distribution part only 180 patients are reported for all ages? Two patients are lacking?5.)Table 2: Cases and control cohorts are not always comparable . Are observed associations also present when comparing Stx2 infected cohorts or LPS 0157 positive cohorts?6.)Line 328-329: “fosfomycin appears to be beneficial in STEC HUS patients and may avert HUS development, especially if administered early in course of illness”. Do your data also support this statement? Can you improve your illustration to support this statement?7.)The authors should elaborate on the molecular mechanism of the beneficial effect of fosfomycin in STEC-HUS patients .Advise: Moderate revision.Reviewer #2: The authors studied the association of several factors with the occurrence of HUS in the setting of STEC infection. Their analysis focused on the use of antidiarrheal drugs and antibiotics. They show that the use of antidiarrheal and the b-lactams increase the risk of HUS in this setting whereas fosfomycin decreases this risk. The main issue I have with this study is its rather limited novelty, as several previous studies had assessed this question, as stated by the authors.a) The nature of bactericidal versus bacteriostatic antibiotics should be addressed in the discussion, as the lysis of bacteria  may contribute to the spread of verotoxin and hence to the onset of HUS.b) The use of antidiarrheal agents and antibiotics within distinct groups of patients is not shown in the tables.Reviewer #3: A very interesting and well written paper. The early treatment of HUS is a clinically important topic.As this is a reportable condition in Japan, the likelihood of there being a large number of unreported cases that would be missing from this type of analysis is low. The conclusions are supported by the data, but are hampered by the small sample size. In particular, as the authors point out, about half of the HUS cases were not included in the study, mostly due to lack of response from the physician. My question is whether there is any information available about these excluded patients to know if they are systematically different from those patients who were included in the analysis?It is interesting that the OR for the use of the individual classes of antibiotics tend to lose their significance in the adjusted analyses. My understanding of why the authors did these analyses was to try to blunt the effect of the presenting characteristics that influence the physician decision to give antibiotics . The authors need to be clearer about their interpretation of the difference between the unadjusted and adjusted ORs. For example, the difference in the adjusted and unadjusted ORs for beta lactam use in adults looks important to me. I’m not convinced that they are actually worse in adults. The authors should be clear about which analysis they put the most weight upon. I don’t see that same difference in adjusted and non-adjusted ORs for antidiarrheal agents, which generally look bad by either analytic technique.6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.Reviewer #1: NoReviewer #2: NoReviewer #3: Nohttps://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  3 Dec 2021Response to reviewers and editorsWe wish to express our appreciation to the reviewers and editors for their insightful comments, which have helped us significantly improve the paper. We have addressed your comments with point-by-point responses, and revised the manuscript accordingly.Reviewer #1Comment 1: Line 179: In cases treatments were counted only when they were administered before the development of HUS? Was this comparable with the control group? This may include bias in the data set?Response 1: We thank the Reviewer for this pertinent comment. As we described in “Outcome, exposures, and potential confounders” section (Lines 179-180), treatments were counted only when they were administered before development of HUS in cases. Due to the nature of the case control study, controls did not receive any exposure of interest. In general, case control studies are prone to recall bias. The data collection in our study was a retrospective chart review from participating physicians. They were asked to provide information on all antibiotics, antidiarrheals, and probiotics used during the course of the disease. Subsequently, only drugs used before the onset of HUS were counted as exposures in the cases. Therefore, recall bias by respondents was considered to be minimal.We have added following sentences as one of the limitations (Lines 409-414).