Pakistan BioMedical Journal

Predicting Treatment Resistance in Severe Psychiatric Disorder: A Cross-Diagnostic Analysis of Biopsychosocial Risk Factors in a Pakistani Clinical Cohort

Ayyat Nadeem — 2026-07-31

Severe psychiatric disorders impose a high burden in Pakistan, yet local data on predictors of poor treatment response remain scarce. Objectives: To identify key biopsychosocial correlates of poor treatment response and develop a pragmatic clinical risk-prediction model suitable for resource-limited Pakistani psychiatric settings. Methods: This secondary, retrospective, cross-sectional analysis used a de-identified Pakistani psychiatric dataset (n=764; 409 good, 355 poor responders). Group differences were assessed via Mann-Whitney U and chi-square tests. Multivariable logistic regression identified independent predictors, with performance benchmarked against LASSO regression, Random Forest, and a simplified six-item clinical decision rule. Multicollinearity was checked using variance inflation factors. Results: Poor responders had significantly longer illness duration and higher rates of poor insight, hallucinations, and aggression. Suicidal ideation (adjusted OR=3.84) and speech pressure (OR=3.44) emerged as the strongest independent correlates, while preserved insight was protective (OR=0.33). The logistic model showed acceptable calibration (Hosmer-Lemeshow p=0.401) but explained only 32.4% of the variance. Random Forest achieved the best discrimination (AUC=0.854), modestly outperforming the clinical decision rule (AUC=0.823). Suicidal ideation combined with substance use showed marked synergy (79.1% poor response; OR=5.67). Conclusions: A cross-diagnostic cluster of easily assessable markers—poor insight, suicidality, substance use, and chronicity can inform risk stratification. The simplified decision rule offers a feasible alternative to complex algorithms in overburdened Pakistani psychiatric services, though prospective external validation is essential before clinical implementation.

Identification of Metabolic Phenotypes in Polycystic Ovary Syndrome Using Unsupervised Clustering: A Case-Control Study

Aqsa Haroon — 2026-07-31

PCOS is an endocrine disorder of women. It remains unclear whether adding biomarkers to clinical assessment improves diagnosis, or if androgens explain clinical hirsutism severity. Objectives: To identify metabolic phenotypes via clustering; test if a biomarker panel predicts PCOS better than clinical assessment; and explore the serum androgen-hirsutism correlation. Methods: This retrospective case-control study analyzed Kaggle data (208 PCOS cases and controls). Clinical, biochemical (total/free testosterone, DHEAS, LH/FSH, HOMA-IR, SHBG), and ultrasound (ovarian volume, follicle count) variables were recorded. Logistic regression (clinical vs. full panel) was compared using AUC, DeLong's test, LRT, bootstrap correction, and Hosmer-Lemeshow. K-means clustering (k=2) applied to standardized BMI, HOMA-IR, and SHBG. Pearson correlation assessed FG score. Results: The full model (test AUC 0.596) did not outperform the clinical model (AUC 0.592; DeLong p=0.886; LRT p=0.835). Optimism correction reduced the full AUC to 0.507 versus 0.526 for clinical, with poor calibration (p=0.005). No biomarker independently predicted PCOS. No serum hormone correlated with FG score (|r|≤0.111). Clustering revealed obese/low-SHBG (n=98) and lean/insulin-resistant (n=110) phenotypes, differing in BMI, SHBG, and HOMA-IR (p<0.050), but not testosterone or LH/FSH. Conclusions: Adding biomarkers does not improve diagnosis and is overfitted. Serum androgens do not explain hirsutism. Clustering identifies distinct metabolic subtypes, supporting phenotype-based management.

Prevalence of Biotin Overconsumption for Beauty Purposes Influenced by Social Media: A Cross-Sectional Study

Sidra Khalid — 2026-07-31

Biotin is also commonly consumed in large quantities for cosmetic purposes, although the recommended daily value is just 30 micrograms. Laboratory immunoassays can be interfered with by these high-dose biotin supplements, which may lead to erroneous diagnosis. Social media has been an important place for health information, especially for women under 30. Objectives: To assess the level of biotin excess for beauty in young adult females in Pakistan. And to study its relationship with exposure to social media marketing of nutraceuticals. Methods: The study was conducted in Pakistan with 210 healthy female adults (18-30 years) using a community-based, cross-sectional analytical study in January-March 2026. Data were collected using an online questionnaire sent through social media. Results: People got recommendations from social media influencers (60.0%) before doctors (16.2%). Before using this supplement, most of the participants did not seek doctors' advice. The main reasons for this use were aesthetic benefits, particularly hair growth (35.7%). Biotin consumption was not associated with the source of recommendation (p=0.638). Conclusions: Biotin is an important supplement that plays an important role in the health of young females in Pakistan, and social media has a significant impact on this. The low rate of professional consultation points to a need for better digital health literacy and public health education to encourage safe supplement practices.

