Saurav Basu

Posterior Interosseous Artery Flap for Hand Defects

BACKGROUND Reconstruction of soft tissue defects in the hand need an early, single stage and well vascularised cover to achieve the best functional result. Usually a full thickness graft is required since vital structures like tendons, bones and joints are exposed and often there is need for secondary reconstruction. METHODS We managed 12 cases of complex defects over the hand in the last 2 years with the posterior interosseous artery flap. RESULTS In 5 cases the defect was due to blast injury and in 4 because of crush injury. Males predominated in the ratio of 5:1. The defect was most often in the 1(st) web space and the largest flap was 11×8 cm. In all but one case the donor site was covered by split skin graft, which settled well. 2 patients had superficial flap necrosis needing debridement and skin graft. CONCLUSION Flap based on reverse flow in the posterior interosseous artery is a versatile and reliable source for full thickness cover of complex soft tissue defects in the hand.

Knowledge of diabetes among diabetic patients in government hospitals of Delhi

Background: Poor patient knowledge of recommended diabetic self-care practices is a major barrier toward attainment of good glycemic control and prevention of diabetic complications. Materials and Methods: We assessed the knowledge of diabetes self-care practices through a short 7-item pretested questionnaire among diabetes mellitus patients attending special clinics in three government hospitals. Results: The average diabetes knowledge score attained by the patients was 3.79 ± 1.77 (maximum score = 7). Lifetime treatment requirement for diabetes mellitus, plasma glucose levels for good glycemic control, and symptoms of hypoglycemia were correctly reported by 89%, 74%, and 38.5% of the patients, respectively. Low educational status and female gender were significantly associated with poor knowledge of diabetes (P < 0.05). Low level of knowledge of diabetes was a predictor of poor glycemic control but not medication adherence. Conclusion: Knowledge of diabetes in patients attending government hospitals in India is low. Future studies should explore low-cost health education interventions feasible in the Indian health-care context for improving patient knowledge of diabetes.

HIV-Related Knowledge in PLHIV: Issues to Consider in the Indian Context—A Reply to Banagi Yathiraj et al

The article by Banagi Yathiraj et al reports poor knowledge of HIV transmission among People Living with HIV/AIDS (PLHIV) in India which signifies the need for the provision of regular, effective counseling services. As per the guidelines of the National Aids Control Program IV in India, care and support centers (CSCs) are established and linked to Anti Retroviral Therapy (ART) centers for provision of counseling services to PLHIV. ART centers in India provide refills usually lasting for at least 1-month duration which enable PLHIV to participate in regular counseling session that is expected to improve their knowledge of HIV transmission. However, the Banagi Yathiraj’s et al study did not find duration of ART to be associated with HIV-related knowledge in their subjects. This suggests that either counseling sessions were not being conducted or attended regularly or they were ineffective in increasing knowledge of HIV transmission in a majority of the subjects. An accompanying situational analysis of the operational status and referral linkages of ART centers with CSCs along with assessment of the quality of counseling services and the information, education, and communication (IEC) material used should also be considered in future research. Illiteracy was reported as an independent predictor of poor HIV-related knowledge by the Banagi Yathiraj’s et al study. Indeed, the lack of literacy correlates with lower health literacy which undermines patient comprehension of health information imparted during counseling. Thus, the covariate for low educational status when considering disease-related knowledge in patients is more appropriately due to lack of functional literacy as opposed to only illiteracy since the former includes the subset of the patient population who experience challenges in basic reading and comprehension skills which hinder their utilization of the health information (IEC materials) received either from media or during counseling. Furthermore, it has been observed especially in context of low and lower middleincome countries including India that increase in school enrollment does not necessarily translate into favorable learning outcomes, with less progress likely among children in economically and socially disadvantaged families. Nevertheless, the presence of a certain number of years of schooling usually at least until primary school may be considered as an acceptable proxy for functional literacy. The Banagi Yathiraj’s et al study also should have reported the methodology and definition used for assessment of nonadherence to ART. Multiple methods based on self-report, pill counts, and pharmacy records may be used for assessing ART adherence. Furthermore, the definitional cutoff for nonadherence to ART can be set at an adherence rate <80%, <95%, and also <100%. Since the proportion of ART nonadherent PLHIV subjects in the Banagi Yathiraj’s et al study is likely to vary depending upon the method and definition used for assessing ART adherence, it may also influence the outcome of the relationship between ART adherence and HIV-related knowledge.