“Fourth, case control studies are prone to recall bias in general. The data collection in our study was a retrospective chart review from participating physicians. They were asked to provide information on all antibiotics, antidiarrheal agents, and probiotics used during the course of the disease. Subsequently, only drugs used before the onset of HUS were counted as exposures in the cases. Therefore, recall bias by respondents was considered to be minimal.”Comment 2: Authors should elaborate on the time window of fosfomycin treatment in children with STEC-HUS? What is the effect of fosfomycin at later time points of treatment?Response 2: A previous study that examined the causal effects of fosfomycin on the development of HUS concluded that the risk was reduced when fosfomycin was administered at an earlier phase of illness (as we explained in Lines 333-336). For this reason, we also examined the association between the administration of fosfomycin within five days of onset and the development of HUS, but we did not include the results in our first submission. This was because we did not calculate the sample size beforehand for this subgroup analysis, so we considered it difficult to interpret the results. Based on the reviewer's comments, we have added the results of the analysis to Table S4 (shown below). In order to avoid deriving arbitrary results, the covariates used in the multivariate analysis are the same as those used in the main analysis. In each age group, there was no statistically significant result in either univariate or multivariate analysis. It is difficult to discuss the effectiveness of early administration of fosfomycin in this study, and we consider that further research is necessary.“Table S4. Univariable and multivariable conditional logistic regression analysis to assess the effect of the timing of fosfomycin use within five days of illness on HUS development. Matched OR (95% CI) Matched OR (95% CI) Cases Controls Unadjusted P value Adjusted P valueAll ages 32/90 147/371 0.76 (0.48-1.19) 0.227 0.85 (0.53-1.36) 0.499Children 24/68 125/266 0.67 (0.41-1.11) 0.124 0.77 (0.45-1.29) 0.315Adults 6/22 20/105 1.23 (0.47-3.20) 0.673 1.19 (0.38-3.76) 0.764Unadjusted matched odds ratios were calculated by univariable conditional logistic regression analysis. Adjusted matched odds ratios were calculated by multivariable conditional logistic regression analysis using the following covariates: age, sex, area, presence of bloody stool, initial white blood cell count, initial C-reactive protein level.CI, confidence interval; HUS, hemolytic uremic syndrome; OR, odds ratio”We have added a reference to Table S4 in “Results” section as follows (Lines 318-321).“Additionally, we also evaluated the time-related effect of fosfomycin administration on development of HUS within first five days of STEC infections. In the analysis of all ages, adults and children, there was no significant association between the timing of fosfomycin administration and development of HUS (see Table S4).”Comment 3: Figure 1: What is the reason for exclusion of “6668 not matched controls”. Please specify.Response 3: This study is a matched case control study. As we described in the section of “Data collection”, cases were selected from patients with a record of HUS diagnosis in the NESID, and controls were selected from patients without a record of HUS who were matched to cases with a case-control ratio of 1:5. Therefore, 6668 were not matched as controls. We have modified Figure 1 to make this flow easier to understand from:toComment 4: Table 1: You describe 182 HUS patients. In the age-distribution part only 180 patients are reported for all ages? Two patients are lacking?Response 4: We have checked the original data and found that it was a transcription error for the age group 0-6, so we have corrected it. The following table underlines the part that has been changed. We appreciate the reviewer pointing this out.Table 1 (modified).  