MétaCan
Menu
← Back to cohort
Record W6931896131 · doi:10.5281/zenodo.8004600

Effect of Glycemic Control on Urinary Tract Infections in Type 2 Diabetic Mellitus

2023· article· en· W6931896131 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsDiabetes mellitusGlycemicUrinary systemAsymptomaticType 2 Diabetes MellitusType 2 diabetesUrineAsymptomatic bacteriuriaHemodialysis

Abstract

fetched live from OpenAlex

Introduction Type 2 Diabetes Mellitus (DM) is frequently associated with increased risk of urinary tract infection [1-4]. Poor metabolic control in diabetes along with impaired immune system, microvascular disease in kidney and diabetic cytopathy contribute to it [5-8]. Severe form of urinary tract infections like emphysematous pyelonephritis is more frequent in diabetics [9]. Bacterial UTI are common in diabetics and needs aggressive treatment [10]. E. coli is the most common organism causing UTI, other pathogens that are highly prevalent in diabetics are Klebsiella, Enterococci, Pseudomonas, and Proteus mirabilis, group B Streptococci and fungal infections [11,12]. Improved glycemic control in diabetic cases helps in controlling UTI and proper and accurate screening for UTI in diabetics helps in avoiding complications [13]. There is limited information on glycemic control and UTI in India, therefore we aim to evaluate the effect of glycemic control on UTI in Type 2 Diabetes patients. Materials and Methods This is a retrospective study that included patients reporting to the Endocrinology and Urology Out Patient Department (OPD) with type 2 diabetes mellitus and symptomatic UTI from January 2021 to October 2022. Type 1 DM, pancreatic diabetes, steroid induced diabetes, and other types of diabetes were excluded. Further patients sterile on urine culture, pregnant female, patients with asymptomatic bacteriuria, patients onper urethral catheter and patients on maintenance hemodialysis were excluded. Information like patient’s age, gender, relevant history, examination, laboratory report and imaging finding were collected from OPD record. Body mass index (BMI, Kg/M2) was calculated by height and weight measurement. The plasma glucose was measured by glucose oxidase method and the HbA1c was measured by Bio-Rad D-10 system using a high-performance liquid chromatography method. DM was diagnosed based on 75-g oral glucose tolerance test (OGTT) and/or glycosylated hemoglobin (HbA1c) or based on record in OPD tickets for previously diagnosed diabetic cases [14]. Patients were divided into two groups based on glycemic control, Group 1: good glycemic control(HbA1C<7%), Group 2: suboptimal glycemic control (HbA1C ≥7%). (14) Midstream urine samples were collected after giving proper instructions. The urine samples were immediately transported to the microbiology laboratory. If the urine specimen was found to be contaminated repeat sample was collected on next day. Smears for Gram's staining, culture and biochemical tests for identifying the species of the pathogens were processed using the standard microbiological procedures. Diagnosis of UTI was made if cultures had >105 colony forming units (CFUs)/mL of a single potential pathogen or two potential pathogens. The presence of yeast in any number was significant. Quantitative variables were expressed as mean±standard deviation and analyzed using independent sample t-test. Qualitative variables were expressed as percentage and was analyzed using Fischer Exact test. P-value <0.05 was considered significant. Results We retrospectively collected and evaluated the data of 156 patients having diagnosis of Type 2 DM with urinary tract infection. Baseline characteristics has been summarized in Table 1. Most common symptoms were dysuria (96.8%), frequency (94.2%) & urgency (84.6%) followed by sense of incomplete voiding (60.8%), fever (55.1%), straining to void (44.9%), abdominal pain (32.7%), urinary incontinence (14.1%) and hematuria (6.4%). Average duration of diabetes was 8.9 ±5.7 years & prevalence of newly diagnosed diabetes was 9.6%. Prevalence of Gram negative, Gram positive and Candida were 71.8, 19.9%& 14.1% respectively (Table 2). In Gram negative, E. coli (67.9%) was most common while in Gram positive, Enterococcus fecalis (70.9%) was most common organism (Table 2). Prevalence of good glycemic control & suboptimal glycemic control was 33.7% & 67.3 % respectively. (Table 3). HbA1C [10.5±1.9% vs 6.1±0.6%, p=0.0001] and random plasma glucose 315±146.7 vs 142±52.6 mg/dL= 0.0001] were significantly more in suboptimal versus good glycemic control. Age [56.2±10.3 vs 45.2±8.2 years, p=0.0001] & White Blood Cell (WBC) [16.8±8.5 vs 13.5±5.6 *103/mm3, p=0.0128] were significantly more in suboptimal glycemic control group versus good glycemic control group. Hemoglobin [9.26±1.9 vs. 10.5±2.2 