Evaluating the Predictive Utility of Demographic, Lesion, and Inflammatory Parameters for Immunotherapy Success in Cutaneous Warts

Sheheryar Ahmad Khan — 2026-07-31

HPV is the cause of cutaneous warts; they're very common and sometimes do not respond to damaging treatments. An alternative treatment is intralesional immunotherapy, but there are no good predictors of clearance that will help in patient selection. Objectives: To assess the ability of baseline demographic, lesion, and inflammatory parameters (wart type, age, sex, wart count, lesion area, treatment duration, and induration diameter) to predict complete clearance, and whether induration diameter is a useful predictive biomarker. Methods: Retrospective analysis of 90 patients treated with intralesional immunotherapy (71 had successful treatment, and 19 failed). Categorical variables were compared using chi-square, continuous variables were compared using the Mann-Whitney U-test, and predictors were identified through multivariate logistic regression. The interaction between age and wart type was tested, and the induration diameter was assessed using ROC curve analysis (Youden index). Results: There were no differences among groups for any variable (categorical or continuous). No association was found between outcome and wart type (p=0.680) or sex (p=0.840), and the median induration diameter was the same across both groups (7.0 mm, p=0.910). Age was near significant (p=0.080). The multivariate model accounted for less than 6% of variance in the outcome (Nagelkerke R²=0.06) and did not have any discriminative power (AUC=0.51). Conclusions: The standard demographic, morphological, and inflammatory parameters, such as induration diameter, were not good predictors of the response to immunotherapy in this dataset, and other molecular or immunological parameters will likely be needed for better patient selection.

Floods, Fevers, and Failed Systems: Building Climate-Resilient Public Health in Pakistan

Riffat Mehboob — 2026-07-31

Pakistan is once again facing a familiar crisis now a days. Since the beginning of the monsoon season in Pakistan on 26 June, 47 people have been reported killed and 123 injured in different provinces due to floods or flash floods. Flash floods have continued along major rivers in Punjab. This comes at a time when the country is still recovering from the 2025 floods that claimed the lives and livelihoods of more than 1037 people and displaced people to the tune of approximately 2.9 million during the period of peak flood [1, 2]. It is no longer an exception, but rather a trend, and in 2022, 2023, 2025 and 2026 significant health emergency conditions were reported due to the flooding events [3].

In each cycle the same direction is taken. Sanitation facilities are washed away and drinking water sources are contaminated by flood water, families are displaced to relief areas, and stagnant water breeds disease vectors [1, 4]. In 2025, floods occurred in Punjab and resulted in more than 3500 reported Dengue cases, which was very high as compared to 2024 and thus a Province-wide Dengue Alert was issued [1]. In the relief camps of flood affected people in all over Punjab, the exposed population continued to be subjected to contaminated water and mosquitoes, which could lead to diarrhea, typhoid, malaria and dengue [2].

The downside of this trend is that it's very costly in terms of unnecessary morbidity. The same fragmented data reporting system could have undercounted similar outbreaks in the subsequent floods in 2022, as researchers have warned [2] and similar cholera and dengue data was recorded in 2022 for the flood alone in Sindh [5]. In addition to floods, Pakistan is experiencing a public health emergency over and over again, but without any reference to the basic needs of the people.

There is further confirmation for this diagnosis given by recent analysis of the 2022 and 2025 floods. Drawing on the disaster management cycle, Akhter et al. found that the existing meteorological, hydrological and disease surveillance data systems were not linked, and that there were gaps in the data information systems, which led to failing forecasting and the lack of timely dissemination of early warning information, leaving high-risk districts unprepared for each flooding season [6]. The findings of these analyses point to the fact that the severity of flooding events does not seem to be the reason for the increasing number of public health crises in the country, but rather the failure to develop institutional capacity following previous public health crises.

It will require an entirely new strategy to end this vicious cycle. Pakistan's health system has been treating the floods as a stand-alone event and has been reacting to outbreaks with spraying of larvicides after the event for the last two years. The missing component is climate-integrated public health infrastructure, including the pre-positioning of vector control and water-testing infrastructure and training of the workforce to view the initial response to flooding and the outbreak response as two sides of the same coin.