Group, no. (%) NESID, n (%) Matched controls, n (%) Analysis dataset, n (%) HUS Non-HUS Cases Controls All 182 (100) 7578 (100) 910 (100) 90 (100) 371 (100)Sex  Female 114 (62.6) 4231 (55.8) 570 (62.6) 57 (63.3) 213 (57.4)Age, years  0–6 92 (50.5) 1540 (20.3) 460 (50.5) 50 (55.6) 196 (52.8) 7–15 28 (15.4) 871 (11.5) 140 (15.4) 18 (20.0) 70 (18.9) 16–64 41 (22.5) 4173 (55.1) 205 (22.5) 18 (20.0) 72 (19.4) ≥65 21 (11.5) 994 (13.1) 105 (11.5) 4 (4.4) 33 (8.9)Area  Hokkaido/Tohoku 18 (9.9) 1179 (15.6) 35 (3.8) 8 (8.9) 10 (2.7) Kanto 86 (47.3) 2807 (37.0) 98 (10.8) 41 (45.6) 43 (11.6) Chubu 31 (17.0) 1340 (17.7) 92 (10.1) 19 (21.1) 35 (9.4) Kinki 27 (14.8) 893 (11.8) 217 (23.8) 11 (12.2) 96 (25.9) Chugoku/Shikoku 4 (2.2) 501 (6.6) 113 (12.4) 3 (3.3) 64 (17.3) Kyushu/Okinawa 1 (8.8) 858 (11.3) 355 (39.0) 8 (8.9) 123 (33.2)Comment 5: Table 2: Cases and control cohorts are not always comparable . Are observed associations also present when comparing Stx2 infected cohorts or LPS 0157 positive cohorts?Response 5: The subgroup analysis of only O157 positive cohorts is described in Table S3 in the original manuscript. Analysis of the Stx2 positive cohort was performed, however, we have not shown the results because we judged it to be difficult to interpret the result for the following reasons. First of all, we were not able to create a subgroup of Stx2 positive patients because the notification based on the Infectious Diseases Control Law in Japan includes the following options: Stx1, Stx2, Stx1 plus 2, and serotype unknown. Next, there were many missing data for Stx. Finally, it was difficult to interpret the results due to the small sample size of the subgroup analysis.Comment 6: Line 328-329: “fosfomycin appears to be beneficial in STEC HUS patients and may avert HUS development, especially if administered early in course of illness”. Do your data also support this statement? Can you improve your illustration to support this statement?Response 6:As we described in Response 2, we analyzed the association between early fosfomycin administration and HUS development, however there were no statistically significant results. We have therefore added the following text in “Discussion” (Line 353-362):“We were unable to demonstrate that early fosfomycin administration within two or five days of the onset of gastroenteritis symptoms reduced the risk of developing HUS (see Table S4). This might be due to the use of conditional logistic regression analysis, which resulted in a smaller number of samples belonging to the strata formed by matching factors. We adjusted by confounding factors such as age, gender, presence of bloody stool, initial WBC count and CRP because we considered physicians decide whether to administer antimicrobials in the early stages of disease only by these limited information. Therefore, it is not clear from our study whether fosfomycin should be administered in the early phase of STEC infection.”Comment 7: The authors should elaborate on the molecular mechanism of the beneficial effect of fosfomycin in STEC-HUS patients .Response 7:The reasons for the different results for the different types of antimicrobial agents may be due to the influence of differences in the action of antimicrobial agents in the human body. As pointed out by the reviewer, it is important to consider how the molecular mechanisms of different antibiotics such as beta-lactams and fosfomycin differ. For this reason, we have added the following text to “Discussion“ (Line 366-376).“In a point of view of mechanism of action, both fosfomycin and beta-lactams are bactericidal, and act by inhibiting the synthesis of the peptidoglycan layer of bacterial cell walls. Several studies described the effect of antibiotic administration on toxin production in STEC infections. Class specific ability of certain antibiotics inducing phage replication and Shiga toxin release may explain conflicting results of the associations between different type of antibiotics and HUS development. Bacterial SOS response genes and Stx phage genes are known to be expressed together, and beta-lactams are associated with Stx2 expression in vitro as they are SOS-inducing antimicrobial agents, whereas fosfomycin are not. Although these are plausible hypotheses, further investigation is needed to determine the mechanism by which each antimicrobial agent works in STEC infections.”We have also the following reference.“32. Joseph A, Cointe A, Mariani KP, et al. Shiga Toxin-Associated Hemolytic Uremic Syndrome: A Narrative Review. Toxins (Basel). 2020;12(2):67. doi: 10.3390/toxins12020067. “Reviewer #2Comment 8: The nature of bactericidal versus bacteriostatic antibiotics should be addressed in the discussion, as the lysis of bacteria  may contribute to the spread of verotoxin and hence to the onset of HUS.Response 8: We appreciate the Reviewer’s comment on this point. The reasons for the different results for the different types of antimicrobial agents may be due to the influence of differences in the action of antimicrobial agents in the human body. As pointed out by the reviewer, it is important to consider how the molecular mechanisms of different antibiotics such as beta-lactams and fosfomycin differ. For this reason, we have added the following text to the Discussion (Line 366-376).