A comment on “lacunae in noncommunicable disease control program: Need to focus on adherence issues”

Dear Editor, The article by Singh et al. evaluated medical adherence in diabetes and hypertension patients in a clinic setting in the Punjab state.[1] The strength of the study is that it is one of the few studies which reports medication adherence findings among noncommunicable disease (NCD) patients from a small, nonmetropolitan city of India. Nevertheless, I would like to highlight a few methodological concerns regarding the study which can be clarified on by the authors. 1. Reporting of medication adherence – The Singh et al. study assesses medication adherence jointly for two different disease conditions such as diabetes and hypertension. Furthermore, it does not stratify patients as diabetic, hypertensive, or comorbid which is a limitation of their study since it precludes assessment of the extent of adherence for the individual disease conditions. Such an approach should also be avoided since the factors influencing medication adherence in diabetes can differ from other NCD conditions such as hypertension, thyroid disorders, and chronic obstructive pulmonary disease. Poor adherence to antihypertensive medication in diabetes‐hypertension comorbidity has also been previously reported.[2] This could be due to increasing complexity of regimen resulting from a higher pill burden[3] or patient perceived accentuated side effects from a regimen containing both antihypertensives and antidiabetic medications[2] 2. Sample size calculation – The Singh et al. study calculated the sample size based on reported adherence of 40%, but no previous study has been cited by the authors. Appropriate calculation of sample size for a prevalence study for measuring adherence in a population should preferably identify self‐reported adherence from a previous study which uses a similar method for assessment of medication adherence 3. Assessing medication adherence – Several validated methods exist for measuring medication adherence in diabetes patients.[4] In the Singh et al. study, nonadherence was defined as missing a dose of any of the prescribed antidiabetic or antihypertensive medications in the previous 7 days. The high cutoff is required for optimum clinical outcomes in diseases such as HIV‐AIDS and tuberculosis (≥95% and ≥90% adherence rate, respectively) but should be set lower at ≥80% for diabetes.

Appropriately reporting results using the medication subscale of the summary of diabetes self-care activities measure: A comment on Dasappa et al. (2017)

Dear Editor, It is well established that poor adherence to antidiabetic medications in diabetics causes deterioration of glycemic control and accelerates the onset and progression of microvascular and macrovascular complications of diabetes.[1] The study by Dasappa et al. further corroborates that diabetics in socioeconomically disadvantaged communities are at the risk of medication nonadherence.[2] The researchers utilized the medication subscale of the Summary of Diabetes self-care activities measure (SDSCA-MS) developed by Toobert et al. for assessing medication adherence.[3] The scale includes 2 items which query patients regarding their medication intake behavior during the previous 7 days from the day of assessment. The first item of the SDSCA-MS assesses the number of days on which the patient took his prescribed (antidiabetic) medication or insulin, and the second item assesses the number of days on which the patient took the correct number of pills. The response in both the items will yield a number ranging from 0 to 7. The SDSCA-MS score in the study sample should subsequently be reported as mean and standard deviation in the following manner: 1. The SDSCA-MS score can be reported only for the first item (1 item SDSCA-MS) but preferably by averaging responses to both the items (2 item SDSCA-MS)[3] 2. An alternative validated method recommended by Mayberry et al. is to calculate the 1 and 2 item SDSCA-MS scores by averaging responses to the first item and both items, respectively, for each of the antidiabetic medications in the prescribed regimen[4] 3. Observations from literature show that SDSCA-MS scores have been dichotomized into categorical outcomes with a score of <7 defined as nondaily medication adherence while a score of ≤5 signifying <80% adherence defined as nonadherence.[5] In the present study, Dasappa et al. have not reported SDSCA-MS scores in terms of continuous outcomes and arbitrarily defined a diabetic patient who misses even a single dose of his antidiabetic during the previous 7 days as not having good adherence. They further hypothesize that the subjects may be nonadherent due to their inability to afford the medication which cannot be inferred from their observations. This is because patients with SDSCA-MS score of 6 are more likely to be missing medications due to forgetfulness or carelessness compared to those reporting a score of 0 which rather reflects lack of medication possession due to possible inability to afford medications. However, the dichotomous outcome reported in this study classifies a patient reporting an SDSCA-MS score of 0 and another of 6 in the same category.

A comment on Mokabel et al. (2017)

The facility‐based study by Mokabel et al. (2017) shows that a diabetic educational program was effective in increasing type 2 diabetes mellitus (DM) patients’ knowledge of diabetes, adherence to self‐care practices, and health outcomes.[1] These findings corroborate evidence from previous studies and draw much‐needed attention toward prioritizing the inclusion of therapeutic patient education for effective diabetes management.[2] The following is a comment on an omission in the methodology and certain conclusions drawn by the authors.

Evaluating prescription adherence to evidence-based guidelines in diabetes management: a reply to Pingili et al. (2017)

Dear Editor, The study by Pingili et al. evaluated prescription adherence to AACE guidelines in a South Indian tertiary care hospital. The authors assessed the extent to which physician treatment strategies coincide with evidence-based guidelines for diabetes management [1]. Persistently poor glycemic control due to physician failure to intensify the antihyperglycemic treatment in diabetics not meeting their A1c goal increases their risk of adverse health outcomes. The following suggestions are with regard to the methodology employed in the study.