gm/dL, p=0.0004] and GFR (Glomerular Filtration Rate) [58±25.6vs. 72.2±28.4 ml/minutes/1.73m2, p=0.002] were significantly lower in suboptimal versus good glycemic control group. Acute pyelonephritis was significantly more in suboptimal glycemic control group as compared to good glycemic control group [24.7% vs. 9.8%, p=0.0325]. Cystitis was more common in good versus suboptimal glycemic control but not statistically significant [78.4% vs 67.6%, p=0.19]. Similarly, there was no significant difference in acute prostatitis and emphysematous pyelonephritis in good versus suboptimal glycemic control group (Table 3). Discussion In our study we found increase incidence of UTI in suboptimal glycemic control diabetics as compared to good control diabetics. Previous study in the past have found diabetic women more predisposed to UTI as compared to those not having diabetes [15]. In this study we found E. coli (67.9%) to be the most common Gram-negative organism followed by K. pneumoniae (16.1%) and Psuedomonas aeruginosa (6.3%). E. coli and K. pneumoniae was found to be responsible for about three fourth of gram-negative cases of UTI in Kuwait [13]. Another study found the prevalence of E. coli, K. pneumoniae and P. aeruginosa in 71.3%, 13.5% and 8.8% respectively in type 2 diabetic patients in south India [16]. In Gram positive, we found Enterococcus faecalis was most prevalent (71%) followed by Staphylococcus epidermidis in 22.6 % like another study from south India [16]. We found good glycemic control in one third of the cases and suboptimal glycemic control in two third of cases. Prevalence of good glycemic control has been reported between 13.7 % 2 to 44.8% in different studies in urinary tract infection with diabetic patients [13,16-18]. In our study we found cystitis in 78.4% of cases with good glycemic control as compared to 67.6% of cases of suboptimal glycemic control. Acute prostatitis and emphysematous pyelonephritis were found in 7.8 % and 3.9% respectively in cases of good glycemic control and 3.8% and 3.8%respectively in those having poor glycemic control. Acute pyelonephritis was found in 9.8% of patients with good glycemic control as compared to 24.7% in those with poor glycemic control (p- value 0.0325). In a study by Washington State Health group pyelonephritis was 4.1 times more common in premenopausal diabetic women than in non-diabetic women [19]. Another study reported patients with diabetes mellitus were 3 times more prone to hospitalization for pyelonephritis as compared to those without diabetes [20]. A Canadian study found 6-15 times more hospitalization for diabetic women as compared to non-diabetics and diabetic men needed 3.4-17 times more hospitalization as compared to non-diabetic men [21]. Risk of acute bacterial prostatitis, prostatic abscess has been found to increase in patients of diabetes mellitus [22,23]. In our study we found random blood glucose, HbA1C, age & WBC counts to be significantly higher while hemoglobin and GFR were significantly lower in suboptimal glycemic control group in comparison to good glycemic control group (p-value <0.05). Studies have shown increased blood glucose to be related to higher chances of UTI and bacteriuria [24,25]. On contrary to this, one meta-analysis and systemic review showed that increased blood glucose level was not a significant factor for UTI in diabetic patients [26]. A study done in Type 2 diabetes mellitus in females found age more than 40 years is an important risk factor for UTI [27]. Higher HbA1C has been shown to be strongly associated with risk of CKD [28]. The limitations of our study are retrospective nature, single centre study, small sample size, confounding factor like sex was not analyzed, follow up was not included. Conclusion In type 2 diabetes mellitus, acute pyelonephritis was more common in suboptimal glycemic control group in comparison to good glycemic control. E. coli and Enterococcus fecalis was most common organism in Gram negative and Grampositive bacteria respectively. Age & WBC counts were significantly higher while Hemoglobin and GFR were significantly lower in suboptimal glycemic control group in comparison to good glycemic control group. References 1. Patterson JE, Andriole VT. Bacterial urinary tract infections in diabetes. Infect Dis Clin North Am. 1997 Sep;11(3):735– 50. 2. Joshi N, Caputo GM, Weitekamp MR, Karchmer AW. Infections in patients with diabetes mellitus. N Engl J Med. 1999 Dec 16;341(25):1906–12. 3. Boyko EJ, Fihn SD, Scholes D, Abraham L, Monsey B. Risk of urinary tract infection and asymptomatic bacteriuria among diabetic and nondiabetic postme

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.276
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicPrenatal Screening and Diagnostics→French-language works237,207→