“In a point of view of mechanism of action, both fosfomycin and beta-lactams are bactericidal, and act by inhibiting the synthesis of the peptidoglycan layer of bacterial cell walls. Several studies described the effect of antibiotic administration on toxin production in STEC infections. Class specific ability of certain antibiotics inducing phage replication and Shiga toxin release may explain conflicting results of the associations between different type of antibiotics and HUS development. Bacterial SOS response genes and Stx phage genes are known to be expressed together, and beta-lactams are associated with Stx2 expression in vitro as they are SOS-inducing antimicrobial agents, whereas fosfomycin are not. Although these are plausible hypotheses, further investigation is needed to determine the mechanism by which each antimicrobial agent works in STEC infections.”We have also added the following reference.“32. Joseph A, Cointe A, Mariani KP, et al. Shiga Toxin-Associated Hemolytic Uremic Syndrome: A Narrative Review. Toxins (Basel). 2020;12(2):67. doi: 10.3390/toxins12020067. “Comment 9: The use of antidiarrheal agents and antibiotics within distinct groups of patients is not shown in the tables.Response 9: We are appreciated to the reviewer’s suggestion. In the original manuscript, we have showed the distribution of the exposures of interest  for all age groups, children, and adults in Figure 2. Similarly, use by antimicrobial class is summarized in Figure 3.Reviewer #3Comment 10: As this is a reportable condition in Japan, the likelihood of there being a large number of unreported cases that would be missing from this type of analysis is low. The conclusions are supported by the data, but are hampered by the small sample size. In particular, as the authors point out, about half of the HUS cases were not included in the study, mostly due to lack of response from the physician. My question is whether there is any information available about these excluded patients to know if they are systematically different from those patients who were included in the analysis?Response 10: We thank the Reviewer for this insightful comment. Since all STEC infections are notifiable in Japan, we agree with the Reviewer's comment that there are probably not many cases that are not reported. It is important for the interpretation of the analysis results that the demographic data of the patients excluded for reasons such as not returning the questionnaires are not significantly different from the demographic data of the patients included in the analysis. The proportions of sex, age, and region of patients with HUS in the analyzed dataset were similar to those of patients with HUS registered in the NESID. This means the baseline characteristics of analyzed dataset is similar to the original data of NESID (as shown in Table 1). We have added following descriptions in the manuscript (Lines 256-257).“Although about half of the cases were not included mostly due to lack of responses, the proportions of sex, age, and region of patients with HUS in the analyzed dataset were similar to those of patients with HUS registered in the NESID.”Comment 11: It is interesting that the OR for the use of the individual classes of antibiotics tend to lose their significance in the adjusted analyses. My understanding of why the authors did these analyses was to try to blunt the effect of the presenting characteristics that influence the physician decision to give antibiotics . The authors need to be clearer about their interpretation of the difference between the unadjusted and adjusted ORs. For example, the difference in the adjusted and unadjusted ORs for beta lactam use in adults looks important to me. I’m not convinced that they are actually worse in adults. The authors should be clear about which analysis they put the most weight upon. I don’t see that same difference in adjusted and non-adjusted ORs for antidiarrheal agents, which generally look bad by either analytic technique.Response 11: We believe that previous studies examining the association between antimicrobial agents and HUS have insufficiently considered the confounding factor of patient severity. In other words, it is important to adjust for the severity of disease, because it is possible that patients with more severe disease initially received antimicrobial agents more frequently, and it is also possible that patients with more severe disease were more