Abstract Introduction/Objective Conventional cytogenetic failures can affect hematological cancer diagnosis and prognosis. Resource-constrained regions without contemporary genetic testing facilities may experience this impact more. The effectiveness of this technique is contingent on cultural success, availability of metaphases, and morphological adequacy. The results can be influenced by the underlying diagnosis, inherent biological features of the leukemic clone, sample conditions, and transit time. Culture failure (CF) and suboptimal analysis (SOA) data can identify problems and set standards. Thus, we designed a cohort to find areas of improvement and reduce negative contributing factors, making this cytogenetic technique more accessible and cost-effective. Methods/Case Report A retrospective study was conducted at Cytogenetics laboratory at Indus hospital, Karachi. From January 2021 to March 2023, 1234 blood and bone marrow samples were processed. CF was defined as no growth, whereas suboptimal cases showed a low mitotic index or poor morphology. Data analysis included collection and processing time, sample volume, cell count, specimen type, in-house or out-reach sample, and diagnosis. Armonk, NY-based IBM SPSS 24.0 used to analyze the data. Chi-square used to find association of various factors with karyotyping. A p-value < 0.05 indicated significance. Results (if a Case Study enter NA) Of 1234 samples, 1110 (90%) were bone marrow and 124 (10%) were peripheral blood. There were 32/1234 (2.6%) CF cases. Each CF case was found in bone marrow samples, making the true incidence 32/1110 (2.9%). Constitutional blood tests found no CF in 124 samples. Additionally, chromosomal analysis quality was assessed. SOA occurred in 105/1234 (8.5%) instances, with 58% having poor morphology and 31% having a low mitotic index. Among 137 CF and SOA patients, 134/1110 (12%) were found in marrow and 3/124 (2.4%) in blood. Conclusion Lower CF rates suggest that appropriate standards and quality management may reduce cytogenetic failure rates despite resource constraints and newly established services.
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