A comment on “nomophobic behaviors among smartphone using medical and engineering students in two colleges of West Bengal” letter by dasgupta et alx. (2017)

Sir, I read the article by Dasgupta et al. who evaluated the prevalence of nomophobic behavior among smartphone using Medical and Engineering students of West Bengal with great interest.[1] The authors show that growing intrusion of smartphones in the lives of young carries with it significant implications for public health. However, I have some concerns regarding the methodology used in this study, the clarification of which should aid future research on this subject. 1. The nomophobia questionnaire (NMP‐Q) developed by Yildirim and Correia was used for the assessment of nomophobia.[2] The authors have just stated that they used classified higher scores as nomophobic for logistic regression analysis. Was a particular cutoff score employed by the authors for categorization of a smartphone user as NMP in this study? 2. Items in the NMP questionnaires such as Q. 4, Q. 8, Q. 10, Q. 12, Q. 13 indicate standard capabilities available in all mobile phones. Furthermore, the first 3 factors in the questionnaire are not necessarily linked to NMP in the Indian context. For instance, students belonging to low‐moderate socioeconomic status lacking gadgets such as laptop, television, or Wi‐Fi in their hostel room could use a low‐cost smartphone as a primary electronic device for accessing information and digital entertainment often on‐line (Q. 2). Smartphone apps permit users to book transport like cabs and find routes on digital maps and users may feel stranded in the former’s absence due to poor quality of public transport (Q. 8). Similarly, lack of telephonic connectivity may be of particularly concern for women students in public spaces due to safety concerns (Q. 15) 3. The authors did not find the duration of smartphone usage to be a significant predictor of nomophobia. However, this might be since the authors assessed absolute duration of smartphone usage in the students instead of ascertaining excessive use. A student who uses a smartphone in his hostel‐room to watch videos will have higher duration of smartphone use compared to his peers who use alternate electronic devices like televisions or computers for the same function. On the other hand, another student who habitually checks social networks during his classes or late at night getting fewer hours of sleep in turn is likely to have NMP but exhibit similar duration of smartphone usage as the former 4. Smartphone users may exhibit addiction traits such as behavior and compulsive usage.[3,4] The authors have discussed that nomophobics slept with their mobiles and indulged in compulsive checking suggesting addiction but did not evaluate these traits among their subjects. This could be a study limitation since other validated instruments could be used to identify addiction‐like behavior in smartphone users. Aggarwal et al. who developed a 23‐item questionnaire with most items designed for assessing one or more of the ICD‐10 diagnostic criteria for addiction which includes intense desire, impaired control, withdrawal, tolerance, decreased alternate pleasure, and harmful use.[3] The 33‐item smartphone addiction scale developed by Kwon et al. evaluates six factors relating to smartphone addiction; daily‐life disturbance, positive anticipation, withdrawal, cyberspace‐oriented relationship, overuse, and tolerance.[4]

Addiction-like behavior associated with mobile phone usage among medical students in Delhi

Background: Mobile phone addiction is a type of technological addiction or nonsubstance addiction. The present study was conducted with the objectives of developing and validating a mobile phone addiction scale in medical students and to assess the burden and factors associated with mobile phone addiction-like behavior. Materials and Methods: A cross-sectional study was conducted among undergraduate medical students aged ≥18 years studying in a medical college in New Delhi, India from December 2016 to May 2017. A pretested self-administered questionnaire was used for data collection. Mobile phone addiction was assessed using a self-designed 20-item Mobile Phone Addiction Scale (MPAS). Data were analyzed using IBM SPSS Version 17. Results: The study comprised of 233 (60.1%) male and 155 (39.9%) female medical students with a mean age of 20.48 years. MPAS had a high level of internal consistency (Cronbachs alpha 0.90). Bartletts test of sphericity was statistically significant (P < 0.0001), indicating that the MPAS data were likely factorizable. A principal component analysis found strong loadings on items relating to four components: harmful use, intense desire, impaired control, and tolerance. A subsequent two-stage cluster analysis of all the 20-items of the MPAS classified 155 (39.9%) students with mobile phone addiction-like behavior that was lower in adolescent compared to older students, but there was no significant difference across gender. Conclusion: Mobile phone use with increasing adoption of smartphones promotes an addiction-like behavior that is evolving as a public health problem in a large proportion of Indian youth.

Drug-resistant tuberculosis: Response to More et al. (2017)

Dear Editor, I read with great interest the article by More et al. describing the profile of drug‐resistant tuberculosis (DR‐TB) patients referred to the State TB Training and Demonstration Center, Maharashtra (STDC).[1] The study reported that most DR‐TB were male and below 35 years of age which highlights the enormous threat posed by the increasing burden of DR‐TB on India’s vast demographic dividend. I have the following queries and request for clarifications on a few key observations from the study.