likely to develop HUS. Therefore, we used the presence of bloody stool as one of the covariates in the multivariable conditional logistic regression analysis to reflect the severity of disease. As the reviewer commented, there is difference between unadjusted ORs and adjusted ORs, and this was more noticeable in beta-lactams. The following tables show the distribution of covariates used in the multivariate analysis for all ages, children, and adults with and without beta-lactams (Rev-Table 1-3). In all age groups, the beta-lactam group had higher rates of three known risk factors for HUS: white blood cells, CRP, and O-157. This suggests that the ORs that were significant in the univariate analysis became insignificant after adjustment for confounding factors including these factors.Rev-Table 1. The distribution of covariates used in the multivariate analysis for all ages with and without beta-lactams. All Ages with beta-lactams(n=68) without beta-lactams (n=382)Age 0-6 27/68 39.7% 212/382 55.5% 7-15 12/68 17.6% 74/382 19.4% 16-64 16/68 23.5% 72/382 18.8% ≥65 13/68 19.1% 24/382 6.3%Sex Female 46/68 67.6% 217/382 56.8%Area Hokkaido/Tohoku 5/68 7.4% 12/382 3.1% Kanto 13/68 19.1% 69/382 18.1% Chubu 8/68 11.8% 45/382 11.8% Kinki 20/68 29.4% 85/382 22.3% Chugoku/Shikoku 8/68 11.8% 57/382 14.9% Kyushu/Okinawa 14/68 20.6% 114/382 29.8%Bloody Stool 60/68 88.2% 310/382 81.2%WBC>10000/μL 41/64 64.1% 142/276 51.4%CRP>1.2mg/dL 38/63 60.3% 97/271 35.8%O157 52/68 76.5% 221/382 57.9%Antidiarrheal agents 5/65 7.7% 24/361 6.6%Rev-Table 2. The distribution of covariates used in the multivariate analysis for children with and without beta-lactams. Children with beta-lactams(n=68) without beta-lactams (n=382)Age 0-6 27/39 69.2% 212/286 74.1% 7-15 12/39 30.8% 74/286 25.9% 16-64 0/39 0.0% 0/286 0.0% ≥65 0/39 0.0% 0/286 0.0%Sex Female 19/39 48.7% 131/286 45.8%Area Hokkaido/Tohoku 6/39 15.4% 9/286 3.1% Kanto 10/39 25.6% 62/286 21.7% Chubu 5/39 12.8% 34/286 11.9% Kinki 9/39 23.1% 54/286 18.9% Chugoku/Shikoku 5/39 12.8% 38/286 13.3% Kyushu/Okinawa 8/39 20.5% 89/286 31.1%Bloody Stool 35/39 89.7% 224/286 78.3%WBC>10000/μL 24/36 66.7% 99/187 52.9%CRP>1.2mg/dL 17/36 47.2% 54/185 29.2%O157 27/39 69.2% 153/286 53.5%Antidiarrheal agents 3/37 8.1% 15/267 5.6%Rev-Table 3. The distribution of covariates used in the multivariate analysis for adults with and without beta-lactams. Adults with beta-lactams (n=68) without beta-lactams(n=382)Age 0-6 0/29 0.0% 0/96 0.0% 7-15 0/29 0.0% 0/96 0.0% 16-64 16/29 55.2% 72/96 75.0% ≥65 13/29 44.8% 24/96 25.0%Sex Female 27/29 93.1% 86/96 89.6%Area Hokkaido/Tohoku 3/29 10.3% 3/96 3.1% Kanto 3/29 10.3% 7/96 7.3% Chubu 3/29 10.3% 11/96 11.5% Kinki 11/29 37.9% 31/96 32.3% Chugoku/Shikoku 3/29 10.3% 19/96 19.8% Kyushu/Okinawa 6/29 20.7% 25/96 26.0%Bloody Stool 25/29 86.2% 86/96 89.6%WBC>10000/μL 17/29 60.7% 43/89 48.3%CRP>1.2mg/dL 21/27 77.8% 43/86 50.0%O157 25/29 86.2% 68/96 70.8%Antidiarrheal agents 2/27 7.4% 9/94 9.6%From these additional considerations, we have modified the following texts regarding beta-lactams in “Discussion” section from:“The present study confirmed that beta-lactams were associated with detrimental effects in patients with STEC infection, in agreement with previous studies.”to“The present study confirmed that beta-lactams may have detrimental effects in patients with STEC infection, in agreement with previous studies.” (Lines 364-365)and from:“Although the current guidelines do not clearly distinguish risk according to the type of antibiotics, physicians should be aware that beta-lactams are associated with the development of HUS.”to“Although the current guidelines do not clearly distinguish risk according to the type of antibiotics, physicians should be aware that beta-lactams may be associated with the development of HUS.” (Line 376-378)We wish to thank the Reviewer again for his or her valuable comments.Isao Miyairi, MD, PhDDepartment of Pediatrics, Hamamatsu University School of Medicine1-20-1, Handayama, Higashiku, Hamamatsu, Shizuoka 431-3192, Japan+81-53-435-2312 (telephone)+81-53-431-2311 (fax)miyairi@hama-med.ac.jpAttachmentResponse to reviewers.docxSubmitted filename: Click here for additional data file. 18 Jan 2022Interventions for Shiga toxin-producing Escherichia coli gastroenteritis and risk of hemolytic uremic syndrome: a population-based matched case control studyPONE-D-21-32011R1Dear Dr. Miyairi,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.The revised version of the manuscript is definitely improved. 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